Method, device, equipment, medium and product for determining regional habitat connectivity

Abstract

The application discloses a method, device, equipment, medium and product for determining regional habitat connectivity, and is applied to the field of ecology. The method first takes a plurality of first distance values as reference habitat connectivity thresholds of birds in a target region, and determines corresponding target indexes. Then, logarithmic values are taken, and a fitting curve is established according to the corresponding relationship between the first logarithmic values and the second logarithmic values, so as to obtain a first distance value corresponding to an inflection point of the fitting curve. Further, 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, and the habitat connectivity of the target region can be determined based on the actual habitat connectivity threshold. The application can accurately find out the distance mutation point causing the connectivity mutation by the fitting curve and the inflection point, and further determine the accurate actual habitat connectivity threshold in combination with the maximum migration distance of the target bird, so that the accurate connectivity is obtained.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of ecology, and particularly relates to a method and device for determining regional habitat connectivity, a medium and product. BACKGROUND

[0002] For wading birds that live in marsh wetlands and floodplains and rely on water for survival, the habitat connectivity in the region is crucial, so the habitat connectivity of the region needs to be calculated. For a region, 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 have connectivity.

[0003] In the process of determining the habitat connectivity of the bird living area, the corresponding habitat connectivity threshold needs to be determined. At present, for the habitat connectivity threshold of birds, the staff generally estimates a habitat connectivity threshold by 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

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

[0005] In one aspect, the embodiments of the application provide a method for determining regional habitat connectivity, comprising:

[0006] Within a preset distance range, a plurality of first distance values are taken at a preset interval;

[0007] Each of the first distance values is taken as a reference habitat connectivity threshold of birds in a target region, and a corresponding target index is determined; the target index includes a connectivity index and / or an equivalent connectivity index;

[0008] A first logarithmic value corresponding to each of the first distance values and a second logarithmic value corresponding to each of the target indexes are determined;

[0009] A fitting curve of a preset number of power functions is established according to the corresponding relationship between the first logarithmic values and the second logarithmic values;

[0010] The first distance value corresponding to the inflection point of the fitting curve is obtained;

[0011] Based on the maximum migration distance of the target bird and the first distance value corresponding to the inflection point, an actual habitat connectivity threshold of the target bird in the target region is determined; 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 region is determined.

[0013] In another aspect, before the taking a plurality of first distance values at preset intervals within a preset distance range, the method further comprises:

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

[0015] increasing the initial reference habitat connectivity threshold value by a preset step size until the corresponding number of components becomes 1 to obtain a maximum reference habitat connectivity threshold value;

[0016] determining the preset distance range based on the maximum reference habitat connectivity threshold value.

[0017] In another aspect, after the determining the preset distance range based on the maximum reference habitat connectivity threshold value, and before the taking a plurality of first distance values at preset intervals within a preset distance range, the method further comprises:

[0018] dividing the preset distance range into a plurality of subintervals;

[0019] determining a corresponding preset interval for each of the subintervals; the preset interval is positively correlated with the distance size of the subinterval;

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

[0021] for different subintervals, taking the first distance value at a corresponding preset interval.

[0022] In another aspect, the establishing a fitting curve of a preset order power function based on the corresponding relationship between the first logarithmic value and the second logarithmic value comprises:

[0023] establishing the fitting curve of a cubic power function and a quartic power 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 comprises:

[0025] respectively obtaining the first distance value corresponding to each inflection point of each fitting curve.

[0026] In another aspect, the determining an actual habitat connectivity threshold value of a target bird in the target area based on the maximum migration distance of the target bird and the first distance value corresponding to the inflection point comprises:

[0027] selecting a second distance value from the first distance values corresponding to the inflection points that meets a similarity condition with the maximum migration distance of the target bird;

[0028] determine the actual habitat connectivity threshold value based on the second distance value.

[0029] In another aspect, the determining the habitat connectivity of the target region based on the actual habitat connectivity threshold value comprises:

[0030] determining, in the target region, a plurality of habitat patch groups from two habitat patches each having a distance less than the actual habitat connectivity threshold value;

[0031] determining the habitat connectivity of the target region based on a number of links of a shortest path between two habitat patches in each of the habitat patch groups, an area of each habitat patch in the target region, and an area of the target region.

[0032] In another aspect, before the determining the corresponding target index based on each of the first distance value as a reference habitat connectivity threshold value of birds in the target region, the method further comprises:

[0033] obtaining a remote sensing image dataset of the target region in a target time period;

[0034] determining, as each of the habitat patches in the target region, a seasonal water body in the remote sensing image dataset.

