A method for calculating multi-scale land cover change contribution degree and correlation thereof

Abstract

The application provides a method for calculating multi-scale land cover change contribution degree and its correlation, wherein the method for calculating the contribution degree comprises the following steps: taking a national region, a natural regionalization region, a province and a typical urban area as multi-scale division regions; obtaining multiple land cover changes according to land cover categories; calculating population contribution degrees in multiple comparison modes according to population data in the multi-scale division regions; and calculating land cover change contribution degrees in multiple comparison modes according to the area of each land cover change in the multi-scale division regions. The land cover change in the multi-scale division regions and the population factor can be used to calculate the contribution degrees in multiple comparison modes. The multi-scale and quantitative method for calculating the contribution degrees is not easily affected by a few data deviations, the conclusion is closer to the actual situation, and thus the reference demand of the current land cover change on land policy tendency can be met.

Description

Technical Field

[0001] This disclosure generally relates to the technical field of the impact of population factors on land cover change, and specifically to a method for calculating the contribution of land cover change at multiple scales and its correlation. Background Technology

[0002] Land cover change can cause changes in natural ecosystems and the global environment, and is a crucial factor affecting sustainable development. Current research on land cover change mainly focuses on analyzing land cover change patterns at a single scale, using only one of the following: country, province, city, or natural region.

[0003] Existing research on land cover change focuses solely on administrative or natural divisions, neglecting the impact of population factors. Therefore, analyzing land cover change using single-scale data offers limited guidance. Furthermore, single-scale research is more susceptible to biases when data is present, making it prone to deviating from reality. Because it is easily affected by a few data points, it struggles to reflect the relative importance of different natural regions, provinces, and typical cities within a country in various types of land cover change under a multi-scale comparative model, thus hindering its application in land management, policy-making, and ecological protection. Summary of the Invention

[0004] In view of the above-mentioned defects or deficiencies in the existing technology, it is desirable to provide a method for calculating the contribution of land cover change at multiple scales and its correlation.

[0005] This application provides a method for calculating the contribution of land cover change at multiple scales, including:

[0006] Obtain multi-scale regional divisions of the target country; the multi-scale regional divisions, in descending order of scale, include: national regions, natural regional divisions, provinces, and typical urban areas;

[0007] Obtain the land cover category of the target country, and derive various land cover changes based on the land cover category;

[0008] Acquire population data under multi-scale regional divisions; calculate population contribution under various comparison models based on the population data under multi-scale regional divisions.

[0009] The multiple comparison modes include: a comparison mode between a region of arbitrary scale and a larger-scale region of its own.

[0010] Obtain the area of ​​each land cover change under multi-scale regional division; based on the area of ​​each land cover change under multi-scale regional division, calculate the contribution of land cover change under various comparison models.

[0011] According to the technical solution provided in the embodiments of this application, the city with the largest population in each province is taken as the typical city of the province, and the population of the city with the largest population in each province is taken as the population of the typical city.

[0012] According to the technical solution provided in the embodiments of this application, when a province has multiple natural regional divisions, the natural regional division where the typical urban area of ​​the province is located is taken as the natural regional division to which the province belongs.

[0013] According to the technical solution provided in the embodiments of this application, the steps for obtaining the area of ​​each land cover change under multi-scale regional division include:

[0014] Obtain land cover category maps of the target country at two different time points;

[0015] Obtain national regional boundaries, natural regional boundaries, provincial boundaries, and typical urban area boundaries;

[0016] The two land cover category maps were spatially overlaid with national regional boundaries, natural regional boundaries, provincial boundaries, and typical urban area boundaries, and the areas were statistically analyzed to obtain the area of ​​each land cover change under multi-scale regional divisions, including:

[0017] The area of ​​land cover change for each type of land cover change in the country, the area of ​​land cover change for each type of land cover change in each province, the area of ​​land cover change for each type of land cover change in a typical urban area of ​​each province, and the area of ​​land cover change for each type of land cover change in each natural regional division.

[0018] According to the technical solution provided in the embodiments of this application, the contribution of land cover change under various comparison modes is calculated according to formula (I);

[0019] (one);

[0020] Among them, the area contribution rate represents the contribution of the same type of land cover change under multiple comparison models.

[0021] According to the technical solution provided in the embodiments of this application, when calculating the contribution of land cover change in a comparative model with typical urban areas, the ratio of the sum of the land cover change areas of all typical urban areas included in the larger-scale division area compared with typical urban areas to the land cover change area in the larger-scale division area is taken as the corresponding contribution.

[0022] According to the technical solution provided in the embodiments of this application, the population contribution under the multiple comparison modes is calculated according to formula (II);

[0023] (two);

[0024] Among them, population contribution represents the population contribution under multiple comparison models.

[0025] According to the technical solution provided in the embodiments of this application, when calculating the population contribution under the comparison model with typical urban areas, the ratio of the sum of the population of all typical urban areas included in the larger-scale division area compared with typical urban areas to the land cover change area in the larger-scale division area is used as the corresponding contribution.

