A method for fusing multi-source geographical information

Abstract

The present invention discloses a method for fusing multi-source geographic information, which relates to the field of geographic information and solves the problem of poor geographic information fusion effect. The method includes step A1: obtaining the area values of the first to third type regions corresponding to multiple geographic monitoring sub-regions to obtain area data; step A2: obtaining the difference between the first current feature coefficient and the corresponding first historical feature coefficient of multiple geographic monitoring sub-regions to obtain water area feature data; step A3: obtaining the difference in vegetation feature coefficients corresponding to multiple geographic monitoring sub-regions respectively to obtain vegetation feature data; step A4: obtaining the difference in building feature coefficients corresponding to multiple geographic monitoring sub-regions respectively to obtain building feature data; step A5: obtaining regional geographic information update data by fusing the area data, water area feature data, vegetation feature data and building feature data. The present invention can make the process of fusing geographic information more accurate and comprehensive.

Description

Technical Field

[0001] The present invention belongs to the field of geographic information, relates to information fusion technology, and specifically is a method for multi-source geographic information fusion. Background Art

[0002] Existing geographic information fusion methods have the following defects:

[0003] 1. Existing geographic information fusion methods usually set a fixed time period for systematic upgrade of geographic information, without targeted upgrade of small regional ranges according to actual changes in geographic information, which easily leads to low resource utilization efficiency and lack of pertinence;

[0004] 2. Existing geographic information fusion methods mainly rely on remote sensing images for geographic information fusion. Optical sensors are extremely vulnerable to weather conditions during remote sensing. When natural elements such as clouds, fog, and water vapor form obstructions in the signal propagation path, it will lead to inaccurate or even completely covered remote sensing images, resulting in poor accuracy in the process of obtaining geographic information fusion.

[0005] Therefore, we propose a method for multi-source geographic information fusion. Summary of the Invention

[0006] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a method for multi-source geographic information fusion. The present invention is based on marking a geographic monitoring area as the k1st to the kth k geographic monitoring sub-areas, respectively obtaining the area values of the first type of area, the area values of the second type of area, and the area values of the third type of area in each geographic monitoring sub-area to obtain area data, and obtaining the first current characteristic coefficients and the first historical characteristic coefficients corresponding to the k1st to the kth k geographic monitoring sub-areas respectively. By calculating the difference between each first current characteristic coefficient and the corresponding first historical characteristic coefficient, water area characteristic data is obtained. Obtaining the difference in vegetation characteristic coefficients corresponding to the k1st to the kth k geographic monitoring sub-areas respectively to obtain vegetation characteristic data, obtaining the difference in building characteristic coefficients corresponding to the k1st to the kth k geographic monitoring sub-areas respectively to obtain building characteristic data, and dividing the k1st to the kth k geographic monitoring sub-areas into the first change type monitoring sub-areas and the third change type monitoring sub-areas according to the area data, and updating the geographic information of the first change type monitoring sub-areas.

[0007] To achieve the above purpose, the present invention adopts the following technical solutions: A method for multi-source geographic information fusion specifically includes the following steps:

[0008] Step A1: Mark the geographical monitoring area as the k1st to the kth k geographical monitoring sub-areas, and respectively obtain the area values of the first type of area, the area values of the second type of area, and the area values of the third type of area in each geographical monitoring sub-area to obtain area data;

[0009] Step A2: Obtain the first current characteristic coefficients and the first historical characteristic coefficients respectively corresponding to the k1st to the kth k geographical monitoring sub-areas, and by calculating the difference between each first current characteristic coefficient and the corresponding first historical characteristic coefficient, obtain water area characteristic data;

[0010] Step A3: Obtain the difference in vegetation characteristic coefficients respectively corresponding to the k1st to the kth k geographical monitoring sub-areas to obtain vegetation characteristic data;

[0011] Step A4: Obtain the difference in building characteristic coefficients respectively corresponding to the k1st to the kth k geographical monitoring sub-areas to obtain building characteristic data;

[0012] Step A5: According to the area data, divide the k1st to the kth k geographical monitoring sub-areas into the first change type monitoring sub-areas and the second change type monitoring sub-areas, obtain the geographical information update coefficients corresponding to each second change type monitoring sub-area, obtain the geographical information update coefficient threshold to perform a numerical comparison on the geographical information update coefficients corresponding to the second change type monitoring sub-areas, and further divide the second change type monitoring sub-areas into the first change type monitoring sub-areas and the third change type monitoring sub-areas to obtain regional geographical information update data.

[0013] Furthermore, in the said Step A1, the following specific steps are further included:

[0014] Step A11: Divide the geographical monitoring area into several geographical monitoring sub-areas with characteristic area sizes, and respectively mark them as the k1st to the kth k geographical monitoring sub-areas;

[0015] Step A12: Conduct area monitoring on the k1st geographical monitoring sub-area to obtain the k1st area data;

[0016] Step A13: Conduct area monitoring on the k2nd to the kth k geographical monitoring sub-areas respectively to obtain the area data of the k2nd to the kth k areas;

[0017] Step A14: Define the area data of the k1st to the kth k areas as the area data.

[0018] Further, in step A12, the following specific steps are further included:

[0019] Step A121: Divide the land in the k1st geographical monitoring sub-region into the first-type geographical region, the second-type geographical region, and the third-type geographical region according to land use types respectively;

[0020] Step A122: Obtain the aerial plane image of the k1st geographical monitoring sub-region, and mark the boundary of the k1st geographical monitoring sub-region on the aerial plane image to obtain the first marked region;

[0021] Step A123: Use the region recognition model to recognize the first-type geographical region, the second-type geographical region, and the third-type geographical region in the aerial plane image, mark the first-type geographical region as the second marked region, mark the second-type geographical region as the third marked region, and mark the third-type geographical region as the fourth marked region to obtain the region marked image;

[0022] Step A124: Convert the region marked image into a grayscale image, and respectively perform pixel point statistics on the first to fourth marked regions to obtain the first to fourth pixel point quantity values;

[0023] Step A125: Obtain the actual area value corresponding to the k1st geographical monitoring sub-region;

[0024] Step A126: Calculate the actual area value corresponding to the first-type geographical region by using the actual area value corresponding to the k1st geographical monitoring sub-region, the first pixel point quantity value, and the second pixel point quantity value, and name it the first-type region area value;

[0025] Calculate the actual area value corresponding to the first-type geographical region, and the specific formula configuration is as follows:

[0026]

[0027] Wherein, Sm1 is the actual area value corresponding to the first-type geographical region, Xs1 is the first pixel point quantity value, Xs2 is the second pixel point quantity value, and Smk1 is the actual area value corresponding to the k1st geographical monitoring sub-region;

[0028] Step A127: Calculate the actual area value corresponding to the second-type geographical region by using the actual area value corresponding to the k1st geographical monitoring sub-region, the first pixel point quantity value, and the third pixel point quantity value, and name it the second-type region area value;

[0029] Step A128: Calculate the actual area value of the third type of geographical area from the actual area value, the first pixel point quantity value, and the fourth pixel point quantity value corresponding to the k1 geographical monitoring sub-region, and name it the third type of region area value;

[0030] Step A129: Define the first type of region area value, the second type of region area value, and the third type of region area value as the k1 region area data.

[0031] Furthermore, in the step A123, the following specific steps are further included:

[0032] Obtain multiple aerial plane images of different geographical regions through big data crawler technology, and manually mark the first type of geographical region, the second type of geographical region, and the third type of geographical region in each aerial plane image respectively to obtain sample plane image data;

[0033] Divide the sample plane image data into an identification test set and an identification training set, create an image recognition model through an artificial intelligence platform, use the identification training set to train the image recognition model, and perform at least one training on the image recognition model for each image in the identification training set. Use the identification test set to test the image recognition model and obtain the image recognition accuracy rate;

[0034] If the image recognition accuracy rate is greater than or equal to the target recognition accuracy rate, the image recognition model training is completed to obtain a region recognition model. If the image recognition accuracy rate is less than the target recognition accuracy rate, continue to use the identification training set to train the image recognition model until the image recognition accuracy rate is greater than or equal to the target recognition accuracy rate.

[0035] Furthermore, in the step A2, the following specific steps are further included:

[0036] Step A21: Obtain the water area feature coefficient difference corresponding to the k1 geographical monitoring sub-region to obtain the k1 water area feature coefficient difference;

[0037] Step A22: Respectively obtain the water area feature coefficient differences corresponding to the k2 to k k geographical monitoring sub-regions to obtain the k2 to k k water area feature coefficient differences;

[0038] Step A23: Define the water area feature coefficient differences from k1 to k k as water area feature data.