[0035] In another aspect, the remote sensing image dataset comprises the seasonal water body and a permanent water body.

[0036] Before the determining, as each of the habitat patches in the target region, the seasonal water body, the method further comprises:

[0037] obtaining surface water body data of the target region in the target time period;

[0038] obtaining a first coincidence rate of the permanent water body and a river, a lake, and a reservoir in the surface water body data, and a second coincidence rate of the seasonal water body and a floodplain, a beach, and a marsh in the surface water body data;

[0039] In a case where the first coincidence rate and the second coincidence rate both satisfy a coincidence requirement, determining that the remote sensing image dataset is valid, and entering the step of determining, as each of the habitat patches in the target region, the seasonal water body in the remote sensing image dataset.

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

[0041] a first obtaining module configured to obtain a plurality of first distance values at a preset interval within a preset distance range;

[0042] The first determining module is configured to determine a corresponding target index by taking each of the first distance values as a reference habitat connectivity threshold of the bird in the target region; the target index includes a connectivity index and / or an equivalent connectivity index.

[0043] The second determining module is configured 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] The establishing module is configured to establish a fitting curve of a preset power function according to a corresponding relationship between the first logarithmic values and the second logarithmic values.

[0045] The second obtaining module is configured to obtain the first distance value corresponding to an inflection point of the fitting curve.

[0046] The third determining module is configured to determine an actual habitat connectivity threshold of the target bird in the target region based on a maximum migration distance of the target bird and the first distance value corresponding to the inflection point; the actual habitat connectivity threshold belongs to the preset distance range.

[0047] The fourth determining module is configured to determine the habitat connectivity of the target region based on the actual habitat connectivity threshold.

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

[0049] The processor implements the method for determining habitat connectivity of a region as described above when executing the computer program instructions.

[0050] In another aspect, an embodiment of the present application provides a computer readable storage medium, the computer readable storage medium storing computer program instructions, the computer program instructions being executed by a processor to implement the method for determining habitat connectivity of a region as described above.

[0051] In another aspect, an embodiment of the present application provides a computer program product, instructions in the computer program product being executed by a processor of an electronic device to cause the electronic device to perform the method for determining habitat connectivity of a region as described above.

[0052] The method for determining regional habitat connectivity provided in the embodiment of the present application first takes a plurality of first distance values as reference habitat connectivity thresholds of birds in a target region, and determines corresponding target indexes. Then, logarithmic values are taken, and a fitting curve is established according to the corresponding relationship between the first logarithmic values and the second logarithmic values, so as to obtain a first distance value corresponding to an inflection point of the fitting curve. Further, 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, and the habitat connectivity of the target region can be determined based on the actual habitat connectivity threshold. The embodiment of the present application can accurately find out the distance mutation point causing the connectivity mutation by means of fitting curve and taking the inflection point, and further determine the accurate actual habitat connectivity threshold in combination with the maximum migration distance of the target bird. It can be seen that the present scheme can accurately determine the actual habitat connectivity threshold of the target region, so as to obtain the accurate connectivity. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced below. Those skilled in the art can also obtain other drawings according to these drawings without creating any creative labor.

[0054] Figure 1 A flowchart of a method for determining regional habitat connectivity provided in an embodiment of the present application is shown;

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

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

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

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

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

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

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

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

[0063] Figure 10 A structure schematic diagram of a regional habitat connectivity determination device provided by an embodiment of the present application is shown;

[0064] Figure 11 A hardware structure schematic diagram of a regional habitat connectivity determination device provided by 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 with reference to the accompanying drawings and specific embodiments, so that the purposes, technical solutions and advantages of the present application are more clearly understood. It should be understood that the specific embodiments described herein are only intended to explain the present application, but not to limit the present application. The present application can be implemented without some of these specific details by those skilled in the art. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0066] It should be noted that, in this paper, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the elements defined by the statement "include" do 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 scheme and calculate the accurate habitat connectivity in the bird survival area, the present application provides a regional habitat connectivity determination method, device, equipment, medium and product. First, the regional habitat connectivity determination method provided by the present application is introduced. Figure 1 A flowchart of a regional habitat connectivity determination method provided by an embodiment of the present application is shown. As shown in the figure, the method includes the following steps S101-S107: Figure 1 ​

[0068] S101: Obtain a plurality of first distance values at a preset interval within a preset distance range.

[0069] The idea of the scheme is to find the distance mutation point causing the connectivity mutation (i.e. habitat connectivity threshold) by fitting a curve and taking the inflection point. First, before curve fitting, the preset distance range of the habitat connectivity threshold in the target area needs to be determined. The specific size of the preset distance range is not limited and can be set according to the requirements, which needs to include all possible values of the habitat connectivity threshold in the target area.