[0026] This application, in another aspect, provides a method for calculating the correlation between contributions of land cover change at multiple scales, including the method for calculating contributions of land cover change at multiple scales as described above, and further including:

[0027] Based on the population contribution and land cover change contribution under multiple comparison models, calculate the first Pearson correlation coefficient between any two land cover change contributions under multiple comparison models and the second Pearson correlation coefficient between any one land cover change contribution and population contribution under multiple comparison models; thus obtaining the correlation coefficient matrix under multiple comparison models.

[0028] According to the technical solution provided in the embodiments of this application, the steps of obtaining the correlation coefficient matrix under multiple comparison modes by calculating the first Pearson correlation coefficient and the second Pearson correlation coefficient include:

[0029] According to Formula (III), calculate the first Pearson correlation coefficient for the contribution of each pair of land cover changes to each comparison pattern;

[0030] According to Formula (III), calculate the second Pearson correlation coefficient between the contribution of land cover change and the contribution of population under each comparison model;

[0031] Based on the first Pearson correlation coefficient and the second Pearson correlation coefficient for each comparison mode, the correlation coefficient matrix for the multiple comparison modes is obtained;

[0032] (three);

[0033] in, When calculating the first Pearson correlation coefficient, it represents the first Pearson correlation coefficient; when calculating the second Pearson correlation coefficient, it represents the second Pearson correlation coefficient.

[0034] This represents a contribution rate under a land cover change within a comparative model;

[0035] To and Under the same comparison pattern, another land cover change and A contribution level within the same region;

[0036] This represents the average of all contributions under a land cover change scenario in a comparative model.

[0037] To and The mean of all contributions under another land cover change in the same comparison pattern.

[0038] The beneficial effects of this application are as follows:

[0039] This method uses national regions, natural regional divisions, provinces, and typical urban areas as multi-scale subdivisions. It derives various land cover changes based on land cover categories. Based on population data within these multi-scale subdivisions, it calculates population contribution under multiple comparison models. Furthermore, it calculates the land cover change contribution under multiple comparison models based on the area of ​​each type of land cover change within these multi-scale subdivisions. These comparison models include those between subdivisions at any scale and their larger-scale subdivisions. The method utilizes multiple factors, including population factors, to calculate contributions across various scales. This multi-scale, quantitative approach to contribution calculation is less susceptible to biases from a few data points and comprehensively reflects the importance of different natural regional divisions, provinces, and typical urban areas within a country in various types of land cover changes under multi-scale comparison models, providing a reference for land management, policy formulation, and ecological protection. Attached Figure Description

[0040] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0041] Figure 1 A flowchart illustrating a method for calculating the contribution of multi-scale land cover change provided in this application;

[0042] Figure 2 A multi-scale regional map of Nepal;

[0043] Figure 3 A map showing the population percentage of typical urban areas in various provinces of Nepal;

[0044] Figure 4 A flowchart illustrating a method for calculating the correlation between contributions of land cover change at multiple scales;

[0045] Among them: 1. Morang; 2. Danusa; 3. Kathmandu; 4. Kaski; 5. Rupandeshi; 6. Surkede; 7. Kelari. Detailed Implementation

[0046] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0047] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0048] Example 1

[0049] Please refer to Figure 1 This is a schematic diagram illustrating a method for calculating the contribution of multi-scale land cover change provided in this embodiment, including:

[0050] S1: Obtain the multi-scale division of the target country; the multi-scale division includes, in descending order of scale, the following: national region, natural regional region, province and typical city;

[0051] S2: Obtain the land cover category of the target country, and obtain various land cover changes based on the land cover category;

[0052] S3: Obtain population data under multi-scale regional division; calculate the population contribution under various comparison modes based on the population data under multi-scale regional division.

[0053] The multiple comparison modes include: a comparison mode between a region of arbitrary scale and a larger-scale region of its own.

[0054] S4: Obtain the area of ​​each land cover change under multi-scale regional division; calculate the contribution of land cover change under various comparison models based on the area of ​​each land cover change under multi-scale regional division.

[0055] Specifically, each of the following scales—national region, natural regional region, province, and typical urban area—may contain multiple types of land cover.

[0056] In some implementations, the multiple comparison modes specifically include:

[0057] Comparison patterns between provinces and national regions, comparison patterns between natural regional divisions and national regions, comparison patterns between provinces and natural regional divisions, comparison patterns between typical urban areas and their respective provinces, comparison patterns between typical urban areas and national regions, and comparison patterns between typical urban areas and natural regional divisions.

[0058] In the comparison model between provinces and national regions: it is necessary to calculate the data comparison between each province and the national region separately. The comparison model between natural regional divisions and national regions is similar.

[0059] In the comparison model of provinces to natural division areas: it is necessary to first select a natural division area to which each province belongs; in the existing technology, natural division areas with overlapping areas are generally arbitrarily selected as the natural division areas to which the province belongs; the same applies to the comparison model of typical urban areas to natural division areas.

[0060] For example, Nepal has 7 provinces. To calculate the contribution of each province to the total population of Nepal, it is necessary to calculate the contribution of each province to the total population of Nepal; thus, a total of 7 contribution values ​​of each province to the total population of Nepal are obtained.

