Regional habitat connectivity determination method and device, equipment, medium and product

Abstract

The invention discloses a regional habitat connectivity determination method and device, equipment, a medium and a product, and is applied to the field of ecology. The method comprises the following steps: firstly, taking a plurality of first distance values as reference habitat communication thresholds of birds in a target area, and respectively determining corresponding target indexes; then taking a logarithm value, and establishing a fitting curve according to a corresponding relation between the first logarithm value and the second logarithm value so as to obtain a first distance value corresponding to an inflection point of the fitting curve; and determining an actual habitat connectivity threshold based on the maximum migration distance of the target bird and the first distance value corresponding to the inflection point, and determining the habitat connectivity of the target area based on the actual habitat connectivity threshold. According to the method, the distance abrupt change point causing connectivity abrupt change can be accurately found out by fitting the curve and taking the inflection point, and the accurate actual habitat connectivity threshold value is further determined by combining the maximum migration distance of the target bird, so that the accurate connectivity is obtained.

Description

Technical Field

[0001] The present application belongs to the field of ecology, and in particular, relates to a method, device, equipment, medium and product for determining regional habitat connectivity. Background Art

[0002] For wading birds that live in marshes and floodplains and rely on water for survival, the connectivity of habitats within the region is crucial, so it is necessary to calculate the connectivity of the region. For an area, it is divided into multiple habitat patches. Only when the distance between two habitat patches is less than the habitat connectivity threshold, the two habitat patches are connected.

[0003] In the process of determining the habitat connectivity of bird habitats, it is necessary to determine the corresponding habitat connectivity threshold. At present, for the habitat connectivity threshold of birds, the staff generally estimates a habitat connectivity threshold based on experience and calculates the habitat connectivity. The habitat connectivity threshold obtained in this way is not accurate, which leads to a large error in the determined habitat connectivity. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment, medium and product for determining regional habitat connectivity, which can determine an accurate habitat connectivity threshold and thus obtain accurate habitat connectivity.

[0005] On the one hand, an embodiment of the present application provides a method for determining regional habitat connectivity, comprising:

[0006] Within a preset distance range, taking a plurality of first distance values ​​at preset intervals;

[0007] Using each of the first distance values ​​as a reference habitat connectivity threshold for birds in the target area, and determining a corresponding target index respectively; the target index includes a connectivity index and / or an equivalent connectivity index;

[0008] Determine a first logarithmic value corresponding to each of the first distance values ​​and a second logarithmic value corresponding to each of the target indexes;

[0009] Establishing a fitting curve of a power function of a preset order based on the corresponding relationship between the first pair of values ​​and the second pair of values;

[0010] Obtaining the first distance value corresponding to the inflection point of the fitting curve;

[0011] Determining an actual habitat connectivity threshold of the target birds in the target area based on the maximum migration distance of the target birds and the first distance value corresponding to the inflection point; the actual habitat connectivity threshold belongs to the preset distance range;

[0012] Based on the actual habitat connectivity threshold, the habitat connectivity of the target area is determined.

[0013] On the other hand, before taking a plurality of first distance values ​​at preset intervals within the preset distance range, the method further includes:

[0014] Determining an initial reference habitat connectivity threshold that makes the number of components corresponding to the target area greater than 1;

[0015] Increasing the initial reference habitat connectivity threshold with a preset step size until the corresponding number of components becomes 1, so as to obtain a maximum reference habitat connectivity threshold;

[0016] The preset distance range is determined based on the maximum reference habitat connectivity threshold.

[0017] On the other hand, after determining the preset distance range based on the maximum reference habitat connectivity threshold and before taking a plurality of first distance values ​​at preset intervals within the preset distance range, the method further includes:

[0018] Dividing the preset distance range into a plurality of sub-ranges;

[0019] Determine the corresponding preset interval for each of the sub-intervals; the preset interval is positively correlated with the distance between the sub-intervals;

[0020] The step of taking a plurality of first distance values ​​at preset intervals within a preset distance range comprises:

[0021] For different sub-intervals, the first distance value is taken at the corresponding preset intervals.

[0022] On the other hand, establishing a fitting curve of a power function of a preset order based on the correspondence between the first logarithmic value and the second logarithmic value includes:

[0023] Establishing the fitting curves of the cubic function and the quartic function based on the corresponding relationship between the first logarithmic value and the second logarithmic value;

[0024] Correspondingly, the obtaining the first distance value corresponding to the inflection point of the fitting curve includes:

[0025] The first distance value corresponding to each inflection point of each fitting curve is obtained respectively.

[0026] On the other hand, determining the actual habitat connectivity threshold of the target birds in the target area based on the maximum migration distance of the target birds and the first distance value corresponding to the inflection point includes:

[0027] From the first distance values ​​corresponding to the inflection points, a second distance value that satisfies a similarity condition with the maximum migration distance of the target bird is selected;

[0028] Based on the second distance value, the actual habitat connectivity threshold is determined.

[0029] On the other hand, determining the habitat connectivity of the target area based on the actual habitat connectivity threshold comprises:

[0030] In the target area, determining each pair of habitat patches whose distance is less than the actual habitat connectivity threshold, and obtaining a plurality of habitat patch groups;

[0031] The habitat connectivity of the target area is determined based on the number of links of the shortest paths between two habitat patches in each habitat patch group, the area of ​​each habitat patch in the target area, and the area of ​​the target area.

