CN117668420B - Cultivated land continuous degree calculation method and system considering self-adaptive neighborhood - Google Patents
Cultivated land continuous degree calculation method and system considering self-adaptive neighborhood Download PDFInfo
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Abstract
The invention provides a method and a system for calculating the continuous cropping degree of a cultivated land by considering a self-adaptive neighborhood, wherein the method comprises the following steps: acquiring the vector data of the cultivated map spots, and preprocessing the vector data of the cultivated map spots; performing initial aggregation on the cultivated land patches according to the adjacent relation between the cultivated land and the characteristic elements and according to different neighborhood radiuses; creating a cultivated land grid, iteratively creating a cultivated land self-adaptive multi-scale grid according to the area ratio of the cultivated land subset to the cultivated land complement in the grid, and determining an optimal scale cultivated land grid; and calculating the continuous farmland degree in the grid according to the established optimal-scale farmland grid. The invention can utilize the self-adaptive neighborhood to carry out local space aggregation on the cultivated land patch, and establish the cultivated land self-adaptive multi-scale grid, further comprehensively consider the characteristics of scale, position, shape, distance, space relation and the like of the cultivated land, consider the cultivated land condition of the eight neighborhood range area of the grid, and quantitatively calculate and measure the cultivated land linkage degree.
Description
Technical Field
The invention belongs to the technical field of farmland management planning, and particularly relates to a farmland continuous calculation method and system considering a self-adaptive neighborhood.
Background
At present, the national and local governments of China have continuously exported a series of policy documents to promote the centralized continuous protection of cultivated lands and improve the quality of cultivated lands. However, problems of crushing, low concentration, degradation of quality and the like of cultivated lands still exist, and the problems prevent large-scale and mechanized operation of the cultivated lands, and simultaneously reduce the intensive utilization level of cultivated land resources and ecological service functions, thereby threatening the grain safety to a certain extent. Therefore, the research on the calculation of the continuous cropping of the regional cultivated land becomes particularly important, and the method can provide technical support for the centralized continuous cropping management and protection of the propelled cultivated land.
The existing farmland connection degree research is relatively less, and is mainly focused on three aspects of an area threshold method, a landscape pattern method and a single-scale grid splitting method. Some students have achieved relevant research efforts in these areas, such as Xing Yaodong, zhang Chao, tian Huiwen, li Mengyang, wu Wendi, lu Xuejun, zhang Baohua, and the like. However, the existing research mainly aims at administrative division units of county areas and below in scale, and has larger errors and data redundancy problems for areas of cities and above with larger range; most of research objects are mainly cultivated land grid pixels, few people study the optimal scale of the pixels, and the pixels cannot be accurately mapped to actual cultivated land patches if the pixels are too large, so that the requirements of modern agriculture on fine management cannot be met; the evaluation method is too dependent on landscape pattern indexes, and ignores the spatial relation among cultivated lands, the spatial relation among the cultivated lands and other elements and the spatial difference characteristics of the cultivated lands; grid subdivision and threshold determination generally adopt a subjectively assumed specific scale or a plurality of specified scales for tilling subdivision, and a unified single window width threshold is adopted for evaluating the tilling attachment degree of the whole area. However, the mesh subdivision of a particular scale makes it difficult to precisely match the mesh range with the cultivated land patch. In addition, the cultivated land distribution in different areas has obvious difference, if only a single window width is used for large-scale cultivated land aggregation, the cultivated land continuous sheet calculation result is lack of pertinence, even an unreasonable measurement result can be obtained, and the aim of concentrated continuous sheet protection of the cultivated lands is difficult to realize according to actual conditions.
Disclosure of Invention
The invention provides a cultivated land continuous sheet calculation method and system considering a self-adaptive neighborhood. According to the method, the adaptive neighborhood is utilized to carry out local space aggregation on the cultivated land patch, a cultivated land adaptive multi-scale grid is established, characteristics such as scale, position, shape, distance, space relation and the like of cultivated lands are further comprehensively considered, the cultivated land condition of eight neighborhood region areas of the grid is considered, and quantitative calculation and measurement are carried out on the cultivated land attachment degree. This will provide a reference for the establishment of extensive high standard farmland construction and basic farmland definition improvement measures, thereby overcoming the problems in the prior art as described above.