[0039] Furthermore, in the step A21, the following specific steps are further included:

[0040] Randomly select m first-type geographical regions in the k1 geographical monitoring sub-region as characteristic monitoring waters, and name them the first to the mth characteristic monitoring waters respectively;

[0041] Obtain the current pH value of the regional water body;

[0042] Specifically as follows:

[0043] Collect water body samples of unit volume at different positions in the first characteristic monitoring water area to obtain multiple water body samples, measure the pH value of each water body sample respectively to obtain multiple sample pH values, calculate the average value of the multiple sample pH values to obtain the water body pH value corresponding to the first characteristic monitoring water area, and name it the first water area pH value;

[0044] Obtain the water body pH values corresponding to the second to the mth characteristic monitoring water areas respectively to obtain the second to the mth water area pH values, calculate the average value of the first to the mth water area pH values to obtain the current pH value of the regional water body;

[0045] Obtain the number of single water bodies corresponding to the k1 geographical monitoring sub-region to obtain the current value of the number of single water bodies in the region;

[0046] Calculate the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-region by using the current pH value of the regional water body and the current value of the number of single water bodies in the region;

[0047] Calculate the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-region. The specific formula configuration is as follows:

[0048] Tzq = Dph + Dys × a1;

[0049] Where, Tzq is the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-region, Dph is the current pH value of the regional water body, Dys is the current value of the number of single water bodies in the region, and a1 is a set proportionality coefficient and a1 > 0;

[0050] Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical pH value of the regional water body and the historical value of the number of single water bodies in the region corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data;

[0051] Calculate the first historical characteristic coefficient corresponding to the k1 geographical monitoring sub-region by using the historical pH value of the regional water body and the historical value of the number of single water bodies in the region corresponding to the k1 geographical monitoring sub-region;

[0052] Calculate the first historical characteristic coefficient corresponding to the k1 geographical monitoring sub-region. The specific formula configuration is as follows:

[0053] Tzl = Lph + Lys × a1;

[0054] Among them, TzL is the first historical feature coefficient corresponding to the k1 geographical monitoring sub-region, Lph is the historical pH value of the regional water body, Lys is the historical single water area quantity value of the region, a1 is a set proportionality coefficient and a1 is greater than 0;

[0055] Calculate the difference between the first current feature coefficient and the first historical feature coefficient to obtain the k1 water area feature coefficient difference.

[0056] Furthermore, in the step A3, the following specific steps are further included:

[0057] Step A31: Obtain the vegetation feature coefficient difference corresponding to the k1 geographical monitoring sub-region to obtain the k1 vegetation feature coefficient difference;

[0058] Step A32: Respectively obtain the vegetation feature coefficient differences corresponding to the k2 to k k geographical monitoring sub-regions to obtain the k2 to k k vegetation feature coefficient differences;

[0059] Step A33: Define the k1 to k k water-vegetation feature coefficient differences as vegetation feature data;

[0060] In the step A31, the following specific steps are further included:

[0061] Count the number of vegetation species in the k1 geographical monitoring area to obtain the current quantity value of the regional vegetation species;

[0062] Select z sample monitoring vegetations in the k1 geographical monitoring area respectively, and name them the first to the z sample monitoring vegetations respectively;

[0063] Respectively obtain the quantity values of the first to the z sample monitoring vegetations at the current moment to obtain the current quantity values of the first to the z sample vegetations;

[0064] Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical quantity value of the regional vegetation species corresponding to the k1 geographical monitoring sub-region and the historical quantity values of the first to the z sample vegetations according to the historical geographical information data;

[0065] Calculate the k1 vegetation feature coefficient difference through the current quantity value of the regional vegetation species, the historical quantity value of the regional vegetation species, the current quantity values of the first to the z sample vegetations, and the historical quantity values of the first to the z sample vegetations;

[0066] Calculate the k1 vegetation feature coefficient difference, and the specific formula configuration is as follows:

[0067] Zbx = |Zld - Zll| + (|Dq1 - Ls1| + |Dq2 - Ls2| + ······ + |Dqz - Lsz|);

[0068] Among them, Zbx is the difference of the k1 vegetation characteristic coefficients, Zld is the current quantity value of the regional vegetation species, Zll is the historical quantity value of the regional vegetation species, Dq1 to Dqz are the current quantity values of the first to the zth sample vegetation respectively, and Ls1 to Lsz are the historical quantity values of the first to the zth sample vegetation respectively.

[0069] Furthermore, in the step A4, the following specific steps are further included:

[0070] Step A41: Obtain the difference of the building characteristic coefficients corresponding to the k1 geographical monitoring sub-region to obtain the k1 building characteristic coefficient difference;

[0071] Step A42: Respectively obtain the differences of the building characteristic coefficients corresponding to the k2 to k k geographical monitoring sub-regions to obtain the k2 to k k building characteristic coefficient differences;

[0072] Step A43: Define the k1 to k k building characteristic coefficient differences as building characteristic data;

[0073] In the step A41, the following specific steps are further included:

[0074] Statistically obtain the quantity value of the individual buildings corresponding to the k1 geographical monitoring sub-region at the current moment to obtain the first individual building quantity value;

[0075] Obtain the total road mileage value corresponding to the k1 geographical monitoring sub-region at the current moment to obtain the first road mileage value;

[0076] Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical quantity value of the individual buildings corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data to obtain the second individual building quantity value;

[0077] Obtain the historical total road mileage value corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data to obtain the second road mileage value;

[0078] Calculate the k1 building characteristic coefficient difference through the first individual building quantity value, the first road mileage value, the second individual building quantity value, and the second road mileage value;

[0079] Calculate the k1 building characteristic coefficient difference, and the specific formula configuration is as follows:

[0080] Jzx = |Dtj1 - Dtj2| + |Llc1 - Ll c2|;

[0081] Among them, Jzx is the difference in the k1 building feature coefficients, Dtj1 is the numerical value of the number of the first single buildings, Dtj2 is the numerical value of the number of the second single buildings, Ll c1 is the numerical value of the first road mileage, and Ll c2 is the numerical value of the second road mileage.

[0082] Furthermore, in the step A5, the following specific steps are further included:

[0083] Step A51: Obtain the regional area data, and obtain the k1 to k k regional area data according to the regional area data;

[0084] Step A52: Obtain the k1 to k k regional area data, and obtain the sum of the area changes corresponding to the k1 to k k geographical monitoring sub-regions;

[0085] Step A53: Obtain the sum of the reference area changes of the region, compare the sum of the area changes corresponding to the k1 to k k geographical monitoring sub-regions with the sum of the reference area changes of the region, and divide the k1 to k k geographical monitoring sub-regions into the first type of change type monitoring sub-regions and the third type of change type monitoring sub-regions respectively to obtain the updated regional geographical information data;

[0086] In the step A52, the following specific steps are further included:

[0087] Obtain the numerical values of the area of the first type, the area of the second type, and the area of the third type corresponding to the k1 geographical monitoring sub-region according to the k1 regional area data;

[0088] Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and respectively obtain the historical area numerical value of the first type of region, the historical area numerical value of the second type of region, and the historical area numerical value of the third type of region according to the historical geographical information data;

[0089] Calculate the difference between the area value of the first type of area and the historical area value of the first type of area, then take the absolute value of the obtained difference to get the area change value of the first type of area. Calculate the difference between the area value of the second type of area and the historical area value of the second type of area, then take the absolute value of the obtained difference to get the area change value of the second type of area. Calculate the difference between the area value of the third type of area and the historical area value of the third type of area, then take the absolute value of the obtained difference to get the area change value of the third type of area. Sum up the area change values of the first type of area, the second type of area, and the third type of area to obtain the area change sum corresponding to the k1 geographical monitoring sub-region;

[0090] Respectively obtain the area change sums corresponding to the geographical monitoring sub-regions from k2 to k k geographical monitoring sub-regions.

[0091] Furthermore, in the step A53, the following specific steps are further included:

[0092] When the area change sum is greater than or equal to the reference area change sum, it is determined that the corresponding geographical monitoring sub-region is a first change type monitoring sub-region;

[0093] When the area change sum is less than the reference area change sum, it is determined that the corresponding geographical monitoring sub-region is a second change type monitoring sub-region;

[0094] Further update and judge the second change type monitoring sub-region;

[0095] Specifically as follows:

[0096] Respectively obtain water area feature data, vegetation feature data, and building feature data;

[0097] When the k1 geographical monitoring sub-region is a second change type monitoring sub-region, respectively obtain the k1 water area feature coefficient difference, the k1 vegetation feature coefficient difference, and the k1 building feature coefficient difference according to the water area feature data, the vegetation feature data, and the building feature data;

[0098] Calculate the k1 geographical monitoring sub-region corresponding geographical information update coefficient from the k1 water area feature coefficient difference, the k1 vegetation feature coefficient difference, and the k1 building feature coefficient difference;

[0099] Obtain the geographical information update coefficient corresponding to the k1 geographical monitoring sub-region;

[0100] The specific formula configuration is as follows:

[0101] Dxg = Syx + Zbx + Jzx;

[0102] Among them, Dxg is the geographical information update coefficient corresponding to the k1 geographical monitoring sub-region, Syx is the difference in the k1 water area characteristic coefficient, Zbx is the difference in the k1 vegetation characteristic coefficient, and Jzx is the difference in the k1 building characteristic coefficient;

[0103] Obtain the geographical information update coefficients corresponding to each of the second change type monitoring sub-regions respectively, to obtain a plurality of geographical information update coefficients, and numerically compare the obtained geographical information update coefficient thresholds with the plurality of geographical information update coefficients respectively;

[0104] Specifically as follows:

[0105] Obtain the benchmark difference of the water area characteristic coefficient, the benchmark difference of the vegetation characteristic coefficient, and the benchmark difference of the building characteristic coefficient respectively;

[0106] Calculate the benchmark difference of the water area characteristic coefficient, the benchmark difference of the vegetation characteristic coefficient, and the benchmark difference of the building characteristic coefficient to obtain the geographical information update coefficient threshold;

[0107] When the geographical information update coefficient is greater than or equal to the geographical information update coefficient threshold, divide the second change type monitoring sub-region into the first change type monitoring region;

[0108] When the geographical information update coefficient is less than the geographical information update coefficient threshold, divide the second change type monitoring sub-region into the third change type monitoring region.