[0061] For example, a province may contain multiple natural regional divisions, each encompassing portions of several provinces. In existing techniques, the natural regional division with the largest overlapping area with a province is generally considered the province's natural regional division. Then, data on the provinces included within each natural regional division are compared and calculated with the data of that natural regional division. Data comparisons are not performed between provinces and natural regional divisions that do not overlap in area because they offer no reference value.

[0062] Similarly, data comparisons are made between typical urban areas within a natural zoning area and such natural zoning areas. Data comparisons are also not made between typical urban areas that do not overlap in area and natural zoning areas because they are not of reference value.

[0063] Specifically, calculating the contribution of land cover change under multiple comparative models enables the calculation and analysis of the contribution of land cover change at different scales, thereby reducing the possibility of significant discrepancies between the calculated results and the actual situation due to the bias of a few data points. Quantitative analysis of the contribution is conducted, and definitive conclusions are given based on specific numerical values, thus significantly improving the reliability of the obtained results.

[0064] Furthermore, the most populous urban area in each province is taken as the typical urban area of ​​that province, and the population of the most populous urban area in each province is taken as the population of the typical urban area.

[0065] In some implementations, since the most populous urban area has the greatest impact on the population of the province to which it belongs, the most populous urban area in each province is taken as the typical urban area of ​​the province, and the data has the highest reference value when calculating the population contribution.

[0066] Furthermore, when a province belongs to multiple natural regional divisions, the natural regional division where the province's typical urban area is located is taken as the natural regional division to which the province belongs.

[0067] Specifically, the scope of a natural regionalization area overlaps with that of a province, and a province may have overlapping areas with multiple natural regionalization areas. In the existing technology, the natural regionalization area with the largest overlapping area with a province is generally regarded as the natural regionalization area to which the province belongs.

[0068] In some implementations, since the most populous urban areas have the greatest impact on the population of their respective natural administrative regions, the comparison model between provinces and natural administrative regions requires: firstly, selecting a natural administrative region for each province; theoretically, any natural administrative region with overlapping areas can be selected as the province's natural administrative region, but in existing technologies, the natural administrative region with the largest area overlap is generally selected as the province's natural administrative region; the same principle applies to the comparison model between typical urban areas and natural administrative regions. This also improves the reliability of the data when calculating population contribution.

[0069] Furthermore, the steps for obtaining the area of ​​each land cover change under multi-scale regional divisions include:

[0070] Obtain land cover category maps of the target country at two different time points;

[0071] Obtain national regional boundaries, natural regional boundaries, provincial boundaries, and typical urban area boundaries;

[0072] The two land cover category maps were spatially overlaid with national regional boundaries, natural regional boundaries, provincial boundaries, and typical urban area boundaries, and the areas were statistically analyzed to obtain the area of ​​each land cover change under multi-scale regional divisions, including:

[0073] The area of ​​land cover change for each type of land cover change in the country, the area of ​​land cover change for each type of land cover change in each province, the area of ​​land cover change for each type of land cover change in a typical urban area of ​​each province, and the area of ​​land cover change for each type of land cover change in each natural regional division.

[0074] Specifically, based on the land cover category maps of the target country at two different time points, spatial overlay is performed to obtain a land cover change map between the two time points. The area of ​​each type of land cover change under multi-scale regional divisions is then statistically calculated using this land cover change map.

[0075] In some implementations, by using land cover change maps of the target country at two time points and combining them with national regional boundaries, natural regional boundaries, provincial boundaries, and typical urban boundaries to spatially overlay and statistically analyze the area of ​​each type of land cover change, the area change value can be accurately obtained, further improving the data's reference value.

[0076] Specifically, spatial overlay, also known as spatial stacking or merging, is mainly used for comprehensive analysis of multiple thematic layers and is a traditional spatial analysis method determined by the regional and multi-layered characteristics of GIS. It can be divided into two types: vector and raster. Vector overlay can be further divided into point-polygon overlay, line-polygon overlay, and polygon-polygon overlay.

[0077] In this application, spatial overlay is used to spatially overlay vector maps containing national regional boundaries, natural regional boundaries, provincial boundaries, and typical urban boundaries with land cover change maps, and then to calculate the area of ​​land cover change under multi-scale regional division.

[0078] Furthermore, the contribution of land cover change under multiple comparison models is calculated according to formula (I);

[0079] (one);

[0080] Among them, the area contribution rate represents the contribution of the same type of land cover change under multiple comparison models.

[0081] In some implementations, the natural zoning area where a typical urban area of ​​a province is located is taken as the natural zoning area to which the province belongs, and the contribution of land cover change under the various comparison models includes:

[0082] The contribution of each province to each type of land cover change area to each type of land cover change area in the country region is calculated according to formula (iv);

[0083] (Four);

[0084] The contribution of each type of land cover change area in a typical urban area of ​​each province to the land cover change area of ​​each province is calculated according to formula (V);

[0085] (five);

[0086] The contribution of each land cover change area under each natural regionalization to each land cover change area in the country region is calculated according to formula (vi);

[0087] (six);

[0088] The contribution of the sum of the land cover change areas of each type in the typical urban areas of each province to the land cover change area of ​​each type in the country region is calculated according to formula (VII).