[0070] Secondly, in order to fit the curve, a plurality of sample points (first distance values) need to be taken. 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 too many first distance values and increase the calculation pressure.

[0071] S102: Take each first distance value as a reference habitat connectivity threshold of birds in the target area, and determine the corresponding target index.

[0072] Here, the target index includes the connectivity index and / or the equivalent connectivity index, which is selected according to the requirements. After obtaining a plurality of first distance values, each first distance value is taken as a reference habitat connectivity threshold of 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 the first logarithmic value corresponding to each first distance value and the second logarithmic value corresponding to each target index.

[0074] S104: Establish a fitting curve of a preset degree power function according to the corresponding relationship between the first logarithmic value and the second logarithmic value.

[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 calculated first. Then, the first logarithmic value is taken as the independent variable and the second logarithmic value is taken as the dependent variable to establish a fitting curve of a preset degree power function.

[0076] Here, the preset degree is set according to the actual requirements, and one or more can be set. For example, a cubic power function can be set, 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 degrees are set, the fitting curves of the corresponding degree power functions need to be fitted respectively. For example, the fitting curves of the cubic power function and the quartic power function can be fitted simultaneously.

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

[0078] The habitat connectivity threshold of the target bird in the target area is the distance mutation point causing the connectivity mutation, which is usually the inflection point in the fitting curve, so it is necessary to obtain the first distance value corresponding to the inflection point of the fitting curve.

[0079] The fitting curve obtained in the foregoing steps can be multiple, for example, the connectivity index and the equivalent connectivity index can correspond to a fitting curve respectively, and different order power functions also correspond to a fitting curve respectively. In addition, there can be multiple inflection points in each fitting curve, for example, there are two inflection points in the fitting curve corresponding to the fourth order power function. In actual application, the first distance value corresponding to each inflection point of each fitting curve needs to be obtained.

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

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

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

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

[0084] The specific range of the target area and the specific species of the target bird mentioned above are determined according to actual conditions. After obtaining the actual habitat connectivity threshold of the target bird in the target area, the habitat connectivity of the target area can be determined through 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 component number NC.

[0086] The connectivity index measures the size of connectivity in a region, and the value ranges from 0 to 1, which reflects the degree of connectivity between the habitat patches in the target region. The greater the value, the greater the connectivity of the region. The patch importance index measures the size of the impact on the connectivity index by removing a certain patch in the landscape, which reflects the impact on the overall connectivity if a single patch is removed. The equivalent connectivity index is the arithmetic square root 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 more compact the patches in the landscape, the fewer the number of components.

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

[0088]

[0089] In formulas (1) to (3), n is the number of patches; a i and a j are the areas of patches i and j, respectively; A L is the area of the study area; nl ij is the number of links of the shortest path from patch i to patch j; IIC remove represents the overall index of the remaining patches after the patch is 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] The method for determining the regional habitat connectivity of the embodiment of the application first takes a plurality of first distance values as the reference habitat connectivity threshold of the target bird in the target region, and determines the corresponding target index. Then take the logarithm value, and establish a fitting curve based on the corresponding relationship between the first logarithm value and the second logarithm value, to obtain the first distance value corresponding to the inflection point of the fitting curve. Further, 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, and the habitat connectivity of the target region can be determined based on the actual habitat connectivity threshold. The embodiment of the application can accurately find the distance mutation point causing the connectivity mutation by fitting the curve and taking the inflection point, and further determine the accurate actual habitat connectivity threshold in combination with the maximum migration distance of the target bird. It can be seen that the actual habitat connectivity threshold of the target region can be accurately determined by the scheme, so as to obtain accurate connectivity.

[0091] In a specific implementation, before determining the first distance value, a preset distance range needs to be determined first. Therefore, before taking the plurality of first distance values at the preset intervals within the preset distance range, the preset distance range is determined by the following steps: first, determining an initial reference habitat connectivity threshold value corresponding to the component number of the target region being greater than 1; then increasing the initial reference habitat connectivity threshold value by a preset step size until the corresponding component number becomes 1 to obtain a maximum reference habitat connectivity threshold value; and finally, determining the preset distance range based on the maximum reference habitat connectivity threshold value.

[0092] For example, starting from 100 m, increasing by 100 m as a step size, and calculating the corresponding component number NC, when the value of the component number drops to 1, the corresponding distance is the maximum reference habitat connectivity threshold value Dmax.