[0109] To sum up, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0110] 1. The present invention obtains and fuses regional geographical information through separately obtaining regional area data, water area characteristic data, vegetation characteristic data, and building characteristic data, making the process of fusing and obtaining geographical information more accurate and comprehensive;

[0111] 2. The present invention divides a plurality of geographical monitoring sub-regions into the first change type monitoring sub-regions and the second change type monitoring sub-regions through the regional area data, obtains the geographical information update coefficient corresponding to each second change type monitoring sub-region, obtains the geographical information update coefficient threshold to numerically compare the geographical information update coefficient corresponding to the second change type monitoring sub-region, further divides the second change type monitoring sub-region into the first change type monitoring sub-region and the third change type monitoring sub-region, and finally updates the geographical information of the first change type monitoring sub-region. Compared with setting a fixed time period for systematic geographical information upgrade, it can effectively improve the acquisition efficiency and update efficiency of geographical information. BRIEF DESCRIPTION OF THE DRAWINGS

[0112] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings.

[0113] Figure 1 This is the overall system block diagram of the present invention;

[0114] Figure 2 This is the implementation step diagram of the present invention;

[0115] Figure 3 This is the schematic diagram of the division of the k1th geographical monitoring sub-region in the present invention. Detailed implementation manners

[0116] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0117] Embodiment 1

[0118] Please refer to Figure 1 , the present invention provides a technical solution: a method for multi-source geographic information fusion, including the following steps:

[0119] Step A1: Obtain regional area data;

[0120] Step A11: Divide the geographical monitoring area into several geographical monitoring sub-regions with characteristic area sizes, and label them as the k1th to the kth k geographical monitoring sub-regions;

[0121] Step A12: Monitor the area of the k1th geographical monitoring sub-region to obtain the k1th regional area data;

[0122] In the said step A12, the following steps are further included:

[0123] Step A121: Divide the land of the k1th geographical monitoring sub-region into the first-type geographical region, the second-type geographical region, and the third-type geographical region respectively according to the land use type. Please refer to Figure 3 ;

[0124] Step A122: Obtain the aerial photograph plane image of the k1th geographical monitoring sub-region, and mark the boundary of the k1th geographical monitoring sub-region on the aerial photograph plane image to obtain the first marked area;

[0125] Step A123: Use the region recognition model to recognize the first-type geographical region, the second-type geographical region, and the third-type geographical region in the aerial photograph plane image, mark the first-type geographical region as the second marked area, mark the second-type geographical region as the third marked area, and mark the third-type geographical region as the fourth marked area to obtain the region marked image;

[0126] In this application, step A123 obtains geographical information for the first type of geographical region, the second type of geographical region, and the third type of geographical region in the aerial plane image respectively, enabling the covered geographical information to include water areas, vegetation, and buildings, and being able to provide a more comprehensive acquisition of geographical features, thereby ensuring the wide range and diversity of data sources;

[0127] In the said step A12, the following specific steps are further included:

[0128] In this application, in step A12, by establishing a region recognition model to automatically mark and recognize the first type of geographical region, the second type of geographical region, and the third type of geographical region in the aerial plane image, real-time data processing can be achieved, regional information can be updated in a timely manner, the analysis time can be significantly shortened, especially when processing a large number of aerial images, the need for manual marking can be reduced, thereby improving work efficiency;

[0129] Step A1231: Obtain multiple aerial plane images of different geographical regions through big data crawling technology, and manually mark the first type of geographical region, the second type of geographical region, and the third type of geographical region in each aerial plane image respectively to obtain sample plane image data;

[0130] In this application, in step A1231, compared with the traditional statistical collection method, the data crawling technology can automatically collect data, greatly improving the efficiency of data acquisition. The data crawling technology can simultaneously obtain data from multiple data sources online to ensure the consistency and accuracy of the data;

[0131] Step A1232: Divide the sample plane image data into an identification test set and an identification training set, create an image recognition model through an artificial intelligence platform, use the identification training set to train the image recognition model, and train the image recognition model at least once for each image in the identification training set. Use the identification test set to test the image recognition model and obtain the image recognition accuracy rate;

[0132] Step A1233: If the image recognition accuracy rate is greater than or equal to the target recognition accuracy rate, the image recognition model training is completed to obtain a region recognition model. If the image recognition accuracy rate is less than the target recognition accuracy rate, continue to use the identification training set to train the image recognition model until the image recognition accuracy rate is greater than or equal to the target recognition accuracy rate;

[0133] Step A124: Convert the region-marked image into a grayscale image, and respectively perform pixel point statistics on the first to fourth marked regions to obtain the first to fourth pixel point quantity values;

[0134] Step A125: Obtain the actual area value corresponding to the k1 geographical monitoring sub-region;

[0135] Step A126: Calculate the actual area value corresponding to the first type of geographical region from the actual area value, the first pixel point quantity value, and the second pixel point quantity value corresponding to the k1 geographical monitoring sub-region, and name it the first type of region area value;

[0136] Calculate the actual area value corresponding to the first type of geographical region, and the specific formula configuration is as follows:

[0137]

[0138] Among them, Sm1 is the actual area value corresponding to the first type of geographical region, Xs1 is the first pixel point quantity value, Xs2 is the second pixel point quantity value, and Smk1 is the actual area value corresponding to the k1 geographical monitoring sub-region;

[0139] Step A127: Calculate the actual area value corresponding to the second type of geographical region from the actual area value, the first pixel point quantity value, and the third pixel point quantity value corresponding to the k1 geographical monitoring sub-region, and name it the second type of region area value;

[0140] Step A128: Calculate the actual area value corresponding to the third type of geographical region from the actual area value, the first pixel point quantity value, and the fourth pixel point quantity value corresponding to the k1 geographical monitoring sub-region, and name it the third type of region area value;

[0141] Step A129: Define the first type of region area value, the second type of region area value, and the third type of region area value as the k1 region area data;

[0142] In this application, in Step A12, the areas of the first type of geographical region, the second type of geographical region, and the third type of geographical region are obtained respectively by pixel point statistics, which can greatly reduce the labor cost, reduce the errors caused by manual measurement, and realize the real-time monitoring of the geographical region area change. At the same time, since the pixel point is used as the statistical measurement unit, the accuracy of area acquisition can be effectively improved;

[0143] Step A13: Monitor the areas of the k2 to k k geographical monitoring sub-regions respectively to obtain the k2 to k k region area data;

[0144] Step A14: Define the k1 to k k region area data as the region area data;

[0145] Step A2: Obtain the water area information of the first type of geographical area to get the difference in water area characteristic coefficients;

[0146] Step A21: Obtain the difference in water area characteristic coefficients corresponding to the k1 geographical monitoring sub-area to get the k1 water area characteristic coefficient difference;

[0147] In the said Step A21, the following specific steps are further included:

[0148] Step A211: Randomly select m first-type geographical areas in the k1 geographical monitoring sub-area as characteristic monitoring water areas, and name them the first to the mth characteristic monitoring water areas respectively;

[0149] Step A212: Obtain the current pH value of the regional water body;

[0150] In the present application, by taking the pH value of the regional water body as a specific index for detecting changes in geographical information in Step A212, it can be simply and directly determined whether the water body is polluted or affected by ecosystem changes. To a certain extent, the pH value of the water body can reflect the water body vegetation coverage and water body eutrophication situation in the water area, fully highlighting the correlation between geographical information, providing guarantee for the subsequent division of the geographical information update area, and making the division result more accurate;

[0151] Specifically as follows:

[0152] Step A2121: Collect water body samples of unit volume at different positions in the first characteristic monitoring water area to obtain multiple water body samples, measure the pH value of each water body sample respectively to obtain multiple sample pH values, calculate the average of the multiple sample pH values to obtain the water body pH value corresponding to the first characteristic monitoring water area, and name it the first water area pH value;