[0032] On the other hand, before using each of the first distance values ​​as a reference habitat connectivity threshold for birds in the target area to determine the corresponding target index respectively, the method further includes:

[0033] Acquire a remote sensing image dataset of the target area within a target time period;

[0034] The seasonal water bodies in the remote sensing image data set are determined as the habitat patches in the target area.

[0035] On the other hand, the remote sensing image data set includes the seasonal water bodies and permanent water bodies;

[0036] Before determining the seasonal water bodies as the habitat patches in the target area, the method further comprises:

[0037] Acquire surface water data of the target area within the target time period;

[0038] Obtaining a first coincidence rate between the permanent water body and the rivers, lakes and reservoirs in the surface water body data, and a second coincidence rate between the seasonal water body and the floodplain, beach and swamp in the surface water body data;

[0039] When both the first overlap rate and the second overlap rate meet the overlap requirement, the remote sensing image dataset is determined to be valid, and the step of determining the seasonal water bodies in the remote sensing image dataset as the habitat patches in the target area is entered.

[0040] In another aspect, an embodiment of the present application provides a device for determining regional habitat connectivity, the device comprising:

[0041] A first acquisition module, used to obtain a plurality of first distance values ​​at preset intervals within a preset distance range;

[0042] A first determination module is used to use each of the first distance values ​​as a reference habitat connectivity threshold for birds in a target area, and determine a corresponding target index respectively; the target index includes a connectivity index and / or an equivalent connectivity index;

[0043] A second determination module, used to determine a first logarithmic value corresponding to each of the first distance values ​​and a second logarithmic value corresponding to each of the target indexes;

[0044] An establishing module, used for establishing a fitting curve of a power function of a preset order based on the corresponding relationship between the first pair of values ​​and the second pair of values;

[0045] A second acquisition module, used to acquire the first distance value corresponding to the inflection point of the fitting curve;

[0046] A third determination module is used to determine an actual habitat connectivity threshold of the target birds in the target area based on the maximum migration distance of the target birds and the first distance value corresponding to the inflection point; the actual habitat connectivity threshold belongs to the preset distance range;

[0047] The fourth determination module is used to determine the habitat connectivity of the target area based on the actual habitat connectivity threshold.

[0048] In yet another aspect, an embodiment of the present application provides a device for determining regional habitat connectivity, the device comprising: a processor and a memory storing computer program instructions;

[0049] When the processor executes the computer program instructions, the method for determining regional habitat connectivity as described above is implemented.

[0050] On the other hand, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, the method for determining regional habitat connectivity as described above is implemented.

[0051] On the other hand, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for determining regional habitat connectivity as described above.

[0052] A method for determining regional habitat connectivity in an embodiment of the present application first takes multiple first distance values ​​and uses them as reference habitat connectivity thresholds for birds in the target area to determine the corresponding target indexes. Then take the logarithmic value, and establish a fitting curve based on the correspondence between the first logarithmic value and the second logarithmic value to obtain the first distance value corresponding to the inflection point of the fitting curve. Furthermore, the actual habitat connectivity threshold can be determined based on the maximum migration distance of the target bird and the first distance value corresponding to the inflection point. Based on the actual habitat connectivity threshold, the habitat connectivity of the target area can be determined. The embodiment of the present application can accurately find the distance mutation point that causes the connectivity mutation by fitting the curve and taking the inflection point, and then further determine the accurate actual habitat connectivity threshold in combination with the maximum migration distance of the target bird. It can be seen that this scheme can accurately determine the actual habitat connectivity threshold of the target area, thereby obtaining accurate connectivity. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0054] Figure 1 A schematic diagram showing a flow chart of a method for determining regional habitat connectivity provided by an embodiment of the present application;

[0055] Figure 2 The cubic power function fitting curve of the distance and connectivity index corresponding to the first interval division scheme is shown;

[0056] Figure 3 The fourth power function fitting curve of the distance and connectivity index corresponding to the first interval division scheme is shown;

[0057] Figure 4 The cubic power function fitting curve of the distance and the equivalent connectivity index corresponding to the first interval division scheme is shown;

[0058] Figure 5 The fourth power function fitting curve of the distance and the equivalent connectivity index corresponding to the first interval division scheme is shown;

[0059] Figure 6 The cubic power function fitting curve of the distance and connectivity index corresponding to the second interval division scheme is shown;

[0060] Figure 7 The fourth power function fitting curve of the distance and connectivity index corresponding to the second interval division scheme is shown;

[0061] Figure 8The cubic power function fitting curve of the distance and the equivalent connectivity index corresponding to the second interval division scheme is shown;

[0062] Fig. 9 The fourth power function fitting curve of the distance and the equivalent connectivity index corresponding to the second interval division scheme is shown;

[0063] Fig.10 A schematic diagram showing the structure of a device for determining regional habitat connectivity provided by an embodiment of the present application is shown;

[0064] Fig.11 A schematic diagram of the hardware structure of a device for determining regional habitat connectivity provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0065] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0066] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "include..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0067] In order to solve the problems of the traditional solution and calculate the accurate habitat connectivity in the bird living area, the embodiment of the present application provides a method, device, equipment, medium and product for determining regional habitat connectivity. The method for determining regional habitat connectivity provided by the embodiment of the present application is first introduced below. Figure 1 FIG. 1 is a flow chart showing a method for determining regional habitat connectivity provided by an embodiment of the present application. Figure 1 As shown, the method includes the following steps S101 to S107:

[0068] S101: within a preset distance range, taking a plurality of first distance values ​​at preset intervals.