[0093] The scheme provided by the embodiments of the present application can determine the maximum reference habitat connectivity threshold value by calculating the corresponding component number, 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 value needs to be within the preset distance range, ensuring that the determined actual habitat connectivity threshold value also conforms to the actual situation.

[0094] When selecting the first distance value, it is selected from the preset distance range at preset intervals. Therefore, after determining the preset distance range based on the maximum reference habitat connectivity threshold value and before taking the plurality of first distance values at the preset intervals within the preset distance range, the preset interval needs to be determined.

[0095] The embodiments of the present application provide a specific preset interval determination scheme, which first divides the preset distance range into a plurality of subintervals, then determines the corresponding preset interval for each subinterval, and sets the distance between the preset interval and the subinterval to be positively correlated. Correspondingly, when taking the first distance value, the first distance value is taken at the corresponding preset interval for different subintervals.

[0096] Two schemes are provided here. Scheme one: within 10 to 100 m, the preset interval is set to 10 m. Within 100 to 1000 m, the preset interval is 100 m. Above 1000 m, the preset interval is 1000 m. Scheme two: within 10 to 100 m, 10 m, 50 m and 100 m are taken respectively, while within 100-1000 m, the preset interval is 100 m, and above 1000 m, the preset interval is 1000 m.

[0097] In the embodiments, the preset distance range is divided into a plurality of subintervals, and the distance between the preset interval and the subinterval is set to be positively correlated. Compared with the subintervals of a large distance range, more first distance values can be obtained in the subintervals of a small distance range, thereby ensuring the accuracy of the fitted curve and avoiding excessive calculation pressure caused by obtaining too many first distance values.

[0098] The above embodiments mention that the value of the preset number of times is determined according to actual needs, and in actual application, the cubic function and the quartic function can generally meet the needs. Therefore, the fitting curves of the cubic function and the quartic function are established according to the corresponding relationship between the first logarithmic values and the second logarithmic values, and then the first distance values corresponding to each inflection point of each fitting curve are obtained.

[0099] The embodiments of the present application can efficiently determine the inflection points by establishing the fitting curves of the cubic function and the quartic function, the calculation process is simpler compared to higher power functions, and the obtained inflection points can also meet the needs.

[0100] In actual application, it is not limited 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 similar to the maximum migration distance of the target bird, a second distance value that meets a similarity condition with the maximum migration distance of the target bird can be selected from the first distance values corresponding to the inflection points, and then the actual habitat connectivity threshold is determined based on the second distance value. The similarity condition is set according to actual conditions.

[0101] In actual application, the cubic function is preferred when fitting the curve, and the inflection points of each curve are obtained according to the curve fitting result. Then the average value of the distances corresponding to two curve inflection points can be taken as the threshold distance. It should be noted that when selecting the threshold distance, it needs to 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 function does not meet the above requirements, the quartic function fitting can be performed. At this time, each curve has two inflection points, and the average value of the distances corresponding to the first and second inflection points of the two curves is obtained 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 not exceeding the bird flight distance threshold 40 kilometers.

[0102] The following two specific examples are used to illustrate the habitat connectivity threshold determination scheme.

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

[0104] Figure 2 The cubic function fitting curve of the distance and connectivity index corresponding to the first interval division scheme is shown. As shown in FIG. 2, the first distance value is taken at intervals of 10m from 10 to 100m, 100m from 100 to 1000m, 1000m from 1000m, and the IIC value and EC(IIC) value corresponding to each distance are calculated. Figure 2ln(IIC) and ln(distance) fitting curve, the inflection point of the fitting curve is found, and the distance corresponding to the inflection point is 58.3 m, 8380.8 m, 57.8 m, and 8048.2 m. Among them, the two inflection points corresponding to the distances of 58.3 m and 57.8 m are averaged to 58.05 m. The two inflection points corresponding to the distances of 8380.8 m and 8048.2 m are averaged to 8214.5 m. 8214.5 m is close to the distance of one-time diffusion of migratory birds (i.e. the maximum migration distance of target birds, different migratory birds are about 10 to 40 kilometers), so the threshold distance is set to 8.2 km. Figure 3 The fourth power function fitting curve of the distance and the connectivity index corresponding to the first interval division scheme is shown. As shown in Figure 4 The fourth power function curve is used to fit the scatter points, and the curve equation has two inflection points, the inflection point coordinates are 4.0662, 9.0337, and the corresponding distances are 58.3 m and 8380.8 m.