[0089] (seven);

[0090] The contribution of each type of land cover change area in each province to each type of land cover change area in its natural regionalization is calculated according to formula (viii).

[0091] (eight);

[0092] The contribution of the sum of the land cover change areas of each type in the typical urban areas of each province to the land cover change areas of each type in the natural regional area to which it belongs is calculated according to formula (IX).

[0093] (Nine);

[0094] in, k represents the number of provinces, and the number of typical urban areas is the same as the number of provinces; z is the number of natural regional divisions. , This represents the number of typical urban areas contained in the j-th type of natural regionalization; the number of typical urban areas contained in the j-th type of natural regionalization is equal to the number of provinces contained in the j-th type of natural regionalization.

[0095] The area of ​​change when the national / regional land cover category changes from m to n;

[0096] The area within province i that changes from land cover category m to n;

[0097] Let m be the area of ​​change in land cover category from m to n within a typical urban area of ​​province i.

[0098] Let m be the area within the j-th natural zoning region where the land cover category changes from m to n;

[0099] For the j-th type of natural regionalization The sum of the areas where the land cover category changes from m to n in a typical urban area;

[0100] This represents the contribution of the area of ​​land cover category change from m to n within province i to the area of ​​land cover category change from m to n in the national region.

[0101] This represents the contribution of the area of ​​change in land cover category from m to n in a typical urban area of ​​province i to the area of ​​change in land cover category from m to n in province i.

[0102] This represents the contribution of the area of ​​land cover change from m to n within the j-th natural zoning region to the area of ​​land cover change from m to n within the national region.

[0103] This represents the contribution of the sum of the areas of change in land cover category from m to n within a typical urban area of ​​province i to the area of ​​change in land cover category from m to n in the national region.

[0104] The contribution of the area of ​​land cover category change from m to n within province h to the area of ​​land cover category change from m to n within the region of natural regionalization j;

[0105] For the j-th type of natural regionalization The contribution of the sum of the areas where land cover categories change from m to n in typical urban areas to the areas where land cover categories change from m to n in the j-th natural zoning region;

[0106] m represents one of the land cover categories included in the target country; n represents another land cover category included in the target country. One or more of these categories are calculated based on the actual research content.

[0107] In some implementations, when the natural zoning area with the largest overlapping area with the province is taken as the natural zoning area to which the province belongs, since the typical urban area and the natural zoning area to which the province belongs may be different, it is necessary to calculate the land cover change area containing the typical urban area and the land cover change area containing the province in each natural zoning area separately.

[0108] Specifically, by performing land cover change contribution calculations under multiple comparison models, the contribution of land cover change can be calculated and analyzed at different scales, thereby reducing the possibility of significant discrepancies between the calculation results and the actual situation due to a few data biases.

[0109] Furthermore, when calculating the contribution of land cover change under the comparative model with typical urban areas, the ratio of the sum of the land cover change areas of all typical urban areas included in the larger-scale division area compared with typical urban areas to the land cover change area in the larger-scale division area is used as the corresponding contribution.

[0110] Specifically, comparing the sum of land cover change areas of typical urban areas with the land cover change areas of national regions, and comparing the sum of land cover change areas of typical urban areas within natural regionalization areas with the land cover change areas of natural regionalization areas, can improve the comparability of data and avoid situations where data is too small to be effectively referenced due to differences of several orders of magnitude. It also allows for adaptive adjustments based on differences between different countries and regions, improving the international applicability of this calculation method.

[0111] Furthermore, the population contribution under the various comparison models is calculated according to formula (II);

[0112] (two);

[0113] Among them, population contribution represents the population contribution under multiple comparison models.

[0114] In some implementations, the natural regional area where a typical urban area of ​​a province is located is taken as the natural regional area to which the province belongs, and the population contribution under the various comparison models includes:

[0115] The contribution of each province's population to the total population of the target country is calculated using formula (x).

[0116] (ten);

[0117] The contribution of the population of a typical urban area in each province to the total population of the province is calculated according to formula (XI).

[0118] (eleven);

[0119] The contribution of the population of each natural region to the total population of the target country is calculated according to formula (XII);

[0120] (twelve);

[0121] The contribution of the sum of the populations of typical urban areas in each province to the total population of the target country is calculated according to formula (xiii).

[0122] (Thirteen);

[0123] The contribution of each province's population to the population of its respective natural regional area is calculated according to formula (XIV);

[0124] (fourteen);

[0125] The contribution of the sum of the populations of typical urban areas in each province to the population of the natural regional area to which they belong is calculated according to formula (xv).

[0126] (fifteen);

[0127] in, k represents the number of provinces, and the number of typical urban areas is the same as the number of provinces; z is the number of natural regional divisions. , This represents the number of typical urban areas contained in the j-th type of natural regionalization. The number of typical urban areas contained in the j-th type of natural regionalization is equal to the number of provinces contained in the j-th type of natural regionalization.

[0128] The total population of the target country;

[0129] Let be the population of province i.