[0153] Step A2122: Obtain the water body pH values corresponding to the second to the mth characteristic monitoring water areas respectively to get the second to the mth water area pH values, and calculate the average of the first to the mth water area pH values to obtain the current pH value of the regional water body;

[0154] Step A213: Obtain the number of single water bodies corresponding to the k1 geographical monitoring sub-area to get the current value of the number of single water bodies in the area;

[0155] Step A214: Calculate the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-area by calculating the current pH value of the regional water body and the current value of the number of single water bodies in the area;

[0156] Calculate the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-area, and the specific formula configuration is as follows:

[0157] Tzq = Dph + Dys × a1;

[0158] Among them, Tzq is the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-region, Dph is the current pH value of the regional water body, Dys is the current number value of individual water areas in the region, and a1 is a set proportionality coefficient and a1 > 0;

[0159] Step A215: Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical pH value of the regional water body and the historical number value of individual water areas in the region according to the historical geographical information data;

[0160] Step A216: Calculate the first historical characteristic coefficient corresponding to the k1 geographical monitoring sub-region by using the historical pH value of the regional water body and the historical number value of individual water areas in the region;

[0161] Calculate the first historical characteristic coefficient corresponding to the k1 geographical monitoring sub-region, and the specific formula configuration is as follows:

[0162] Tzl = Lph + Lys × a1;

[0163] Among them, TzL is the first historical characteristic coefficient corresponding to the k1 geographical monitoring sub-region, Lph is the historical pH value of the regional water body, Lys is the historical number value of individual water areas in the region, and a1 is a set proportionality coefficient and a1 > 0;

[0164] Step A217: Calculate the difference between the first current characteristic coefficient and the first historical characteristic coefficient to obtain the k1 water area characteristic coefficient difference;

[0165] Step A22: Obtain the water area characteristic coefficient differences corresponding to the k2 to k k geographical monitoring sub-regions respectively to obtain the water area characteristic coefficient differences corresponding to the k2 to k k water area characteristic coefficient differences;

[0166] Step A23: Define the water area characteristic coefficient differences from k1 to k k as water area characteristic data;

[0167] Step A3: Obtain vegetation characteristic data by acquiring vegetation information of the second type of geographical region;

[0168] Step A31: Obtain the vegetation characteristic coefficient difference corresponding to the k1 geographical monitoring sub-region to obtain the k1 vegetation characteristic coefficient difference;

[0169] In the said Step A31, the following specific steps are further included:

[0170] Step A311: Count the number of vegetation species in the k1 geographical monitoring region to obtain the current number value of regional vegetation species;

[0171] Step A312: Select z types of sample monitored vegetation in the k1 geographical monitoring area respectively, and name them the first to the z-th sample monitored vegetation respectively;

[0172] Step A313: Obtain the quantity values of the first to the z-th sample monitored vegetation at the current moment respectively, and obtain the current quantity values of the first to the z-th sample vegetation;

[0173] Step A314: Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-area, and obtain the historical quantity values of the regional vegetation types and the historical quantity values of the first to the z-th sample vegetation corresponding to the k1 geographical monitoring sub-area according to the historical geographical information data;

[0174] Step A315: Calculate the difference of the k1 vegetation characteristic coefficients by using the current quantity value of the regional vegetation type, the historical quantity value of the regional vegetation type, the current quantity values of the first to the z-th sample vegetation, and the historical quantity values of the first to the z-th sample vegetation;

[0175] Calculate the difference of the k1 vegetation characteristic coefficients, and the specific formula configuration is as follows:

[0176] Zbx = |Zld - Zll| + (|Dq1 - Ls1| + |Dq2 - Ls2| + ······ + |Dqz - Lsz|);

[0177] Wherein, Zbx is the difference of the k1 vegetation characteristic coefficients, Zld is the current quantity value of the regional vegetation type, Zll is the historical quantity value of the regional vegetation type, Dq1 to Dqz are the current quantity values of the first to the z-th sample vegetation respectively, and Ls1 to Lsz are the historical quantity values of the first to the z-th sample vegetation respectively;

[0178] In this application, Step A31 analyzes the change of the regional vegetation characteristics by selecting multiple sample vegetations and obtaining the difference between their current quantity values and historical quantity values to reflect the vegetation change of the region, which can improve the efficiency of data acquisition and analysis and the fusion speed of multi-source geographical information;

[0179] Step A32: Obtain the differences of the vegetation characteristic coefficients corresponding to the k2 to k k geographical monitoring sub-areas respectively, and obtain the differences of the k2 to k k vegetation characteristic coefficients;

[0180] Step A33: Define the differences of the k1 to k k water vegetation characteristic coefficients as vegetation characteristic data;

[0181] Step A4: Obtain building information of the third type of geographical area to obtain building characteristic data;

[0182] Step A41: Obtain the building feature coefficient difference corresponding to the k1 geographical monitoring sub-region to get the k1 building feature coefficient difference;

[0183] In the said Step A41, the following specific steps are further included:

[0184] Step A411: Count the number value of individual buildings corresponding to the k1 geographical monitoring sub-region at the current moment to get the first individual building number value;

[0185] Step A412: Obtain the total road mileage value corresponding to the k1 geographical monitoring sub-region at the current moment to get the first road mileage value;

[0186] Step A413: Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical individual building number value corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data to get the second individual building number value;

[0187] Step A414: Obtain the historical total road mileage value corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data to get the second road mileage value;

[0188] Step A415: Calculate the k1 building feature coefficient difference through the first individual building number value, the first road mileage value, the second individual building number value and the second road mileage value;

[0189] Calculate the k1 building feature coefficient difference, and the specific formula configuration is as follows:

[0190] Jzx = |Dtj1 - Dtj2| + |Llc1 - Ll c2|;

[0191] Wherein, Jzx is the k1 building feature coefficient difference, Dtj1 is the first individual building number value, Dtj2 is the second individual building number value, Ll c1 is the first road mileage value, and Ll c2 is the second road mileage value;

[0192] Step A42: Respectively obtain the building feature coefficient differences corresponding to the k2 to k k geographical monitoring sub-regions to get the k2 to k k building feature coefficient differences;

[0193] Step A43: Define the k1 to k k building feature coefficient differences as building feature data;

[0194] Step A5: Perform data geographical information update judgment by fusing regional area data, water area feature data, vegetation feature data and building feature data to get regional geographical information update data;

[0195] Step A51: Obtain the regional area data, and obtain the k1st to kth k regional area data according to the regional area data;

[0196] Step A52: According to the k1st to kth k regional area data, obtain the area changes corresponding to the k1st to kth k geographical monitoring sub-regions and;

[0197] In the said Step A52, the following specific steps are further included:

[0198] Step A521: According to the k1st regional area data, obtain the first-type regional area value, the second-type regional area value, and the third-type regional area value corresponding to the k1st geographical monitoring sub-region;

[0199] Step A522: Obtain the historical geographical information data corresponding to the k1st geographical monitoring sub-region, and respectively obtain the first-type regional historical area value, the second-type regional historical area value, and the third-type regional historical area value according to the historical geographical information data;

[0200] Step A523: Calculate the difference between the first-type regional area value and the first-type regional historical area value, then take the absolute value of the obtained difference to get the first-type regional area change value, calculate the difference between the second-type regional area value and the second-type regional historical area value, then take the absolute value of the obtained difference to get the second-type regional area change value, calculate the difference between the third-type regional area value and the third-type regional historical area value, then take the absolute value of the obtained difference to get the third-type regional area change value, and sum up the first-type regional area change value, the second-type regional area change value, and the third-type regional area change value to obtain the area change sum corresponding to the k1st geographical monitoring sub-region;

[0201] Step A524: Respectively obtain the area change sums corresponding to the k2nd to kth k geographical monitoring sub-regions;

[0202] Step A53: Obtain the regional area baseline change sum, compare the area change sums corresponding to the k1st to kth k geographical monitoring sub-regions with the regional area baseline change sum in terms of numerical values, and divide the k1st to kth k geographical monitoring sub-regions into the first change type monitoring sub-regions and the third change type monitoring sub-regions respectively to obtain the regional geographical information update data;

[0203] Specifically as follows:

[0204] Step A531: When the sum of the regional area changes is greater than or equal to the reference sum of the regional area changes, it is determined that the corresponding geographical monitoring sub-region is a monitoring sub-region of the first change type;

[0205] Step A532: When the sum of the regional area changes is less than the reference sum of the regional area changes, it is determined that the corresponding geographical monitoring sub-region is a monitoring sub-region of the second change type;

[0206] In this application, by calculating the sum of the areas and comparing the numerical values with the reference sum of the regional area changes through the first-type regional area change value, the second-type regional area change value, and the third-type regional area change value, the integration of regional area data can be achieved. At the same time, a preliminary judgment is made on the sub-regions that need to update geographical information. For the regions with insignificant regional area changes, by making targeted judgments from three perspectives of water area, vegetation, and buildings respectively, the accuracy and pertinence of the division of the regions to be updated with geographical information can be effectively improved;