[0105] Figure 4 The third power function fitting curve of the distance and the equivalent connectivity index corresponding to the first interval division scheme is shown. As shown in Figure 4 ln(IIC) and ln(distance) fitting curve, the inflection point of the fitting curve is found, and the distance corresponding to the inflection point is 58.3 m, 8380.8 m, 57.8 m, and 8048.2 m. Among them, the two inflection points corresponding to the distances of 58.3 m and 57.8 m are averaged to 58.05 m. The two inflection points corresponding to the distances of 8380.8 m and 8048.2 m are averaged to 8214.5 m. 8214.5 m is close to the distance of one-time diffusion of migratory birds (i.e. the maximum migration distance of target birds, different migratory birds are about 10 to 40 kilometers), so the threshold distance is set to 8.2 km. 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. As shown in Figure 5 The fourth power function curve is used to fit the scatter points, and the curve equation has two inflection points, the inflection point coordinates are 4.0567, 8.9932, and the corresponding distances are 57.8 m and 8048.2 m.

[0106] ln(IIC), ln(EC(IIC)), and ln(distance) fitting curve, the inflection point of the fitting curve is found, and the distance corresponding to the inflection point is 58.3 m, 8380.8 m, 57.8 m, and 8048.2 m. Among them, the two inflection points corresponding to the distances of 58.3 m and 57.8 m are averaged to 58.05 m. The two inflection points corresponding to the distances of 8380.8 m and 8048.2 m are averaged to 8214.5 m. 8214.5 m is close to the distance of one-time diffusion of migratory birds (i.e. the maximum migration distance of target birds, different migratory birds are about 10 to 40 kilometers), so the threshold distance is set to 8.2 km.

[0107] In Example Two, 10-100 m takes 10 m, 50 m, and 100 m, 100-1000 m takes every 100 m, and 1000 m above takes every 1000 m, and takes the first distance value. And calculate the IIC value and EC(IIC) value corresponding to each distance.

[0108] Figure 6 The third power function fitting curve of the distance and the connectivity index corresponding to the second interval division scheme is shown. As shown in Figure 6ln(IIC) and ln(distance) fitting curves, the inflection points of the fitting curves are found, and the distances corresponding to the inflection points are 62.9 m, 8080.4 m, 74.8 m, and 4020.6 m. Among them, the two inflection points corresponding to the distances of 62.9 m and 74.8 m are averaged to 68.85 m. The two inflection points corresponding to the distances of 8080.4 m and 4020.6 m are averaged to 6050.5 m. 6050.5 m is relatively close to the distance threshold (10-40 kilometers) of the migratory birds, so the threshold distance is set to 6 km. Figure 7 The fourth power function fitting curve of the distance and the connectivity index corresponding to the second interval division scheme is shown. The scatter points are fitted with a fourth power function curve, and the curve equation has two inflection points, with inflection point coordinates 4.1427, 8.9972, corresponding to distances 62.9 m and 8080.4 m.

[0109] Figure 8 The third power function fitting curve of the distance and the equivalent connectivity index corresponding to the second interval division scheme is shown. As shown in Figure 8 The scatter points are fitted with a third power function curve, and the curve equation has an inflection point, with an inflection point coordinate of 11.3809, corresponding to a distance of 87631 m. Figure 9 The fourth power function fitting curve of the distance and the equivalent connectivity index corresponding to the second interval division scheme is shown. As shown in Figure 9 The scatter points are fitted with a fourth power function curve, and the curve equation has two inflection points, with inflection point coordinates 4.316, 8.2992, corresponding to distances 74.8 m and 4020.6 m.

[0110] ln(IIC), ln(EC(IIC)), and ln(distance) fitting curves, the inflection points of the fitting curves are found, and the distances corresponding to the inflection points are 62.9 m, 8080.4 m, 74.8 m, and 4020.6 m. Among them, the two inflection points corresponding to the distances of 62.9 m and 74.8 m are averaged to 68.85 m. The two inflection points corresponding to the distances of 8080.4 m and 4020.6 m are averaged to 6050.5 m. 6050.5 m is relatively close to the distance threshold (10-40 kilometers) of the migratory birds, so the threshold distance is set to 6 km.

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

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

[0113] The embodiment of the present application provides a specific determination method of the actual habitat connectivity threshold value, the second distance value close to the maximum migration distance of the target bird is selected, and then the actual habitat connectivity threshold value is determined based on the second distance value, so that the accuracy of the actual habitat connectivity threshold value is ensured.

[0114] Based on the actual habitat connectivity threshold value, the habitat connectivity of the target region can be determined by determining two habitat patches (i.e., patch i and patch j in the above) in the target region, which are less than the actual habitat connectivity threshold value, to obtain a plurality of habitat patch groups. Then, based on the number of links of the shortest path between the two habitat patches in each habitat patch group, the area of each habitat patch in the target region, and the area of the target region, the habitat connectivity of the target region is determined.