[0069] The idea of ​​the solution proposed in the embodiment of the present application is to find the distance mutation point (i.e., habitat connectivity threshold) that causes connectivity mutation by fitting the curve and taking the inflection point. First, before performing curve fitting, it is necessary to determine the preset distance range of the habitat connectivity threshold in the target area. The specific size of the preset distance range is not limited and can be set according to demand, and it is necessary to include all possible values ​​of the habitat connectivity threshold in the target area.

[0070] Secondly, in order to fit the curve, multiple sample points (first distance values) need to be taken, and the preset interval of the values ​​is selected according to the actual situation. Generally, in the interval with smaller distance within the preset distance range, the preset interval is set smaller to obtain more first distance values ​​and ensure the accuracy of curve fitting. In the interval with larger distance within the preset distance range, the preset interval is set larger to avoid increasing the calculation pressure due to too many first distance values.

[0071] S102: Using each first distance value as a reference habitat connectivity threshold for birds in the target area, and determining a corresponding target index respectively.

[0072] Here, the target index includes a connectivity index and / or an equivalent connectivity index, which is selected according to the needs. After obtaining multiple first distance values, each first distance value is used as a reference habitat connectivity threshold for birds in the target area, and the corresponding value is obtained through the calculation formula of the connectivity index and the equivalent connectivity index.

[0073] S103: Determine a first logarithmic value corresponding to each first distance value and a second logarithmic value corresponding to each target index.

[0074] S104: establishing a fitting curve of a power function of a preset order based on the corresponding relationship between the first pair of values ​​and the second pair of values.

[0075] In order to fit the curve, the first logarithmic value corresponding to the first distance value and the second logarithmic value corresponding to each target index are first calculated. Then, the first logarithmic value is used as the independent variable and the second logarithmic value is used as the dependent variable to establish a fitting curve of a preset power function.

[0076] The preset times here are set according to actual needs, and can be set to one or more. For example, it can be set to a cubic power function, and the corresponding function form is: y = ax 3 +bx 2 +cx+y0, y is the dependent variable, x is the independent variable, a, b, c, y0 are constants. If multiple preset times are set, the fitting curves of the power functions of the corresponding times need to be fitted respectively. For example, the fitting curves of the cubic power function and the quartic power function can be fitted at the same time.

[0077] S105: Obtain a first distance value corresponding to the inflection point of the fitting curve.

[0078] The habitat connectivity threshold of the target birds in the target area is the distance mutation point that causes the connectivity mutation. This point is usually the inflection point in the fitting curve. Therefore, it is necessary to obtain the first distance value corresponding to the inflection point of the fitting curve.

[0079] There may be multiple fitting curves obtained in the above steps. For example, the connectivity index and the equivalent connectivity index may correspond to a fitting curve respectively, and the power functions of different orders may also correspond to a fitting curve respectively. In addition, there may be multiple inflection points in each fitting curve. For example, there are two inflection points in the fitting curve corresponding to the fourth power function. In practical applications, it is necessary to obtain the first distance value corresponding to each inflection point of each fitting curve.

[0080] S106: Determine an actual habitat connectivity threshold of the target birds in the target area based on the maximum migration distance of the target birds and the first distance value corresponding to the inflection point.

[0081] In practical applications, the actual habitat connectivity threshold of the target birds in the target area is affected by the maximum migration distance of the target birds and is close to the maximum migration distance of the target birds. Therefore, the second distance value close to the maximum migration distance of the target birds can be found from the first distance value corresponding to the inflection point, and then the actual habitat connectivity threshold can be determined.

[0082] It should be noted that the actual habitat connectivity threshold is within the preset distance range, so when determining the actual habitat connectivity threshold based on the first distance value, the first distance values ​​outside the preset distance range may be filtered out first.

[0083] S107: Determine the habitat connectivity of the target area based on the actual habitat connectivity threshold.

[0084] The specific scope of the target area and the specific species of the target birds mentioned above are determined according to the actual situation. After obtaining the actual habitat connectivity threshold of the target birds in the target area, the habitat connectivity of the target area can be determined by the corresponding calculation formula.

[0085] The habitat connectivity of the target area can be measured based on the landscape ecology connectivity index of graph theory, including the overall connectivity index IIC, the equivalent connectivity index EC(IIC), the patch importance index dIIC and the number of components NC.

[0086] The connectivity index measures the degree of connectivity in a region, ranging from 0 to 1, reflecting the degree of connectivity between habitat patches in the target area. The larger the value, the greater the connectivity of the region. The patch importance index measures the impact of removing a patch in the landscape on the connectivity index, reflecting the impact on the overall connectivity if a single patch is removed. The equivalent connectivity index is the arithmetic square root of the numerator of the connectivity index; the number of components refers to the whole composed of functionally or structurally interconnected patches. Isolated patches form a component, and there is no functional relationship between different components. Therefore, the denser the patches in the landscape, the fewer the number of components.