[0207] Step A533: Further update judgment is made on the monitoring sub-regions of the second change type;

[0208] Specifically as follows:

[0209] Step A5331: Obtain water area feature data, vegetation feature data, and building feature data respectively;

[0210] Step A5332: When the k1-th geographical monitoring sub-region is a monitoring sub-region of the second change type, obtain the k1-th water area feature coefficient difference, the k1-th vegetation feature coefficient difference, and the k1-th building feature coefficient difference respectively according to the water area feature data, the vegetation feature data, and the building feature data;

[0211] Step A5333: Calculate the geographical information update coefficient corresponding to the k1-th geographical monitoring sub-region by using the k1-th water area feature coefficient difference, the k1-th vegetation feature coefficient difference, and the k1-th building feature coefficient difference;

[0212] Obtain the geographical information update coefficient corresponding to the k1-th geographical monitoring sub-region;

[0213] The specific formula configuration is as follows:

[0214] Dxg = Syx + Zbx + Jzx;

[0215] Where Dxg is the geographical information update coefficient corresponding to the k1-th geographical monitoring sub-region, Syx is the k1-th water area feature coefficient difference, Zbx is the k1-th vegetation feature coefficient difference, and Jzx is the k1-th building feature coefficient difference;

[0216] Step A5334: Obtain the geographic information update coefficients corresponding to each second change type monitoring sub-region respectively, to obtain a plurality of geographic information update coefficients, and numerically compare the obtained geographic information update coefficient thresholds with the plurality of geographic information update coefficients;

[0217] Specifically as follows:

[0218] Step A53341: Obtain the water area feature coefficient reference difference, the vegetation feature coefficient reference difference, and the building feature coefficient reference difference respectively;

[0219] Step A53342: Calculate the water area feature coefficient reference difference, the vegetation feature coefficient reference difference, and the building feature coefficient reference difference to obtain the geographic information update coefficient threshold;

[0220] Calculate the geographic information update coefficient threshold, and the specific formula configuration is as follows:

[0221] Dxgj = Syxj + Zbxj + Jzxj;

[0222] Where, Dxgj is the geographic information update coefficient threshold, Syxj is the water area feature coefficient reference difference, Zbxj is the vegetation feature coefficient reference difference, and Jzxj is the building feature coefficient reference difference;

[0223] Step A53343: When the geographic information update coefficient is greater than or equal to the geographic information update coefficient threshold, divide the second change type monitoring sub-region into the first change type monitoring area;

[0224] Step A53344: When the geographic information update coefficient is less than the geographic information update coefficient threshold, divide the second change type monitoring sub-region into the third change type monitoring area.

[0225] In this application, if there are corresponding calculation formulas, the above calculation formulas are all dimensionless and take their numerical values for calculation. The weight coefficients, proportionality coefficients, etc. in the formulas are set in such a way that a result value is obtained by quantifying each parameter. Regarding the magnitudes of the weight coefficients and proportionality coefficients, as long as the proportional relationship between the parameters and the result value is not affected.

[0226] Embodiment 2

[0227] Please refer to Figure 2, based on another concept of the same invention, a system for multi-source geographic information fusion is now proposed, including a regional area module, a first regional analysis module, a second regional analysis module, a third regional analysis module, an information fusion module, and a server. The regional area module, the first regional analysis module, the second regional analysis module, the third regional analysis module, and the information fusion module are respectively connected to the server, and the server controls the regional area module, the first regional analysis module, the second regional analysis module, the third regional analysis module, and the information fusion module respectively;

[0228] The regional area module obtains regional area data;

[0229] The geographical monitoring area is divided into several geographical monitoring sub-areas with characteristic area sizes, and they are respectively marked as the k1th to the k k Geographical monitoring sub-areas;

[0230] It should be noted here that:

[0231] In this application, the characteristic area size is specifically 5KM 2 , in specific implementation, the characteristic area size needs to be set accordingly according to the actual situation;

[0232] In this invention, the k involved here k is specifically the numerical value corresponding to the geographical monitoring sub-area, and k k is an integer greater than 0;

[0233] Monitor the area of the k1th geographical monitoring sub-area to obtain the k1th regional area data;

[0234] Specifically as follows:

[0235] The land of the k1th geographical monitoring sub-area is divided into the first type of geographical area, the second type of geographical area, and the third type of geographical area respectively according to the land use type;

[0236] It should be noted here that:

[0237] In this application, the first type of geographical area is the water flow coverage area, and its constituent geographical features include but are not limited to reservoirs, ponds, rivers, and lakes. The second type of geographical area is the vegetation coverage area, and its constituent geographical features include but are not limited to forests, green belts, and lawns. The third type of geographical area is the artificial building coverage area, and its constituent geographical features include but are not limited to roads, houses, and shopping malls;

[0238] Obtain the aerial plane image of the k1th geographical monitoring sub-area, and mark the boundary of the k1th geographical monitoring sub-area on the aerial plane image to obtain the first marked area;

[0239] Use the regional recognition model to identify the first type of geographical region, the second type of geographical region, and the third type of geographical region in the aerial plane image, mark the first type of geographical region as the second marked region, mark the second type of geographical region as the third marked region, mark the third type of geographical region as the fourth marked region, and obtain the regional marked image;

[0240] The establishment of the regional recognition model is as follows:

[0241] Obtain multiple aerial plane images of different geographical regions through big data crawling technology, and manually mark the first type of geographical region, the second type of geographical region, and the third type of geographical region in each aerial plane image respectively to obtain the sample plane image data;

[0242] Divide the sample plane image data into an identification test set and an identification training set, create an image recognition model through an artificial intelligence platform, use the identification training set to train the image recognition model, and train the image recognition model at least once for each image in the identification training set. Use the identification test set to test the image recognition model and obtain the image recognition accuracy rate;

[0243] If the image recognition accuracy rate is greater than or equal to the target recognition accuracy rate, the image recognition model training is completed, and the regional recognition model is obtained;

[0244] If the image recognition accuracy rate is less than the target recognition accuracy rate, continue to use the identification training set to train the image recognition model until the image recognition accuracy rate is greater than or equal to the target recognition accuracy rate;

[0245] Convert the regional marked image into a grayscale image, and respectively count the pixel points of the first to fourth marked regions to obtain the first to fourth pixel point quantity values;

[0246] Obtain the actual area value corresponding to the k1 geographical monitoring sub-region;

[0247] Here it should be noted that:

[0248] The actual area value corresponding to the k1 geographical monitoring sub-region here is the characteristic area size, that is, 5 square kilometers;

[0249] Calculate the actual area value corresponding to the first type of geographical region through the actual area value corresponding to the k1 geographical monitoring sub-region, the first pixel point quantity value, and the second pixel point quantity value, and name it the first type of regional area value;

[0250] Calculate the actual area value corresponding to the first type of geographical region, and the specific formula configuration is as follows:

[0251]

[0252] Among them, Sm1 is the actual area value corresponding to the first type of geographical area, Xs1 is the first pixel point quantity value, Xs2 is the second pixel point quantity value, and Smk1 is the actual area value corresponding to the k1 geographical monitoring sub-area;

[0253] Calculate the actual area value corresponding to the second type of geographical area from the actual area value, the first pixel point quantity value, and the third pixel point quantity value corresponding to the k1 geographical monitoring sub-area, and name it the second type of area value;

[0254] Calculate the actual area value corresponding to the third type of geographical area from the actual area value, the first pixel point quantity value, and the fourth pixel point quantity value corresponding to the k1 geographical monitoring sub-area, and name it the third type of area value;

[0255] Define the first type of area value, the second type of area value, and the third type of area value as the k1 area data;

[0256] Perform area monitoring on the k2 to k k geographical monitoring sub-areas respectively to obtain the k2 to k k area data;

[0257] Define the k1 to k k area data as the area data;

[0258] The area module obtains the area data and transports it to the information fusion module;

[0259] The first area analysis module obtains information on the first type of geographical area to obtain the water area characteristic coefficient difference;

[0260] Obtain the water area characteristic coefficient difference corresponding to the k1 geographical monitoring sub-area to obtain the k1 water area characteristic coefficient difference;

[0261] Specifically as follows:

[0262] Randomly select m first type of geographical areas in the k1 geographical monitoring sub-area as the characteristic monitoring water areas, and name them the first to m characteristic monitoring water areas respectively;

[0263] Collect water body samples of unit volume at different positions in the first characteristic monitoring water area to obtain a plurality of water body samples, measure the pH value of each water body sample respectively to obtain a plurality of sample pH values, calculate the average value of the plurality of sample pH values to obtain the water body pH value corresponding to the first characteristic monitoring water area, and name it the first water area pH value;