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

[0116] In actual application, when calculating each index for measuring connectivity, the data of the target region needs to be obtained, and the habitat patches of the target region need to be determined. Therefore, before each first distance value is taken as the reference habitat connectivity threshold value of the bird in the target region and the corresponding target index is determined, the remote sensing image dataset of the target region in the target time period can be obtained; then the seasonal water in the remote sensing image dataset is determined as each habitat patch in the target region.

[0117] The embodiment of the present application directly takes the seasonal water in the remote sensing image dataset as the habitat patch of the target region, which is efficient and consistent with the actual situation.

[0118] Before the seasonal water is determined as each habitat patch in the target region, the reliability of the remote sensing image dataset can be verified, and therefore the embodiment provides a verification scheme.

[0119] The surface water data of the target region in the target time period is obtained, then the first coincidence rate of the permanent water and the river, lake and reservoir in the surface water data, and the second coincidence rate of the seasonal water and the floodplain, beach and marsh in the surface water data are obtained. In the case that the first coincidence rate and the second coincidence rate meet the coincidence requirement, it is determined that the remote sensing image dataset is valid, and the step of determining the seasonal water in the remote sensing image dataset as each habitat patch in the target region is entered.

[0120] The remote sensing image dataset includes seasonal water and permanent water; the published global 30m resolution surface water remote sensing image dataset can be directly downloaded, and the seasonal water and permanent water with categories 2 and 3 are extracted respectively for calculation and comparison.

[0121] Load remote sensing images of wet years and dry years in the past ten years, in the basin range, adopt the combination of automatic extraction and manual visual interpretation, compare the coincidence rate of rivers, lakes, reservoirs, floodplains, beaches and marshes in the remote sensing image data set and the surface water body data of the corresponding year, and correct and verify the data. When the coincidence rate is greater than 90%, it is indicated that the data can represent the actual situation.

[0122] Birds grow in the environment of shallow swamp wetlands, and the bird habitat is dynamically changing in wet and dry years, and the seasonal water body of the surface water body data meets the characteristics of the dynamic change of the bird habitat every year, so the seasonal water body is regarded as the habitat patch of the bird.

[0123] Before taking the seasonal water body as the habitat patch of the target area, the application embodiment performs a verification on the surface water body data to ensure the reliability of the data.

[0124] To solve the above technical problems, the application embodiment also provides a region habitat connectivity determination device, Figure 10 The structure schematic diagram of the region habitat connectivity determination device provided by the application embodiment is shown, as Figure 10 The device includes the following modules:

[0125] The first acquisition module 1001 is configured to take a plurality of first distance values at a preset interval within a preset distance range.

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

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

[0128] The establishment module 1004 is configured to establish a fitting curve of a preset number of power functions according to the corresponding relationship between the first logarithmic value and the second logarithmic value.

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

[0130] The third determination module 1006 is configured to determine an actual habitat connectivity threshold of a target bird in the target area based on the maximum migration distance of the target bird 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 configured to determine the habitat connectivity of the target area based on the actual habitat connectivity threshold.

[0132] In some embodiments, the determining device of the regional habitat connectivity further comprises a fifth determining module configured to determine an initial reference habitat connectivity threshold value, which makes the number of components corresponding to the target region greater than 1, before the plurality of first distance values are taken at the preset intervals within the preset distance range;

[0133] a growing module configured to grow the initial reference habitat connectivity threshold value by a preset step size until the number of corresponding components becomes 1 to obtain a maximum reference habitat connectivity threshold value;

[0134] The fifth determining module is further configured to determine the preset distance range based on the maximum reference habitat connectivity threshold value.

[0135] In some embodiments, the determining device of the regional habitat connectivity further comprises a dividing module configured to divide the preset distance range into a plurality of subintervals after determining the preset distance range based on the maximum reference habitat connectivity threshold value and before the plurality of first distance values are taken at the preset intervals within the preset distance range;

[0136] a sixth determining module configured to determine a corresponding preset interval for each subinterval; the preset interval is positively correlated with the distance of the subinterval;

[0137] a third obtaining module configured to take the first distance value at the corresponding preset interval for different subintervals.

[0138] In some embodiments, the establishing module is specifically configured to:

[0139] establish a fitting curve of a cubic power function and a quartic power function based on the corresponding relationship between the first pair of values and the second pair of values;

[0140] Correspondingly, the second obtaining module is specifically configured to:

[0141] obtain the first distance value corresponding to each inflection point of each fitting curve, respectively.