[0130] Let be the population within the j-th type of natural regionalization.

[0131] Let be the population of a typical urban area in province i.

[0132] Let be the population of province h under the j-th type of natural regionalization.

[0133] For the j-th type of natural regionalization The sum of the populations of a typical urban area;

[0134] This represents the contribution of the population of province i to the total population of the country / region.

[0135] This represents the contribution of the population of a typical urban area in province i to the total population of the province.

[0136] This represents the contribution of the population within the j-th type of natural regionalization to the total population of the country.

[0137] This represents the contribution of the sum of the populations of all typical urban areas to the total population of the country / region.

[0138] This represents the contribution of the population of province h under the j-th type of natural regionalization to the total population of the j-th type of natural regionalization.

[0139] This represents the contribution of the h-th typical urban area within the j-th natural regionalization to the j-th natural regionalization.

[0140] Calculate one or more of the above based on the actual research content.

[0141] In some implementations, when the natural division area with the largest overlapping area with the province is taken as the natural division area to which the province belongs, since the typical urban area and the natural division area to which the province belongs may be different, it is necessary to calculate the population of the typical urban area and the population of the province in each natural division area separately.

[0142] Furthermore, when calculating the population contribution under the comparative model with typical urban areas, the ratio of the sum of the population of all typical urban areas included in the larger-scale division area compared with typical urban areas to the land cover change area in the larger-scale division area is used as the corresponding contribution.

[0143] Specifically, comparing the sum of the populations of typical urban areas with the total population of the country / region, and comparing the sum of the populations of typical urban areas within a natural regionalization with the total population of the natural regionalization, improves the comparability of the data and avoids situations where the data is too small due to differences of several orders of magnitude. It also allows for adaptive adjustments based on differences between different countries and regions, enhancing the international applicability of this calculation method.

[0144] Example 2

[0145] refer to Figure 4 This is a schematic diagram illustrating a method for calculating the correlation between contributions of land cover change at multiple scales, as provided in this embodiment.

[0146] The method for calculating the contribution of multi-scale land cover change as described above also includes:

[0147] S5: Based on the population contribution and the land cover change contribution under the multiple comparison models, calculate the first Pearson correlation coefficient between any two land cover change contributions under the multiple comparison models and the second Pearson correlation coefficient between any one land cover change contribution and the population contribution under the multiple comparison models; obtain the correlation coefficient matrix under the multiple comparison models.

[0148] In some implementations, the correlation coefficient matrix under the comparison mode includes:

[0149] The correlation coefficient matrix between provinces and national regions includes: Pearson correlation coefficients of the contribution of each type of land cover change to the land cover change of the national region versus the contribution of another type of land cover change to the land cover change of the national region, under the comparison model between provinces and national regions;

[0150] The Pearson correlation coefficient between the contribution of each type of land cover change to the national land cover change and the contribution of the population of each province to the total population of the national region;

[0151] The correlation coefficient matrix between natural regional divisions and national regions includes: Pearson correlation coefficients of the contribution of each type of land cover change to the land cover change of the national region versus the contribution of another type of land cover change to the land cover change of the national region under the comparison model of natural regional divisions and national regions.

[0152] The Pearson correlation coefficient between the contribution of each type of land cover change to the national regional land cover change and the contribution of the population under each natural regionalization to the total national regional population;

[0153] The correlation matrix of all typical urban areas to the national region includes: the Pearson correlation coefficient of the contribution of each land cover change to the national region versus the contribution of another land cover change to the national region under the comparison model of all typical urban areas to the national region.

[0154] The Pearson correlation coefficient between the contribution of each type of land cover change to the national regional land cover change and the contribution of the sum of the populations of all typical urban areas to the total national regional population.

[0155] The correlation coefficient matrix between provinces and their respective natural regionalizations includes: the Pearson correlation coefficient between the contribution of each type of land cover change to the national regional land cover change and the contribution of another type of land cover change to the national regional land cover change, under the comparison model of provinces and their respective natural regionalizations.

[0156] The Pearson correlation coefficient between the contribution of each type of land cover change to national regional land cover change and the contribution of each province's population to the population of its respective natural region.

[0157] The correlation coefficient matrix between typical urban areas and their respective provinces includes: the Pearson correlation coefficient between the contribution of each type of land cover change to the national regional land cover change and the contribution of another type of land cover change to the national regional land cover change, under the comparison model of typical urban areas and their respective provinces.

[0158] The Pearson correlation coefficient between the contribution of each type of land cover change in a typical urban area of ​​each province to the land cover change of the province and the contribution of the population of the typical urban area of ​​each province to the population of the province.

[0159] The correlation matrix of all typical urban areas to their respective natural regions includes: Pearson correlation coefficients of the contribution of each type of land cover change to the national regional land cover change and the contribution of another type of land cover change to the national regional land cover change, under the comparison model of typical urban areas to their respective natural regions.

[0160] The Pearson correlation coefficient between the contribution of each type of land cover change to national regional land cover change and the contribution of the sum of the populations of typical urban areas to the populations of their respective natural regions.