[0264] Obtain the water body pH values corresponding to the second to the mth characteristic monitoring waters respectively to get the pH values of the second to the mth waters, and calculate the average of the pH values of the first to the mth waters to obtain the current pH value of the regional water body;

[0265] Obtain the number of individual waters corresponding to the k1 geographical monitoring sub-region to get the current value of the number of individual waters in the region;

[0266] It should be noted here that:

[0267] The number of individual waters involved here specifically refers to the number of water body individuals that are divided into independent and separate waters in a specific region;

[0268] Calculate the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-region through the current pH value of the regional water body and the current value of the number of individual waters in the region;

[0269] Calculate the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-region, and the specific formula configuration is as follows:

[0270] Tzq = Dph + Dys × a1;

[0271] Where, Tzq is the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-region, Dph is the current pH value of the regional water body, Dys is the current value of the number of individual waters in the region, and a1 is a set proportional coefficient and a1 > 0;

[0272] Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical pH value of the regional water body and the historical value of the number of individual waters in the region corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data;

[0273] It should be noted here that:

[0274] Historical geographical information data refers to the geographical information in the historical period collected and analyzed for a specific geographical region. The historical geographical information data involved here specifically refers to the historical geographical information data of the previous version at the current moment;

[0275] Calculate the first historical characteristic coefficient corresponding to the k1 geographical monitoring sub-region through the historical pH value of the regional water body and the historical value of the number of individual waters in the region corresponding to the k1 geographical monitoring sub-region;

[0276] Calculate the first historical characteristic coefficient corresponding to the k1 geographical monitoring sub-region, and the specific formula configuration is as follows:

[0277] Tzl = Lph + Lys × a1;

[0278] Among them, TzL is the first historical feature coefficient corresponding to the k1 geographical monitoring sub-region, Lph is the historical pH value of the regional water body, Lys is the historical value of the number of individual water areas in the region, and a1 is a set proportionality coefficient and a1 > 0;

[0279] Calculate the difference between the first current feature coefficient and the first historical feature coefficient to obtain the k1 water area feature coefficient difference;

[0280] Respectively obtain the water area feature coefficient differences corresponding to the geographical monitoring sub-regions from k2 to k k to obtain the water area feature coefficient differences from k2 to k k water area feature coefficient differences;

[0281] Define the water area feature coefficient differences from k1 to k k as water area feature data;

[0282] The first regional analysis module obtains the water area feature data and transports it to the information fusion module;

[0283] The second regional analysis module obtains information on the second type of geographical region to obtain vegetation feature data;

[0284] Obtain the vegetation feature coefficient difference corresponding to the k1 geographical monitoring sub-region to obtain the k1 vegetation feature coefficient difference;

[0285] Specifically as follows:

[0286] Count the number of vegetation species in the k1 geographical monitoring area to obtain the current value of the number of regional vegetation species;

[0287] Select z sample monitoring vegetation in the k1 geographical monitoring area respectively, and name them the first to the z sample monitoring vegetation respectively;

[0288] It should be noted here that:

[0289] The z involved here is the value of the number of species corresponding to the selected sample monitoring vegetation, and z is an integer greater than 0;

[0290] Respectively obtain the current values of the number of the first to the z sample monitoring vegetation at the current moment to obtain the current values of the number of the first to the z sample vegetation;

[0291] The sample monitoring vegetation involved here are all trees with a tree age of more than five years. Among them, the first sample monitoring vegetation can be a pine tree, the second sample monitoring vegetation can be a poplar tree... the z sample monitoring vegetation can be a willow tree;

[0292] Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical value of the number of regional vegetation species and the historical values of the number of the first to the z sample vegetation corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data;

[0293] Calculate the difference in the k1 vegetation characteristic coefficients from the current quantity value of the regional vegetation types, the historical quantity value of the regional vegetation types, the current quantity values of the first to zth sample vegetations, and the historical quantity values of the first to zth sample vegetations;

[0294] Calculate the difference in the k1 vegetation characteristic coefficients, and the specific formula configuration is as follows:

[0295] Zbx = |Zld - Zll| + (|Dq1 - Ls1| + |Dq2 - Ls2| + ······ + |Dqz - Lsz|);

[0296] Wherein, Zbx is the difference in the k1 vegetation characteristic coefficients, Zld is the current quantity value of the regional vegetation types, Zll is the historical quantity value of the regional vegetation types, Dq1 to Dqz are the current quantity values of the first to zth sample vegetations respectively, and Ls1 to Lsz are the historical quantity values of the first to zth sample vegetations respectively;

[0297] Obtain the differences in the vegetation characteristic coefficients corresponding to the k2 to k k geographical monitoring sub-regions respectively, and obtain the differences in the k2 to k k vegetation characteristic coefficients;

[0298] Define the differences in the k1 to k k water vegetation characteristic coefficients as vegetation characteristic data;

[0299] The second regional analysis module obtains the vegetation characteristic data and transmits it to the information fusion module;

[0300] The third regional analysis module obtains information on the third type of geographical region and obtains building characteristic data;

[0301] Obtain the difference in the building characteristic coefficients corresponding to the k1 geographical monitoring sub-region, and obtain the k1 building characteristic coefficient difference;

[0302] Specifically as follows:

[0303] Count the number of individual buildings corresponding to the k1 geographical monitoring sub-region at the current moment to obtain the first individual building quantity value;

[0304] Obtain the total road mileage value corresponding to the k1 geographical monitoring sub-region at the current moment to obtain the first road mileage value;

[0305] It should be noted here that:

[0306] The total road mileage value refers to the total length of all roads within the k1 geographical monitoring sub-region;

[0307] The single building involved here refers to a building composed of an independent structure, which is usually composed of a complete foundation, walls, roof, etc., and is not directly connected to other buildings. Single buildings can be residential buildings, commercial buildings, industrial buildings, etc.;

[0308] Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical single building quantity value corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data to obtain the second single building quantity value;

[0309] Obtain the total historical road mileage value corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data to obtain the second road mileage value;

[0310] Calculate the k1 building feature coefficient difference by calculating the first single building quantity value, the first road mileage value, the second single building quantity value, and the second road mileage value;

[0311] Calculate the k1 building feature coefficient difference, and the specific formula configuration is as follows:

[0312] Jzx = |Dtj1 - Dtj2| + |Llc1 - Ll c2|;

[0313] Among them, Jzx is the k1 building feature coefficient difference, Dtj1 is the first single building quantity value, Dtj2 is the second single building quantity value, Ll c1 is the first road mileage value, and Ll c2 is the second road mileage value;

[0314] Respectively obtain the building feature coefficient differences corresponding to the k2 to k k geographical monitoring sub-regions to obtain the k2 to k k building feature coefficient differences;

[0315] Define the k1 to k k building feature coefficient differences as building feature data;

[0316] The third region analysis module obtains the building feature data and transports it to the information fusion module;

[0317] The information fusion module updates and judges the data geographical information by fusing the regional area data, water area feature data, vegetation feature data, and building feature data to obtain the regional geographical information update data;

[0318] Obtain the regional area data, and obtain the k1 to k k regional area data;

[0319] Obtain the area values of the first type of area, the second type of area, and the third type of area corresponding to the k1 geographical monitoring sub-region according to the area data of the k1 region;

[0320] Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and respectively obtain the historical area values of the first type of area, the second type of area, and the third type of area according to the historical geographical information data;

[0321] Calculate the difference between the area value of the first type of area and the historical area value of the first type of area, then take the absolute value of the obtained difference to get the area change value of the first type of area. Calculate the difference between the area value of the second type of area and the historical area value of the second type of area, then take the absolute value of the obtained difference to get the area change value of the second type of area. Calculate the difference between the area value of the third type of area and the historical area value of the third type of area, then take the absolute value of the obtained difference to get the area change value of the third type of area. Sum up the area change values of the first type of area, the second type of area, and the third type of area to obtain the area change sum corresponding to the k1 geographical monitoring sub-region;

[0322] Respectively obtain the area change sums corresponding to the geographical monitoring sub-regions from k2 to k k ;

[0323] Obtain the reference area change sum, compare the area change sums corresponding to the geographical monitoring sub-regions from k1 to k k with the reference area change sum in terms of numerical values, and divide the geographical monitoring sub-regions from k1 to k k into the first change type monitoring sub-regions and the third change type monitoring sub-regions respectively to obtain the regional geographical information update data;

[0324] It should be noted here that:

[0325] The reference area change sum involved here is the maximum change value of the water area, vegetation area, and building area of the set geographical monitoring sub-region compared with the historical geographical information data;

[0326] When the area change sum is greater than or equal to the reference area change sum, it is determined that the corresponding geographical monitoring sub-region is the first change type monitoring sub-region;

[0327] When the area change sum is less than the reference area change sum, it is determined that the corresponding geographical monitoring sub-region is the second change type monitoring sub-region;

[0328] Further update judgment is performed on the second change type monitoring sub-region, specifically as follows:

[0329] Obtain water area feature data, vegetation feature data, and building feature data respectively;

[0330] When the k1th geographical monitoring sub-region is a second change type monitoring sub-region, obtain the k1th water area feature coefficient difference, the k1th vegetation feature coefficient difference, and the k1th building feature coefficient difference respectively according to the water area feature data, the vegetation feature data, and the building feature data;

[0331] Calculate the geographical information update coefficient corresponding to the k1th geographical monitoring sub-region from the k1th water area feature coefficient difference, the k1th vegetation feature coefficient difference, and the k1th building feature coefficient difference;

[0332] Obtain the geographical information update coefficient corresponding to the k1th geographical monitoring sub-region;

[0333] The specific formula configuration is as follows:

[0334] Dxg = Syx + Zbx + Jzx;

[0335] Where Dxg is the geographical information update coefficient corresponding to the k1th geographical monitoring sub-region, Syx is the k1th water area feature coefficient difference, Zbx is the k1th vegetation feature coefficient difference, and Jzx is the k1th building feature coefficient difference;

[0336] Obtain the geographical information update coefficients corresponding to each of the second change type monitoring sub-regions respectively, to obtain multiple geographical information update coefficients, and numerically compare the geographical information update coefficient threshold with the multiple geographical information update coefficients;

[0337] Specifically as follows:

[0338] Obtain the water area feature coefficient baseline difference, the vegetation feature coefficient baseline difference, and the building feature coefficient baseline difference respectively;

[0339] Calculate the geographical information update coefficient threshold from the water area feature coefficient baseline difference, the vegetation feature coefficient baseline difference, and the building feature coefficient baseline difference;

[0340] It should be noted here that:

[0341] The water area feature coefficient baseline difference, the vegetation feature coefficient baseline difference, and the building feature coefficient baseline difference involved here are respectively the maximum water area feature coefficient difference, vegetation feature coefficient difference, and building feature coefficient difference corresponding to the first change type monitoring sub-region;

[0342] Calculate the geographical information update coefficient threshold, and the specific formula configuration is as follows:

[0343] Dxgj = Syxj + Zbxj + Jzxj;

[0344] Among them, Dxgj is the threshold of the geographical information update coefficient, Syxj is the reference difference of the water area feature coefficient, Zbxj is the reference difference of the vegetation feature coefficient, and Jzxj is the reference difference of the building feature coefficient;

[0345] When the geographical information update coefficient is greater than or equal to the threshold of the geographical information update coefficient, the second change type monitoring sub-region is divided into the first change type monitoring region;

[0346] When the geographical information update coefficient is less than the threshold of the geographical information update coefficient, the second change type monitoring sub-region is divided into the third change type monitoring region;

[0347] It should be noted here that:

[0348] In this application, the geographical information corresponding to the first change type monitoring region needs to be updated, and the geographical information corresponding to the second change type monitoring region does not need to be updated.

[0349] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to the specific implementation manners. Obviously, many modifications and changes can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principle and practical application of the present invention, so that those skilled in the art in the relevant technical field can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A method for fusing multi-source geographic information, characterized in that, It includes the following specific steps: Step A1: Mark the geographical monitoring area as the k1-th to the k-th k geographical monitoring sub-areas, and respectively obtain the area values of the first-type areas, the area values of the second-type areas, and the area values of the third-type areas in each geographical monitoring sub-area to obtain area data; Step A2: Obtain the first current feature coefficients and the first historical feature coefficients corresponding to the k1st to the kth k geographical monitoring sub-regions, and obtain water area feature data by calculating the difference between each first current feature coefficient and the corresponding first historical feature coefficient; Calculate the first current feature coefficient corresponding to the k1 geographical monitoring sub-region, and the specific formula is configured as follows: ； Among them, Tzq is the first current feature coefficient corresponding to the k1 geographical monitoring sub-region, Dph is the current pH value of the regional water body, Dys is the current value of the number of individual water areas in the region, and a1 is a set proportionality coefficient and a1>0; Step A3: Obtain the differences in vegetation characteristic coefficients corresponding to the k1-th to k-th k geographical monitoring sub-regions to obtain vegetation characteristic data; Step A4: Obtain the differences in building feature coefficients corresponding to the k1st to the kth k geo-monitoring sub-regions to obtain building feature data; In step A3, it also includes the following specific steps: Step A31: Obtain the vegetation feature coefficient difference corresponding to the k1 geographical monitoring sub-region to obtain the k1 vegetation feature coefficient difference; Step A32: Obtain the differences in vegetation characteristic coefficients corresponding to the k2nd to kth k geo-monitoring sub-regions respectively, to obtain the differences in vegetation characteristic coefficients from the k2nd to the kth k vegetation characteristic coefficients; Step A33: From the k1st to the kth k The difference in the water vegetation characteristic coefficients is defined as the vegetation characteristic data; In step A31, it also includes the following specific steps: Count the number of vegetation species in the k1 geographical monitoring area to obtain the current value of the number of regional vegetation species; Select z sample monitoring vegetations in the k1 geographical monitoring area respectively, and name them the first to the z sample monitoring vegetations respectively; Obtain the quantity values of the first to the z sample monitoring vegetations at the current moment respectively to obtain the current quantity values of the first to the z sample vegetations; Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical quantity value of the regional vegetation species corresponding to the k1 geographical monitoring sub-region and the historical quantity values of the first to the z sample vegetations according to the historical geographical information data; Calculate the k1 vegetation feature coefficient difference through the current value of the number of regional vegetation species, the historical quantity value of the regional vegetation species, the current quantity values of the first to the z sample vegetations, and the historical quantity values of the first to the z sample vegetations; Calculate the k1 vegetation feature coefficient difference, and the specific formula is configured as follows: ； Among them, Zbx is the k1 vegetation feature coefficient difference, Zld is the current value of the number of regional vegetation species, Zll is the historical quantity value of the regional vegetation species, Dq1 to Dqz are the current quantity values of the first to the z sample vegetations respectively, and Ls1 to Lsz are the historical quantity values of the first to the z sample vegetations respectively; In step A4, it also includes the following specific steps: Step A41: Obtain the building feature coefficient difference corresponding to the k1 geographical monitoring sub-region to obtain the k1 building feature coefficient difference; Step A42: Obtain the differences in building feature coefficients corresponding to the k2nd to kth k geo-monitoring sub-regions respectively, to obtain the differences in building feature coefficients from the k2nd to the kth k building feature coefficients; Step A43: From the k1st to the kth k Define the difference in building feature coefficients as building feature data; In step A41, it also includes the following specific steps: Count the value of the number of individual buildings corresponding to the k1 geographical monitoring sub-region at the current moment to obtain the first value of the number of individual buildings; Obtain the total road mileage value corresponding to the k1 geographical monitoring sub-region at the current moment to obtain the first road mileage value; Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical value of the number of individual buildings corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data to obtain the second value of the number of individual buildings; Obtain the historical total road mileage value corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data to obtain the second road mileage value; Calculate the k1 building feature coefficient difference through the first value of the number of individual buildings, the first road mileage value, the second value of the number of individual buildings, and the second road mileage value; Calculate the k1 building feature coefficient difference, and the specific formula is configured as follows: ； Among them, Jzx is the difference in the building feature coefficient of the k1-th, Dtj1 is the numerical value of the number of the first single buildings, Dtj2 is the numerical value of the number of the second single buildings, Ll c1 is the numerical value of the first road mileage, and Ll c2 is the numerical value of the second road mileage; Step A5: According to the regional area data, divide the geographical monitoring sub-regions from the k1-th to the k-th k into the first change type monitoring sub-regions and the second change type monitoring sub-regions, obtain the geographical information update coefficient corresponding to each second change type monitoring sub-region, obtain the geographical information update coefficient threshold value to perform a numerical comparison on the geographical information update coefficient corresponding to the second change type monitoring sub-region, further divide the second change type monitoring sub-regions into the first change type monitoring sub-regions and the third change type monitoring sub-regions, and obtain the regional geographical information update data; In the step A5, the following specific steps are further included: Step A51: Obtain the regional area data and, based on the regional area data, obtain the k1st to k k regional area data; Step A52: According to the area data of the k1st to k k Obtain the k1st to k k from the area data of the geographical monitoring sub-regions corresponding to the area change respectively; Step A53: Obtain the sum of changes in the regional area baseline, and from the k1st to the kth k Perform a numerical comparison between the sum of changes in the corresponding regional areas of the geographical monitoring sub-regions and the sum of changes in the regional area baseline, and from the k1st to the kth k Divide the geographical monitoring sub-regions into the first change type monitoring sub-regions and the third change type monitoring sub-regions respectively to obtain the updated regional geographical information data; In the step A52, the following specific steps are further included: Obtain the numerical values of the areas of the first type of region, the second type of region, and the third type of region corresponding to the k1-th geographical monitoring sub-region according to the area data of the k1-th region; Obtain the historical geographical information data corresponding to the k1-th geographical monitoring sub-region, and respectively obtain the historical area numerical values of the first type of region, the second type of region, and the third type of region according to the historical geographical information data; Calculate the difference between the numerical value of the area of the first type of region and the historical area numerical value of the first type of region, then take the absolute value of the obtained difference to obtain the area change value of the first type of region. Calculate the difference between the numerical value of the area of the second type of region and the historical area numerical value of the second type of region, then take the absolute value of the obtained difference to obtain the area change value of the second type of region. Calculate the difference between the numerical value of the area of the third type of region and the historical area numerical value of the third type of region, then take the absolute value of the obtained difference to obtain the area change value of the third type of region. Sum up the area change values of the first type of region, the second type of region, and the third type of region to obtain the regional area change sum corresponding to the k1-th geographical monitoring sub-region; Obtain the area changes of the corresponding regions of the k2nd to kth geographical monitoring sub-regions respectively; k ​ In the step A53, the following specific steps are further included: When the regional area change sum is greater than or equal to the reference regional area change sum, determine that the corresponding geographical monitoring sub-region is the first change type monitoring sub-region; When the regional area change sum is less than the reference regional area change sum, determine that the corresponding geographical monitoring sub-region is the second change type monitoring sub-region; Perform further update judgment on the second change type monitoring sub-region; Specifically as follows: Respectively obtain the water area feature data, the vegetation feature data, and the building feature data; When the k1-th geographical monitoring sub-region is the second change type monitoring sub-region, respectively obtain the k1-th water area feature coefficient difference, the k1-th vegetation feature coefficient difference, and the k1-th building feature coefficient difference according to the water area feature data, the vegetation feature data, and the building feature data; Calculate the k1-th water area feature coefficient difference, the k1-th vegetation feature coefficient difference, and the k1-th building feature coefficient difference to obtain the geographical information update coefficient corresponding to the k1-th geographical monitoring sub-region; Obtain the geographical information update coefficient corresponding to the k1-th geographical monitoring sub-region; The specific formula configuration is as follows: ； Among them, Dxg is the geographical information update coefficient corresponding to the k1-th geographical monitoring sub-region, Syx is the k1-th water area feature coefficient difference, Zbx is the k1-th vegetation feature coefficient difference, and Jzx is the k1-th building feature coefficient difference; Respectively obtain the geographical information update coefficients corresponding to each of the second change type monitoring sub-regions to obtain a plurality of geographical information update coefficients, and compare the geographical information update coefficient threshold values with the plurality of geographical information update coefficients numerically; Specifically as follows: Obtain the reference differences of water area characteristic coefficients, vegetation characteristic coefficients, and building characteristic coefficients respectively; Calculate the reference differences of water area characteristic coefficients, vegetation characteristic coefficients, and building characteristic coefficients to obtain the threshold of the geographic information update coefficient; When the geographic information update coefficient is greater than or equal to the threshold of the geographic information update coefficient, divide the second change type monitoring sub-region into the first change type monitoring region; When the geographic information update coefficient is less than the threshold of the geographic information update coefficient, divide the second change type monitoring sub-region into the third change type monitoring region.