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

[0143] select a second distance value from the first distance values corresponding to the inflection points, which satisfies a similarity condition with the maximum migration distance of the target bird species;

[0144] determine an actual habitat connectivity threshold value based on the second distance value.

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

[0146] determine a plurality of habitat patch groups by determining two habitat patches in the target region whose distance is less than the actual habitat connectivity threshold value;

[0147] The habitat connectivity of the target area is determined based on the number of links of the shortest paths between the 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 device for determining the regional habitat connectivity further comprises a fourth acquisition module configured to acquire a remote sensing image dataset of the target area in a target time period before the corresponding target indices are determined respectively by taking each first distance value as the reference habitat connectivity threshold of the bird in the target area.

[0149] The seventh determination module is further configured to determine the seasonal water body in the remote sensing image dataset as each habitat patch in the target area.

[0150] In some embodiments, the remote sensing image dataset comprises the seasonal water body and the permanent water body.

[0151] The fourth acquisition module is further configured to acquire surface water body data of the target area in the target time period before the seasonal water body is determined as each habitat patch in the target area, and acquire a first coincidence rate of the permanent water body and the river, lake and reservoir in the surface water body data, and a second coincidence rate of the seasonal water body and the floodplain, beach and marsh in the surface water body data.

[0152] The device for determining the regional habitat connectivity further comprises a determination module configured to determine that the remote sensing image dataset is valid and enter the step of determining the seasonal water body in the remote sensing image dataset as each habitat patch in the target area when the first coincidence rate and the second coincidence rate both meet the coincidence requirement.

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

[0154] Figure 11 A hardware structure schematic diagram of the device for determining the regional habitat connectivity provided in the embodiments of the present application is shown. Figure 11 As shown in the figure, the device for determining the regional habitat connectivity can comprise a processor 1101 and a memory 1102 storing computer program instructions.

[0155] Specifically, the above-mentioned processor 1101 can comprise a central processing unit (CPU), or an application specific integrated circuit (ASIC), or can be configured as one or more integrated circuits implementing the embodiments of the present application.

[0156] The memory 1102 can include mass storage for data or instructions. As an example and not by way of limitation, the memory 1102 can include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disc (e.g., a compact disc (CD) or a digital versatile disc (DVD)), a solid-state drive (SSD), a USB drive, or a combination of two or more of these. Where appropriate, the memory 1102 can include removable or non-removable (or fixed) media, where appropriate. The memory 1102 can be internal or external to the integrated gateway disaster recovery device. In particular embodiments, the memory 1102 is non-volatile, solid-state memory.

[0157] The memory 1102 can include read-only memory (ROM), random-access memory (RAM), a disk storage medium device, an optical storage medium device, a flash memory device, electrical, optical, or other physical / tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software that, when executed (by one or more processors), is operable to

[0158] The processor 1101 implements the determination method of the regional habitat connectivity in any of the above embodiments by reading and executing computer program instructions stored in the memory 1102.

[0159] In one example, the determination device of the regional habitat connectivity can further include a communication interface 1103 and a bus 1104. The processor 1101, the memory 1102, and the communication interface 1103 are connected through the bus 1104 and complete communication with each other.

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

[0161] Bus 1104 includes hardware, software, or both, that couples components of a device that defines regional habitat connectivity together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 1104 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0162] Furthermore, in conjunction with the method for determining regional habitat connectivity in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the methods for determining regional habitat connectivity in the above embodiments.

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

[0164] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0165] The functional blocks shown in the structural diagram above can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on 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, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0166] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. 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 embodiments, or in a different order, or several steps can be performed simultaneously.

[0167] The foregoing flowcharts and / or block diagrams describing methods, apparatuses, devices, media, and products for determining regional habitat connectivity according to embodiments of this disclosure have described various aspects of the present disclosure. It should be understood that each block in the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, 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 apparatus to create a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowcharts and / or block diagrams. 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 is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0168] The above is merely a specific implementation of the present application. As can be clearly understood by a person skilled in the art from the above description, for the convenience and brevity of description, the specific working process of the system, module and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described herein again. It should be understood that the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed in the present application, and these modifications or replacements should be covered within 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, multiple first distance values ​​are taken at preset intervals; Each of the first distance values ​​is used as a reference habitat connectivity threshold for birds in the target area, and the corresponding target index is determined accordingly; the target index includes a connectivity index and / or an equivalent connectivity index; Determine the first logarithmic value corresponding to each of the first distance values ​​and the second logarithmic value corresponding to each of the target indices; Based on the correspondence between the first logarithmic value and the second logarithmic value, a fitting curve for a preset power function is established; Obtain the first distance value corresponding to the inflection point of the fitted curve; 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 of the target birds in the target area is determined; 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; The step of 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: From the first distance values ​​corresponding to the inflection point, select the second distance value that satisfies the similarity condition with the maximum migration distance of the target bird. Based on the second distance value, the actual habitat connectivity threshold is determined.