[0087] The calculation formulas of connectivity index IIC, equivalent connectivity index EC(IIC) and patch importance index dIIC are as follows:

[0088]

[0089] In formulas (1) to (3), n is the number of plaques; a i and a j are the areas of patch i and patch j respectively; A L is the area of ​​the study area; nl ij is the number of links in the shortest path from patch i to patch j; IIC remove It represents the overall index of the remaining patches after the patches are removed. It should be noted that the distance between patch i and patch j is less than the actual habitat connectivity threshold determined above.

[0090] A method for determining regional habitat connectivity in an embodiment of the present application first takes multiple first distance values ​​and uses them as reference habitat connectivity thresholds for birds in the target area to determine the corresponding target indexes. Then take the logarithmic value, and establish a fitting curve based on the correspondence between the first logarithmic value and the second logarithmic value to obtain the first distance value corresponding to the inflection point of the fitting curve. Furthermore, the actual habitat connectivity threshold can be determined based on the maximum migration distance of the target bird and the first distance value corresponding to the inflection point. Based on the actual habitat connectivity threshold, the habitat connectivity of the target area can be determined. The embodiment of the present application can accurately find the distance mutation point that causes the connectivity mutation by fitting the curve and taking the inflection point, and then further determine the accurate actual habitat connectivity threshold in combination with the maximum migration distance of the target bird. It can be seen that this scheme can accurately determine the actual habitat connectivity threshold of the target area, thereby obtaining accurate connectivity.

[0091] In a specific implementation, before determining the first distance value, it is necessary to first determine a preset distance range. Therefore, in this embodiment, before taking multiple first distance values ​​at preset intervals within the preset distance range, the preset distance range is determined by the following steps: first determine an initial reference habitat connectivity threshold that makes the number of components corresponding to the target area greater than 1; then increase the initial reference habitat connectivity threshold with a preset step length until the corresponding number of components becomes 1, so as to obtain the maximum reference habitat connectivity threshold; finally, determine the preset distance range based on the maximum reference habitat connectivity threshold.

[0092] For example, we can start from 100m and increase it in steps of 100m, and calculate the corresponding number of components NC. When the value of the number of components drops to 1, the corresponding distance is the maximum reference habitat connectivity threshold Dmax.

[0093] The solution provided in the embodiment of the present application can determine the maximum reference habitat connectivity threshold by calculating the corresponding number of components, thereby ensuring that the value range of the first distance value is more reasonable and the fitted curve is more in line with the requirements. The calculated actual habitat connectivity threshold needs to be within the preset distance range to ensure that the determined actual habitat connectivity threshold also meets the actual situation.

[0094] When selecting the first distance value, it is selected from the preset distance range at a preset interval. Therefore, it is necessary to determine the preset interval after determining the preset distance range based on the maximum reference habitat connectivity threshold and before taking multiple first distance values ​​at preset intervals within the preset distance range.

[0095] The embodiment of the present application provides a specific preset interval determination scheme, which first divides the preset distance range into multiple sub-intervals, then determines the corresponding preset interval for each sub-interval, and sets the preset interval to be positively correlated with the distance size of the sub-interval. Correspondingly, when taking the first distance value, for different sub-intervals, the first distance value is taken with the corresponding preset interval.

[0096] Here are two options: Option 1: Within 10 to 100m, set the preset interval to 10m. Within 100 to 1000m, set the preset interval to 100m. Above 1000m, set the preset interval to 1000m. Option 2: Within 10 to 100m, set 10m, 50m and 100m respectively, and within 100-1000m, set the preset interval to 100m, and above 1000m, set the preset interval to 1000m.

[0097] In this embodiment, the preset distance range is divided into multiple sub-intervals, and the preset interval is set to be positively correlated with the size of the sub-interval distance. Compared with the sub-intervals of the large distance range, more first distance values ​​can be obtained in the sub-intervals of the small distance range, thereby ensuring the accuracy of the fitting curve and avoiding excessive calculation pressure caused by obtaining too many first distance values.

[0098] The above embodiment mentioned that the value of the preset number is determined according to actual needs. In practical applications, the cubic function and the quartic function can usually meet the needs. Therefore, the fitting curves of the cubic function and the quartic function are established based on the corresponding relationship between the first pair of values ​​and the second pair of values; and then the first distance values ​​corresponding to the inflection points of each fitting curve are obtained respectively.

[0099] The embodiment of the present application can efficiently determine the inflection point by establishing fitting curves of cubic function and quartic function. Compared with functions of higher powers, the calculation process is simpler and it can also ensure that the obtained inflection point meets the requirements.

[0100] In actual application, there is no limitation on how to determine the actual habitat connectivity threshold based on the first distance values ​​corresponding to the inflection points. Because the actual habitat connectivity threshold is close to the maximum migration distance of the target bird, the second distance value that satisfies the similarity condition with the maximum migration distance of the target bird can be selected from the first distance values ​​corresponding to the inflection points; then the actual habitat connectivity threshold is determined based on the second distance value. The similarity condition is set according to the actual situation.

[0101] In practical applications, the cubic power function is preferred when fitting the curve, and the inflection points of each curve are obtained according to the curve fitting results. Then the average value of the distances corresponding to the inflection points of the two curves can be taken as the threshold distance. It should be noted that when selecting the threshold distance, it must be ensured that it is not greater than Dmax and does not exceed the maximum threshold of the bird flight distance (40 kilometers). When the threshold distance obtained by the cubic power function does not meet the above requirements, the quartic power function can be fitted. At this time, each curve has two inflection points. The average value of the distances corresponding to the first inflection point and the second inflection point of the two curves is taken to obtain two distance thresholds. Compared with the bird flight threshold distance, the value that meets the following conditions is selected as the distance threshold: closer to 10-40 kilometers, not greater than Dmax, and does not exceed the bird flight distance threshold of 40 kilometers.