[0161] Specifically, calculating the correlation coefficient matrix under multiple comparison modes can reflect the correlation between the contributions of land cover change and between the contributions of land cover change and the contributions of population at different scales; it can effectively reduce the assessment error caused by data bias; and improve the degree of agreement between the calculation results and the actual situation.

[0162] In some implementations, one or more of the above calculations are performed based on the specific research content. Calculating one or more correlation coefficient matrices according to actual needs can adapt to more national conditions and improve the international applicability of this solution.

[0163] Furthermore, the step of obtaining the correlation coefficient matrix under multiple comparison modes by calculating the first Pearson correlation coefficient and the second Pearson correlation coefficient includes:

[0164] According to Formula (III), calculate the first Pearson correlation coefficient for the contribution of each pair of land cover changes to each comparison pattern;

[0165] According to Formula (III), calculate the second Pearson correlation coefficient between the contribution of land cover change and the contribution of population under each comparison model;

[0166] Based on the first Pearson correlation coefficient and the second Pearson correlation coefficient for each comparison mode, the correlation coefficient matrix for the multiple comparison modes is obtained;

[0167] (three);

[0168] in, When calculating the first Pearson correlation coefficient, it represents the first Pearson correlation coefficient; when calculating the second Pearson correlation coefficient, it represents the second Pearson correlation coefficient.

[0169] This represents a contribution rate under a land cover change within a comparative model;

[0170] To and Under the same comparison pattern, another land cover change and A contribution level within the same region;

[0171] This represents the average of all contributions under a land cover change scenario in a comparative model.

[0172] To and The mean of all contributions under another land cover change in the same comparison pattern.

[0173] In some implementations, the process of calculating the Pearson correlation coefficient under a contrast model according to formulas (iii) and (xvii) includes:

[0174] Get all of these comparison modes and all To facilitate the description of the calculation process, let's assume... and There are n of each;

[0175] right Take the average, and get ;right Take the average, and get ;

[0176] Calculate each and The difference is used to obtain the first type of difference, which includes: , , ..., ;

[0177] Calculate each and The difference is used to obtain the second type of difference, which includes: , ,..., ;

[0178] Multiply the first type of difference and the second type of difference separately, and then add them together to obtain the first intermediate value. ;

[0179] Sum the squares of each first-type difference to obtain the second median value. ;

[0180] Sum the squares of each second-type difference to obtain the third median value. ;

[0181] Using the first intermediate value as the numerator, multiply the second and third intermediate values... Using the power as the denominator, the result is calculated. and Pearson correlation coefficient:

[0182] (sixteen);

[0183] Formula (III) is derived from Formula (XVI), and Formula (III) and Formula (XVI) are equivalent formulas.

[0184] Specifically, the Pearson correlation coefficient is used to determine the correlation between various contributions; the correlation between two different types of land cover change or between one type of land cover change and population is quantitatively analyzed to analyze the patterns of different land cover changes at multiple national scales and their relationship with population, and to give definite conclusions based on specific values, thereby significantly improving the reference value of the results.

[0185] Specifically, refer to Figure 2 This paper applies a method for calculating the contribution of land cover change at multiple scales and its correlation provided in this application to analyze the correlation between the contribution of land cover change and the contribution of population in Nepal at multiple scales between 2016 and 2019.

[0186] Obtain the multi-scale regional divisions of Nepal; the multi-scale regional divisions of Nepal, in descending order of scale, include: Nepal's national region, natural regional divisions, Nepal's provinces, and typical urban areas of Nepal; among them, the target natural regional divisions take ecological regions as an example, and the ecological regions included in Nepal include: mountainous areas, hilly areas, and the Terai plain. As shown in Table 1, Nepal's regional division table.

[0187] The land cover categories of Nepal are obtained as follows: forest, farmland, grassland, and urban areas. Based on these land cover categories, various land cover changes are obtained, including: forest to farmland, farmland to urban areas, farmland to grassland, and farmland to forest.

[0188] Obtain population data across multiple scales and regions; based on population data from the 2011 and 2021 Nepal censuses.

[0189] Since the land cover change data covers the period from 2016 to 2019, the 2011 census data and the 2021 census data are used as reference values ​​for Nepal's population data at the two time points of 2016 and 2019, respectively.

[0190] Based on population data divided into regions at multiple scales, population contribution rates were calculated under various comparative models.

[0191] Table 2 shows the contribution of provinces to national regional land cover change and population, Table 3 shows the contribution of typical urban areas to their respective provinces to land cover change and population, and Table 4 shows the contribution of ecological zones to national regional land cover change.

[0192] Among them, reference Figure 3 The city with the largest population in each province is taken as the typical city of that province, as shown in Table 1; the population of the city with the largest population in each province is taken as the population of the typical city.

[0193] The typical urban area of ​​Nepal's First Province is: Morang 1;

[0194] A typical city in Madhya Pradesh is Danusa 2.

[0195] A typical city in Baghmati is Kathmandu.

[0196] A typical urban area in Gandaki is Kaski 4;

[0197] A typical urban area in Lumbini is Rupandehi 5.