2. The method for fusing multiple geographical information according to claim 1, wherein In the step A1, the following specific steps are further included: Step A11: Divide the geographical monitoring area into several geographical monitoring sub-areas of a characteristic area size, and label them as the k1th to the kth k geographical monitoring sub-areas; Step A12: Monitor the area of the k1th geographic monitoring sub-region to obtain the area data of the k1th region; Step A13: Monitor the areas of the k2nd to kth k geographical monitoring sub-regions respectively to obtain the area data of the k2nd to kth k regions; Step A14: Define the area data of the k1st to kth k area data as the area data of the region.

3. A method for fusing multi-source geographical information according to claim 2, characterized in that, In the step A12, the following specific steps are further included: Step A121: Divide the land of the k1th geographic monitoring sub-region into the first type geographic region, the second type geographic region, and the third type geographic region according to the land use type respectively; Step A122: Obtain the aerial photograph plane image of the k1th geographic monitoring sub-region, and mark the boundary of the k1th geographic monitoring sub-region on the aerial photograph plane image to obtain the first marked region; Step A123: Use the region recognition model to recognize the first type geographic region, the second type geographic region, and the third type geographic region in the aerial photograph plane image, mark the first type geographic region as the second marked region, mark the second type geographic region as the third marked region, and mark the third type geographic region as the fourth marked region to obtain the region marked image; Step A124: Convert the region marked image into a grayscale image, and count the pixel points of the first to fourth marked regions respectively to obtain the first to fourth pixel point quantity values; Step A125: Obtain the actual area value corresponding to the k1th geographic monitoring sub-region; Step A126: Calculate the actual area value corresponding to the first type geographic region from the actual area value corresponding to the k1th geographic monitoring sub-region, the first pixel point quantity value, and the second pixel point quantity value, and name it the first type region area value; Calculate the actual area value corresponding to the first type geographic region, and the specific formula configuration is as follows: ； Among them, Sm1 is the actual area value corresponding to the first type geographic region, Xs1 is the first pixel point quantity value, Xs2 is the second pixel point quantity value, and Smk1 is the actual area value corresponding to the k1th geographic monitoring sub-region; Step A127: Calculate the actual area value corresponding to the second type geographic region from the actual area value corresponding to the k1th geographic monitoring sub-region, the first pixel point quantity value, and the third pixel point quantity value, and name it the second type region area value; Step A128: Calculate the actual area value corresponding to the third type geographic region from the actual area value corresponding to the k1th geographic monitoring sub-region, the first pixel point quantity value, and the fourth pixel point quantity value, and name it the third type region area value; Step A129: Define the area values of the first type of region, the second type of region, and the third type of region as the area data of the k1 region.

4. A method for fusing multiple geographical information according to claim 3, characterized in that, In the said step A123, the following specific steps are further included: Obtain multiple aerial plane images of different geographical regions through big data crawler technology, and mark the first type of geographical region, the second type of geographical region, and the third type of geographical region in each aerial plane image respectively to obtain sample plane image data; Divide the sample plane image data into an identification test set and an identification training set, create an image recognition model through an artificial intelligence platform, use the identification training set to train the image recognition model, and train the image recognition model at least once for each image in the identification training set. Use the identification test set to test the image recognition model and obtain the image recognition accuracy rate; If the image recognition accuracy rate is greater than or equal to the target recognition accuracy rate, the image recognition model training is completed to obtain a region recognition model. If the image recognition accuracy rate is less than the target recognition accuracy rate, continue to use the identification training set to train the image recognition model until the image recognition accuracy rate is greater than or equal to the target recognition accuracy rate.

5. A method for fusing multiple geographical information according to claim 1, characterized in that In the said step A2, the following specific steps are further included: Step A21: Obtain the difference in water area characteristic coefficients corresponding to the k1 geographical monitoring sub-region to obtain the k1 water area characteristic coefficient difference; Step A22: Obtain the differences in water area characteristic coefficients corresponding to the k2nd to kth k geo-monitoring sub-regions respectively, to obtain the differences in water area characteristic coefficients from the k2nd to the kth k water area characteristic coefficients; Step A23: From the k1th to the kth k The difference in water area characteristic coefficients is defined as water area characteristic data.

6. A method for fusing multi-source geographic information according to claim 5, characterized in that In the said step A21, the following specific steps are further included: Randomly select m first-type geographical regions in the k1 geographical monitoring sub-region as characteristic monitoring waters, and name them the first to the mth characteristic monitoring waters respectively; Obtain the current pH value of the regional water body; Specifically as follows: Collect water body samples of unit volume at different positions in the first characteristic monitoring water area to obtain multiple water body samples, measure the pH value of each water body sample respectively to obtain multiple sample pH values, calculate the average of the multiple sample pH values to obtain the water body pH value corresponding to the first characteristic monitoring water area, and name it the first water area pH value; Obtain the water body pH values corresponding to the second to the mth characteristic monitoring waters respectively to obtain the second to the mth water area pH values, calculate the average of the first to the mth water area pH values to obtain the current pH value of the regional water body; Obtain the number of single waters corresponding to the k1 geographical monitoring sub-region to obtain the current value of the number of single waters in the region; Calculate the first current characteristic coefficient corresponding to the k1 geographical monitoring sub-region through the current pH value of the regional water body and the current value of the number of single waters in the region; Obtain the historical geographical information data corresponding to the k1 geographical monitoring sub-region, and obtain the historical pH value of the regional water body and the historical value of the number of single waters in the region corresponding to the k1 geographical monitoring sub-region according to the historical geographical information data; Calculate the first historical characteristic coefficient corresponding to the k1 geographical monitoring sub-region through the historical pH value of the regional water body and the historical value of the number of single waters in the region corresponding to the k1 geographical monitoring sub-region; Calculate the difference between the first current characteristic coefficient and the first historical characteristic coefficient to obtain the k1 water area characteristic coefficient difference.

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