[0102] The following is an explanation of the habitat connectivity threshold determination scheme using two specific examples.

[0103] In Example 1, the intervals from 10 to 100 m are 10 m apart, the intervals from 100 to 1000 m are 100 m apart, and the intervals above 1000 m are 1000 m apart. The first distance value is taken, and the IIC value and EC (IIC) value corresponding to each distance are calculated.

[0104] Figure 2 The cubic power function fitting curve of the distance and connectivity index corresponding to the first interval division scheme is shown. Figure 2As shown, a scatter plot is made with ln(distance) as the horizontal coordinate and ln(IIC) as the vertical coordinate, and a curve is used to fit the scattered points. The scattered points are fitted with a cubic power function curve. The curve equation has an inflection point, the horizontal coordinate of the inflection point is 13.9166, and the corresponding distance is 1106375m. Figure 3 The fourth power function fitting curve of the distance and connectivity index corresponding to the first interval division scheme is shown. Figure 4 As shown, the scattered points are fitted with a fourth power function curve. The curve equation has two inflection points, with horizontal coordinates of 4.0662 and 9.0337, and corresponding distances of 58.3m and 8380.8m.

[0105] Figure 4 The cubic power function fitting curve of the distance and equivalent connectivity index corresponding to the first interval division scheme is shown. Figure 4 As shown in the figure, a scatter plot is made with ln(distance) as the horizontal coordinate and ln(EC(IIC)) as the vertical coordinate, and a curve is used to fit the scattered points. The scattered points are fitted with a cubic power function curve. The curve equation has an inflection point with a horizontal coordinate of 13.9583, corresponding to a distance of 1153486m. Figure 5 The fourth power function fitting curve of the distance and equivalent connectivity index corresponding to the first interval division scheme is shown. Figure 5 As shown, the scattered points are fitted with a fourth power function curve. The curve equation has two inflection points, with horizontal coordinates of 4.0567 and 8.9932, and corresponding distances of 57.8m and 8048.2m.

[0106] ln(IIC), ln(EC(IIC)) and ln(distance) fitting curves are found, and the inflection points of the fitting curves are 58.3m, 8380.8m, 57.8m, and 8048.2m. The two inflection points with distances of 58.3m and 57.8m correspond, and the average value is 58.05m. The two inflection points with distances of 8380.8m and 8048.2m correspond, and the average value is 8214.5m. 8214.5m is close to the one-time diffusion distance of migratory birds (that is, the maximum migration distance of target birds, which is about 10 to 40 kilometers for different migratory birds), so the threshold distance is set to 8.2km.

[0107] In Example 2, 10-100m is set to 10m, 50m, 100m, 100-1000m is set to every 100m, and above 1000m is set to every 1000m. The first distance value is taken. And the IIC value and EC (IIC) value corresponding to each distance are calculated.

[0108] Figure 6 The cubic power function fitting curve of the distance and connectivity index corresponding to the second interval division scheme is shown. Figure 6As shown, a scatter plot is made with ln(distance) as the horizontal coordinate and ln(IIC) as the vertical coordinate, and a curve is used to fit the scattered points. The scattered points are fitted with a cubic power function curve. The curve equation has an inflection point, the horizontal coordinate of the inflection point is 11.3571, and the corresponding distance is 85570m. Figure 7 The fourth power function fitting curve of the distance and connectivity index corresponding to the second interval division scheme is shown. The scattered points are fitted with the fourth power function curve, and the curve equation has two inflection points, with the horizontal coordinates of the inflection points being 4.1427 and 8.9972, and the corresponding distances being 62.9m and 8080.4m.

[0109] Figure 8 The cubic power function fitting curve of the distance and equivalent connectivity index corresponding to the second interval division scheme is shown. Figure 8 As shown in the figure, a scatter plot is made with ln(distance) as the horizontal coordinate and ln(EC(IIC)) as the vertical coordinate, and a curve is used to fit the scattered points. The scattered points are fitted with a cubic power function curve. The curve equation has an inflection point, the horizontal coordinate of the inflection point is 11.3809, and the corresponding distance is 87631m. Fig. 9 The fourth power function fitting curve of the distance and equivalent connectivity index corresponding to the second interval division scheme is shown. Fig. 9 As shown, the scattered points are fitted with a fourth power function curve. The curve equation has two inflection points, with horizontal coordinates of 4.316 and 8.2992, and corresponding distances of 74.8m and 4020.6m.

[0110] ln(IIC), ln(EC(IIC)) and ln(distance) fitting curves were used to find the inflection points of the fitting curves. The distances corresponding to the inflection points were 62.9m, 8080.4m, 74.8m and 4020.6m. The two inflection points at distances of 62.9m and 74.8m corresponded, and the average value was 68.85m. The two inflection points at distances of 8080.4m and 4020.6m corresponded, and the average value was 6050.5m. 6050.5m is close to the one-time diffusion distance of migratory birds (10 to 40 kilometers), so the threshold distance was set to 6km.