[0198] A typical urban area in Karnataka is Surkhed 6;

[0199] The typical city in Far West State is: Kelari 7.

[0200] The natural administrative region where the typical urban area of ​​each province is located is taken as the natural administrative region of the province to which the typical urban area belongs.

[0201] Nepal's various contrast models include:

[0202] Comparison patterns between provinces and national regions; comparison patterns between ecological zones and national regions; comparison patterns between typical urban areas and their respective provinces.

[0203] Obtain Nepal's national and regional boundaries, ecological zone boundaries, provincial boundaries, and typical urban boundaries;

[0204] Based on the land cover classification maps of Nepal in 2016 and 2019, the boundaries of Nepalese administrative regions, the boundaries of ecological zones, the boundaries of Nepalese provinces, and the boundaries of typical urban areas, a multi-scale land cover change map of Nepal for the period of 2016-2019 was obtained by spatial overlaying.

[0205] Using the land cover change maps of Nepal at multiple scales for the period 2016-2019, the area of ​​each type of land cover change under the multi-scale regional divisions was obtained, including:

[0206] The area of ​​land cover change for each type of land cover change in the country, the area of ​​land cover change for each type of land cover change in each province, the area of ​​land cover change for each type of land cover change in a typical urban area of ​​each province, and the area of ​​land cover change for each type of land cover change in each natural regional division.

[0207] Based on the area of ​​each land cover change under multi-scale regional division, the contribution of land cover change under various comparative models in Nepal was calculated.

[0208] Table 2 shows the contribution of provinces to national regional land cover change and population, Table 3 shows the contribution of typical urban areas to their respective provinces to land cover change and population, and Table 4 shows the contribution of ecological zones to national regional land cover change.

[0209] Based on the population contribution and land cover change contribution under various comparative models in Nepal, the first Pearson correlation coefficient between land cover change contribution and the second Pearson correlation coefficient between land cover change contribution and population contribution under various comparative models in Nepal were calculated; thus, the correlation coefficient matrix under various comparative models in Nepal was obtained. These are shown in Table 5 (Province to Country Region Correlation Coefficient Matrix), Table 6 (Natural Regional Division to Country Region Correlation Coefficient Matrix), and Table 7 (Typical City to Province Correlation Coefficient Matrix).

[0210] Specifically, taking the Pearson correlation coefficient of the correlation coefficient matrix between provinces and the country as an example, the steps to calculate the Pearson correlation coefficient between the contribution of Nepalese provinces to the conversion of farmland to grassland and the contribution of Nepalese provinces to the conversion of farmland to urban areas are as follows:

[0211] calculate The average contribution of provincial farmland-to-grassland conversion to the national regional farmland-to-grassland conversion. The average contribution of provincial farmland conversion to urban areas to the national regional farmland conversion to urban areas;

[0212] Will , Substituting the values ​​of each province's farmland-to-grassland conversion in Table 2 to the national-regional farmland-to-grassland conversion, and the values ​​of each province's farmland-to-urban conversion in Table 2 to the national-regional farmland-to-urban conversion, into Formula (III), the calculated Pearson correlation coefficient is 0.08. Based on the correlation criteria, the conclusion is that between 2016 and 2019, land cover change from farmland to grassland and from farmland to urban in Nepal exhibits a very weak or no correlation at the province-to-national-regional scale. Therefore, it can be concluded that there is a very weak or no correlation between land cover change from farmland to urban in Nepal and land cover change from farmland to grassland.

[0213] Specifically, existing research findings include the following criteria for judging the relevance of the Pearson correlation coefficient r:

[0214] When 0.8 < When the correlation coefficient is ≤1.0, it is defined as extremely strong correlation;

[0215] When 0.6 < A correlation of ≤0.8 is defined as strong.

[0216] When 0.4 < A correlation of ≤0.6 is defined as moderate.

[0217] When 0.2 < When the correlation coefficient is ≤0.4, it is defined as a weak correlation;

[0218] When 0.0≤ When the correlation is ≤0.2, it is defined as extremely weak or no correlation.

[0219] in, This represents the absolute value of r; when r is greater than 0, it is defined as a positive correlation; when r is less than 0, it is defined as a negative correlation; and when r equals 0, it is defined as no correlation.

[0220] For example, r=-0.25 indicates that the two compared data are negatively correlated and have a weak correlation; r=0.65 indicates that the two compared data are positively correlated and have a strong correlation.

[0221] Using the same calculation process and inputting the corresponding data, the Pearson correlation coefficient between Nepal's 2011 population and the contribution of provincial farmland-to-urban conversion to the national farmland-to-urban conversion was calculated at the provincial-to-national scale. The Pearson correlation coefficient was found to be 0.62. Based on the aforementioned correlation judgment criteria, the following conclusion can be drawn: the contribution of Nepal's 2011 provincial population to the total national population is positively and strongly correlated with the contribution of Nepal's 2011 population contribution and the contribution of land cover change from farmland-to-urban conversion during the 2016-2019 period, calculated under the provincial-to-national scale. Based on this judgment, it can be concluded that: the greater the population contribution of a province in Nepal, the greater the land cover contribution from farmland-to-urban conversion tends to be in that province; conversely, the smaller the population contribution of a province, the smaller the land cover contribution from farmland-to-urban conversion tends to be in that province.