2. The method for determining regional habitat connectivity according to claim 1, characterized in that, Before taking multiple first distance values ​​at preset intervals within a preset distance range, the method further includes: Determine an initial reference habitat connectivity threshold that makes the number of components corresponding to the target region greater than 1; The initial reference habitat connectivity threshold is increased by a preset step size until the corresponding number of components becomes 1, so as to obtain the 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 multiple first distance values ​​at preset intervals within the preset distance range, the method further includes: The preset distance range is divided into multiple sub-intervals; A corresponding preset interval is determined for each of the sub-intervals; the preset interval is positively correlated with the distance between the sub-intervals. The step of taking multiple first distance values ​​at preset intervals within a preset distance range includes: For different sub-intervals, the first distance value is taken at the corresponding preset interval.

4. The method for determining regional habitat connectivity according to claim 1, characterized in that, The step of establishing a fitting curve for a preset power function based on the correspondence between the first logarithmic value and the second logarithmic value includes: Based on the correspondence between the first logarithmic value and the second logarithmic value, the fitting curves of the cubic power function and the fourth power function are established; Correspondingly, obtaining the first distance value corresponding to the inflection point of the fitted curve includes: Obtain the first distance value corresponding to each inflection point of each of the fitted curves.

5. The method for determining regional habitat connectivity according to any one of claims 1 to 4, characterized in that, Determining the habitat connectivity of the target area based on the actual habitat connectivity threshold includes: In the target area, two pairs of habitat patches with a distance less than the actual habitat connectivity threshold are identified to obtain multiple habitat patch groups; The habitat connectivity of the target region is determined based on the number of shortest path links between two habitat patches in each habitat patch group, the area of ​​each habitat patch in the target region, and the area of ​​the target region.

6. The method for determining regional habitat connectivity according to claim 5, characterized in that, Before determining the corresponding target index by using each of the first distance values ​​as a reference habitat connectivity threshold for birds in the target area, the method further includes: Obtain the remote sensing image dataset of the target area within the target time period; The seasonal water bodies in the remote sensing image dataset are identified as the habitat patches within the target area.

7. The method for determining regional habitat connectivity according to claim 6, characterized in that, The remote sensing image dataset includes both seasonal and permanent water bodies. Before identifying the habitat patches within the target area from the seasonal water body, the method further includes: Obtain surface water data for the target area within the target time period; Obtain the first overlap rate of the permanent water body with the rivers, lakes and reservoirs in the surface water data, and the second overlap rate of the seasonal water body with the floodplains, beaches and marshes in the surface water data; If both the first overlap rate and the second overlap rate meet the overlap rate requirements, the remote sensing image dataset is determined to be valid, and the process proceeds to the step of identifying the seasonal water bodies in the remote sensing image dataset as the habitat patches within the target area.

8. A device for determining regional habitat connectivity, characterized in that, The device includes: The first acquisition module is used to acquire multiple first distance values ​​at preset intervals within a preset distance range; The first determining module is used to use each of the first distance values ​​as a reference habitat connectivity threshold for birds in the target area, and to determine the corresponding target index respectively; the target index includes a connectivity index and / or an equivalent connectivity index; The second determining module is used to determine the first logarithmic value corresponding to each of the first distance values ​​and the second logarithmic value corresponding to each of the target indices; A module is established to establish a fitting curve for a preset power function based on the correspondence between the first logarithmic value and the second logarithmic value. The second acquisition module is used to acquire the first distance value corresponding to the inflection point of the fitted curve; The third determining module 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; The fourth determining module is used to determine the habitat connectivity of the target area based on the actual habitat connectivity threshold. The third determining module includes: The distance selection unit is used to select a second distance value from each of the first distance values ​​corresponding to the inflection point that satisfies the similarity condition with the maximum migration distance of the target bird. A threshold determination unit is used to determine the actual habitat connectivity threshold based on the second distance value.

9. A device for determining regional habitat connectivity, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the method for determining regional habitat connectivity as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the method for determining regional habitat connectivity as described in any one of claims 1 to 7.

11. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device causes the electronic device to perform the method for determining regional habitat connectivity as described in any one of claims 1 to 7.

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