[0111] Because the threshold distance of 8.2 km in Example 1 is closer to the bird flight distance threshold (10-40 kilometers) than the threshold distance of 6 km in Example 2, 8.2 km was finally selected as the threshold distance for bird habitat connectivity.

[0112] It can be seen that the preset interval division scheme of Example 1 is more suitable for the selection of the threshold distance than the scheme in Example 2, and the scheme of Example 1 is more recommended for the selection of the threshold distance.

[0113] The embodiment of the present application provides a specific method for determining the actual habitat connectivity threshold value, by selecting a second distance value close to the maximum migration distance of the target bird, and then determining the actual habitat connectivity threshold value based on the second distance value, thereby ensuring the accuracy of the actual habitat connectivity threshold value.

[0114] When determining the habitat connectivity of the target area based on the actual habitat connectivity threshold, the habitat patches (i.e., patch i and patch j in the above text) whose distance is less than the actual habitat connectivity threshold can be determined in the target area to obtain multiple habitat patch groups. Then, the habitat connectivity of the target area is determined based on the number of links of the shortest path between two habitat patches in each habitat patch group, the area of ​​each habitat patch in the target area, and the area of ​​the target area.

[0115] After obtaining the actual habitat connectivity threshold, the embodiment of the present application can determine the habitat patch group whose distance is less than the actual habitat connectivity threshold, and then calculate the connectivity through the habitat patch group to obtain the accurate habitat connectivity of the target area.

[0116] In practical applications, when calculating various indicators to measure connectivity, it is necessary to first obtain data of the target area and determine the habitat patches of the target area. Therefore, before using each first distance value as the reference habitat connectivity threshold of birds in the target area and determining the corresponding target index, the remote sensing image dataset of the target area in the target time period can be obtained; then the seasonal water bodies in the remote sensing image dataset are determined as the habitat patches in the target area.

[0117] The embodiment of the present application directly uses seasonal water bodies in the remote sensing image data set as habitat patches in the target area, which is efficient and in line with actual conditions.

[0118] Before seasonal water bodies are identified as habitat patches in a target area, the reliability of the remote sensing image dataset may be verified first. Therefore, this embodiment provides a verification solution.

[0119] First, the surface water data of the target area in the target time period is obtained, and then the first overlap ratio of permanent water bodies and rivers, lakes and reservoirs in the surface water data, and the second overlap ratio of seasonal water bodies and floodplains, beaches and swamps in the surface water data are obtained. When both the first overlap ratio and the second overlap ratio meet the overlap requirements, the remote sensing image dataset is determined to be valid, and the step of determining the seasonal water bodies in the remote sensing image dataset as the habitat patches in the target area is entered.

[0120] The remote sensing image dataset includes seasonal water bodies and permanent water bodies. You can directly download the published global 30m resolution surface water remote sensing image dataset and extract seasonal water bodies and permanent water bodies of categories 2 and 3 for calculation and comparison.

[0121] Load the remote sensing images of the wet and dry years in the past ten years, and use a combination of automatic extraction assistance and manual visual interpretation to compare the surface water data of the corresponding years with the overlap rate of rivers, lakes, reservoirs, floodplains, beaches and swamps in the remote sensing image data within the basin, and calibrate and verify the data. When the overlap rate is greater than 90%, it means that the data can represent the actual situation.

[0122] Birds need shallow marsh wetland environments for their growth and habitat. Bird habitats change dynamically in wet and dry years. The seasonal water bodies in surface water data are consistent with the annual dynamic changes in migratory bird habitats. Therefore, seasonal water bodies are regarded as bird habitat patches.

[0123] Before taking seasonal water bodies as habitat patches in target areas, the embodiment of the present application performs a verification through surface water body data to ensure the reliability of the data.

[0124] In order to solve the above technical problems, the embodiment of the present application further provides a device for determining regional habitat connectivity. Fig.10 FIG. 4 is a schematic diagram showing the structure of a device for determining regional habitat connectivity provided by an embodiment of the present application; Fig.10 As shown, the device includes the following modules:

[0125] A first acquisition module 1001 is used to obtain a plurality of first distance values ​​at preset intervals within a preset distance range;

[0126] The first determination module 1002 is used to use each first distance value as a reference habitat connectivity threshold of birds in the target area, and determine the corresponding target index respectively; the target index includes a connectivity index and / or an equivalent connectivity index;

[0127] The second determination module 1003 is used to determine a first logarithmic value corresponding to each first distance value and a second logarithmic value corresponding to each target index;

[0128] Establishing module 1004, used to establish a fitting curve of a power function of a preset order based on the corresponding relationship between the first logarithmic value and the second logarithmic value;

[0129] The second acquisition module 1005 is used to acquire a first distance value corresponding to the inflection point of the fitting curve;

[0130] The third determination module 1006 is used to determine the actual habitat connectivity threshold of the target birds in the target area based on the maximum migration distance of the target birds and the first distance value corresponding to the inflection point; the actual habitat connectivity threshold belongs to the preset distance range;

[0131] The fourth determination module 1007 is used to determine the habitat connectivity of the target area based on the actual habitat connectivity threshold.