[0222]

[0223] Table 1. Administrative Divisions of Nepal

[0224]

[0225] Table 2. Provincial Contributions to National Regional Land Cover Change and Population

[0226]

[0227] Table 3. Contribution of Typical Urban Areas to Land Cover Change and Population in Their Provinces

[0228]

[0229] Table 4. Contribution of Ecological Zones to National Regional Land Cover Change

[0230]

[0231] Table 5: Correlation Matrix of Provinces to National Regions

[0232]

[0233] Table 6. Correlation Matrix of Natural Regional Divisions to National Regions

[0234]

[0235] Table 7. Correlation Matrix of Typical Urban Areas with Their Corresponding Provinces

[0236] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for calculating a contribution degree of multi-scale land cover change, characterized in that, The method comprises the following steps: obtaining a multi-scale divided region of a target country; the multi-scale divided region comprises, in order from large to small, a country region, a natural division region, a province, and a typical urban area; obtaining land cover categories of the target country, and obtaining a plurality of land cover changes according to the land cover categories; obtaining population data in the multi-scale divided region, and calculating population contribution degrees in a plurality of comparison modes according to the population data in the multi-scale divided region; the population contribution degrees in the plurality of comparison modes are calculated according to formula (2); (ii); wherein the population contribution degree represents the population contribution degree in the plurality of comparison modes; the plurality of comparison modes comprise a comparison mode between a divided region of any scale and a larger-scale divided region in which the divided region of any scale is located; obtaining an area of each land cover change in the multi-scale divided region, comprising: obtaining land cover category maps of the target country at two different time points; obtaining country region boundaries, natural division region boundaries, province boundaries, and typical urban area boundaries; spatially superimposing the two land cover category maps on the country region boundaries, the natural division region boundaries, the province boundaries, and the typical urban area boundaries respectively, and counting the areas to obtain the area of each land cover change in the multi-scale divided region, comprising: a country region area of each land cover change, a per-province area of each land cover change, a typical urban area area of each land cover change in each province, and a natural division region area of each land cover change; calculating land cover change contribution degrees in a plurality of comparison modes according to the area of each land cover change in the multi-scale divided region; the land cover change contribution degrees in the plurality of comparison modes are calculated according to formula (1); (I); wherein the area contribution degree represents the contribution degree of the same type of land cover change in the plurality of comparison modes.

2. The method of claim 1, wherein, taking the urban area with the largest population in each province as the typical urban area of the province, and taking the population of the urban area with the largest population in each province as the population of the typical urban area.

3. The method of claim 1, wherein, when there are multiple natural division regions to which a province belongs, taking the natural division region in which the typical urban area of the province is located as the natural division region to which the province belongs.

4. The method of claim 1, wherein, when calculating the land cover change contribution degrees in the comparison modes related to the typical urban area, taking the ratio of the sum of the land cover change areas of all typical urban areas contained in the larger-scale divided region to the land cover change area in the larger-scale divided region as the corresponding contribution degree.

5. The method of claim 1, wherein, when calculating the population contribution degrees in the comparison modes related to the typical urban area, taking the ratio of the sum of the populations of all typical urban areas contained in the larger-scale divided region to the land cover change area in the larger-scale divided region as the corresponding contribution degree.

6. A method for calculating the correlation between the contributions of multi-scale land cover changes, comprising a method for calculating the contributions of multi-scale land cover changes according to claim 1, characterized in that, The method further comprises the following steps: calculating first Pearson correlation coefficients between any two land cover change contribution degrees in a plurality of comparison modes and second Pearson correlation coefficients between any land cover change contribution degree and a population contribution degree in the plurality of comparison modes according to the population contribution degrees in the plurality of comparison modes and the land cover change contribution degrees in the plurality of comparison modes; obtaining a correlation coefficient matrix in the plurality of comparison modes.

7. The method of claim 6, wherein the method further comprises: The step of obtaining the correlation coefficient matrix under the plurality of comparison modes by calculating the first and second Pearson correlation coefficients comprises: According to formula (three), the first Pearson correlation coefficient between the contribution degree of each land cover change under each comparison mode is calculated one by one; According to formula (three), the second Pearson correlation coefficient between the contribution degree of each land cover change and the population contribution degree under each comparison mode is calculated one by one; According to the first Pearson correlation coefficient under each comparison mode and the second Pearson correlation coefficient under each comparison mode, the correlation coefficient matrix under the plurality of comparison modes is obtained; (three); wherein represents the first Pearson correlation coefficient when calculating the first Pearson correlation coefficient, and represents the second Pearson correlation coefficient when calculating the second Pearson correlation coefficient; is a contribution of a land cover change under a contrast mode; a contribution of the same region under another land cover change a contribution of the same region under another land cover change a contribution of the same region under another land cover change is the mean of all contributions under a land cover change for a contrast mode; The mean of all contributions under another land cover change under the same comparison mode. The mean of all contributions under another land cover change under the same comparison mode.

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