[0132] In some embodiments, the apparatus for determining regional habitat connectivity further includes: a fifth determination module for determining an initial reference habitat connectivity threshold that makes the number of components corresponding to the target area greater than 1 before taking a plurality of first distance values ​​at preset intervals within a preset distance range;

[0133] A growth module, used to increase the initial reference habitat connectivity threshold with a preset step size until the corresponding number of components becomes 1, so as to obtain the maximum reference habitat connectivity threshold;

[0134] The fifth determination module is further used to determine a preset distance range based on a maximum reference habitat connectivity threshold.

[0135] In some embodiments, the apparatus for determining regional habitat connectivity further includes: a partitioning module for dividing the preset distance range into a plurality of sub-intervals after determining the preset distance range based on the maximum reference habitat connectivity threshold and before taking a plurality of first distance values ​​at preset intervals within the preset distance range;

[0136] A sixth determination module is used to determine a corresponding preset interval for each sub-interval; the preset interval is positively correlated with the distance between the sub-intervals;

[0137] The third acquisition module is used to obtain the first distance value at corresponding preset intervals for different sub-intervals.

[0138] In some embodiments, a module is established, specifically for:

[0139] According to the corresponding relationship between the first pair of values ​​and the second pair of values, fitting curves of the cubic function and the quartic function are established;

[0140] Correspondingly, the second acquisition module is specifically used for:

[0141] The first distance value corresponding to each inflection point of each fitting curve is obtained respectively.

[0142] In some embodiments, the third determination module is specifically configured to:

[0143] From each first distance value corresponding to the inflection point, a second distance value that satisfies a similarity condition with the maximum migration distance of the target bird is selected;

[0144] Based on the second distance value, an actual habitat connectivity threshold is determined.

[0145] In some embodiments, the fourth determining module is specifically configured to:

[0146] In the target area, determine the habitat patches with distances less than the actual habitat connectivity threshold, and obtain multiple habitat patch groups;

[0147] The habitat connectivity of the target area was determined based on the number of links in the shortest path between two habitat patches in each habitat patch group, the area of ​​each habitat patch in the target area, and the area of ​​the target area.

[0148] In some embodiments, the apparatus for determining regional habitat connectivity further includes: a fourth acquisition module, further used to: before using each first distance value as a reference habitat connectivity threshold for birds in the target area and determining the corresponding target index respectively, acquire a remote sensing image dataset of the target area within a target time period;

[0149] The seventh determination module is also used to determine the seasonal water bodies in the remote sensing image data set as various habitat patches in the target area.

[0150] In some embodiments, the remote sensing imagery dataset includes seasonal water bodies as well as permanent water bodies;

[0151] The fourth acquisition module is also used to obtain the surface water body data of the target area within the target time period before the seasonal water body is determined as each habitat patch in the target area; and obtain the first coincidence rate of rivers, lakes and reservoirs in the permanent water body and the surface water body data, and the second coincidence rate of river floodplains, beach lands and swamps in the seasonal water body and the surface water body data;

[0152] The device for determining regional habitat connectivity also includes: a determination module, which is used to determine that the remote sensing image data set is valid when the first overlap rate and the second overlap rate both meet the overlap road requirements, and enter the step of determining the seasonal water bodies in the remote sensing image data set as the habitat patches in the target area.

[0153] The device provided in the embodiment of the present application is the same as the method in the above embodiment, so both have the same embodiments and beneficial effects, which will not be repeated here.

[0154] Fig.11 FIG. 4 is a schematic diagram showing the hardware structure of a device for determining regional habitat connectivity provided by an embodiment of the present application; Fig.11 As shown, the apparatus for determining regional habitat connectivity may include a processor 1101 and a memory 1102 storing computer program instructions.

[0155] Specifically, the processor 1101 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0156] The memory 1102 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 1102 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 1102 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 1102 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 1102 is a non-volatile solid-state memory.

[0157] The memory 1102 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0158] The processor 1101 reads and executes computer program instructions stored in the memory 1102 to implement any one of the methods for determining regional habitat connectivity in the above embodiments.

[0159] In one example, the apparatus for determining regional habitat connectivity may further include a communication interface 1103 and a bus 1104. The processor 1101, the memory 1102, and the communication interface 1103 are connected via the bus 1104 and communicate with each other.

[0160] The communication interface 1103 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0161] Bus 1104 includes hardware, software or both, and the components of the determining device of regional habitat connectivity are coupled to each other. For example, but not limitation, the bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 1104 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0162] In addition, in combination with the method for determining regional habitat connectivity in the above embodiments, the present application embodiment may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any method for determining regional habitat connectivity in the above embodiments is implemented.

[0163] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements any one of the methods for determining regional habitat connectivity in the above embodiments.

[0164] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0165] The functional blocks shown in the block diagram above can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0166] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0167] Aspects of the present disclosure are described above with reference to the flowcharts and / or block diagrams of the methods, devices, equipment, media and products for determining regional habitat connectivity according to embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the functions / actions specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0168] The above contents are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application.

Claims

1. A method for determining regional habitat connectivity, characterized in that: include: Within a preset distance range, taking a plurality of first distance values ​​at preset intervals; Using each of the first distance values ​​as a reference habitat connectivity threshold for birds in the target area, and determining a corresponding target index respectively; the target index includes a connectivity index and / or an equivalent connectivity index; Determine a first logarithmic value corresponding to each of the first distance values ​​and a second logarithmic value corresponding to each of the target indexes; Establishing a fitting curve of a power function of a preset order based on the corresponding relationship between the first pair of values ​​and the second pair of values; Obtaining the first distance value corresponding to the inflection point of the fitting curve; Determine an actual habitat connectivity threshold of the target birds in the target area based on the maximum migration distance of the target birds and the first distance value corresponding to the inflection point; The actual habitat connectivity threshold falls within the preset distance range; Based on the actual habitat connectivity threshold, the habitat connectivity of the target area is determined.

2. The method for determining regional habitat connectivity according to claim 1, characterized in that: Before taking a plurality of first distance values ​​at preset intervals within the preset distance range, the method further includes: Determining an initial reference habitat connectivity threshold that makes the number of components corresponding to the target area greater than 1; Increasing the initial reference habitat connectivity threshold with a preset step size until the corresponding number of components becomes 1, so as to obtain a maximum reference habitat connectivity threshold; The preset distance range is determined based on the maximum reference habitat connectivity threshold.

3. The method for determining regional habitat connectivity according to claim 2, characterized in that: After determining the preset distance range based on the maximum reference habitat connectivity threshold, and before taking a plurality of first distance values ​​at preset intervals within the preset distance range, the method further includes: Dividing the preset distance range into a plurality of sub-ranges; Determine the corresponding preset interval for each of the sub-intervals; the preset interval is positively correlated with the distance between the sub-intervals; The step of taking a plurality of first distance values ​​at preset intervals within a preset distance range comprises: For different sub-intervals, the first distance value is taken at the corresponding preset intervals.

4. The method for determining regional habitat connectivity according to claim 1, characterized in that: The step of establishing a fitting curve of a power function of a preset order based on the corresponding relationship between the first logarithmic value and the second logarithmic value includes: Establishing the fitting curves of the cubic function and the quartic function based on the corresponding relationship between the first logarithmic value and the second logarithmic value; Correspondingly, the obtaining the first distance value corresponding to the inflection point of the fitting curve includes: The first distance value corresponding to each inflection point of each fitting curve is obtained respectively.

5. The method for determining regional habitat connectivity according to claim 1, characterized in that: The determining, based on the maximum migration distance of the target birds and the first distance value corresponding to the inflection point, an actual habitat connectivity threshold of the target birds in the target area comprises: From the first distance values ​​corresponding to the inflection points, a second distance value that satisfies a similarity condition with the maximum migration distance of the target bird is selected; Based on the second distance value, the actual habitat connectivity threshold is determined.

6. The method for determining regional habitat connectivity according to any one of claims 1 to 5, characterized in that: The determining the habitat connectivity of the target area based on the actual habitat connectivity threshold comprises: In the target area, determining each pair of habitat patches whose distance is less than the actual habitat connectivity threshold, and obtaining a plurality of habitat patch groups; The habitat connectivity of the target area is determined based on the number of links of the shortest paths between two habitat patches in each habitat patch group, the area of ​​each habitat patch in the target area, and the area of ​​the target area.

7. The method for determining regional habitat connectivity according to claim 6, characterized in that: Before using each of the first distance values ​​as a reference habitat connectivity threshold for birds in the target area to determine the corresponding target index respectively, the method further includes: Acquire a remote sensing image dataset of the target area within a target time period; The seasonal water bodies in the remote sensing image data set are determined as the habitat patches in the target area.

8. The method for determining regional habitat connectivity according to claim 7, characterized in that: The remote sensing image data set includes the seasonal water body and the permanent water body; Before determining the seasonal water bodies as the habitat patches in the target area, the method further comprises: Acquire surface water data of the target area within the target time period; Obtaining a first coincidence rate between the permanent water body and the rivers, lakes and reservoirs in the surface water body data, and a second coincidence rate between the seasonal water body and the floodplain, beach and swamp in the surface water body data; When both the first overlap rate and the second overlap rate meet the overlap requirement, the remote sensing image dataset is determined to be valid, and the step of determining the seasonal water bodies in the remote sensing image dataset as the habitat patches in the target area is entered.

9. A device for determining regional habitat connectivity, characterized in that: The device comprises: A first acquisition module, used to obtain a plurality of first distance values ​​at preset intervals within a preset distance range; A first determination module is used to use each of the first distance values ​​as a reference habitat connectivity threshold for birds in a target area, and respectively determine a corresponding target index; the target index includes a connectivity index and / or an equivalent connectivity index; A second determination module, used to determine a first logarithmic value corresponding to each of the first distance values ​​and a second logarithmic value corresponding to each of the target indexes; An establishing module, used for establishing a fitting curve of a power function of a preset order based on the corresponding relationship between the first pair of values ​​and the second pair of values; A second acquisition module, used to acquire the first distance value corresponding to the inflection point of the fitting curve; A third determination module is used to determine an actual habitat connectivity threshold of the target birds in the target area based on the maximum migration distance of the target birds and the first distance value corresponding to the inflection point; the actual habitat connectivity threshold belongs to the preset distance range; The fourth determination module is used to determine the habitat connectivity of the target area based on the actual habitat connectivity threshold.

10. A device for determining regional habitat connectivity, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the method for determining regional habitat connectivity according to any one of claims 1 to 8 is implemented.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for determining regional habitat connectivity according to any one of claims 1 to 8 is implemented.

12. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for determining regional habitat connectivity as described in any one of claims 1 to 8.

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