The technical scheme for solving the technical problems is as follows:
In a first aspect, the present invention provides a method for calculating a continuous cultivation scale in consideration of an adaptive neighborhood, including the steps of:
S1: acquiring the vector data of the cultivated map spots, and preprocessing the vector data of the cultivated map spots;
s2: performing initial aggregation on the cultivated land patches according to the adjacent relation between the cultivated land and the characteristic elements and according to different neighborhood radiuses;
s3: creating a cultivated land grid, iteratively creating a cultivated land self-adaptive multi-scale grid according to the area ratio of the cultivated land subset to the cultivated land complement in the grid, and determining an optimal scale cultivated land grid;
s4: and calculating the continuous farmland degree in the grid according to the established optimal-scale farmland grid.
In some embodiments, the S1 comprises:
s11: land utilization vector data based on homeland investigation data comprises three subclasses of dry land, paddy field and watered land;
S12: space merging is carried out on adjacent dry lands, paddy fields and watered land patches, and a new cultivated land patch aggregation layer is generated;
S13: each cultivated land patch area is calculated.
In some embodiments, the S2 comprises:
S21: calculating the characteristic element patch widths among the farmland patches in the target area, and calculating the average value of all the characteristic element patch widths;
S22: taking the minimum width of all the characteristic element patches as an initial aggregation value, initially aggregating the cultivated land patches, adding one meter to the initial aggregation value according to each iteration, and iteratively aggregating the cultivated land patches; counting the total number of cultivated land patches after each polymerization;
S23: based on the number of the cultivated land patches before and after the aggregation, calculating the relative error of the cultivated land patches before and after the aggregation, calculating the average value of the relative error, converging the relative error according to an upward rounding principle, and selecting an aggregation threshold value, with the relative error closest to the average value of the relative error, as an optimal aggregation radius;
S24: and (3) aggregating the cultivated land patches according to the optimal aggregation radius, intersecting and inverting the cultivated land patches with the original cultivated land patches, extracting image patch data exceeding the range of the original cultivated land patches after aggregation, and erasing the cultivated land patch vector data formed by aggregation to obtain final cultivated land patch aggregation vector data.
In some embodiments, the S3 comprises:
s31: establishing a grid maximum scale of the cultivated land patches of the target area by taking four points of the circumscribed enveloping rectangular frame of all the cultivated land patches in the target area as references;
s32: and determining the optimal scale of each cultivated land patch corresponding to the grid based on the ratio of the cultivated land area occupied ratio in the grid to the cultivated land complement area occupied ratio in the grid.
In some embodiments, the step S4 includes:
s41: according to the established optimal-scale cultivated land grid, calculating original indexes of the cultivated land continuous sheet degree in the grid, wherein the original indexes comprise cultivated land area indexes, cultivated land gathering degree, cultivated land connecting degree, cultivated land crushing degree, cultivated land compactness and cultivated land proximity;
s42: and calculating the continuous cropping degree of the cultivated land according to the original index.
In some embodiments, the step S41 includes:
S411: calculating an index of the cultivated land area, wherein the specific formula is as follows:
Wherein, Representing the cultivated area index of the ith grid,/>Representing the cultivated land area of the ith grid, and S represents the total cultivated land area in the eight neighborhood grid set domain;
s412: the farmland gathering degree is calculated, and the specific formula is as follows:
Wherein, Representing the cultivated land concentration of the ith grid,/>Representing the area of the grid l plowing plaque,/>Representing the area of the grid k farmland plague,/>Representing the average value of all plowing plaque areas in the range of the grid set domain of the eight neighborhood grids of grid l and grid k,/>The element value of the spatial weight matrix of the cultivated land is represented by n, which is the grid number;
s413: the cultivated land connectivity is calculated, and the specific formula is as follows:
Wherein, For the cultivated land connectivity of the ith grid,/>For the area of the cultivated land patch I,/>The area of the cultivated land patch k is n is the total number of cultivated land patches in the grid, and S is the total area of cultivated lands in the grid;
s414: the cultivated land crushing degree is calculated, and the specific formula is as follows:
Wherein, Representing the cultivated land breaking degree of the ith grid,/>Representing the number of plowing patches in the ith grid,/>Representing the total area of cultivated land in the ith grid;
S415: the cultivated land compactness is calculated, and the specific formula is as follows:
Wherein, Representing the compactness of the cultivated land in the ith grid,/>Representing the area of the mth tilling area within the grid,The external rectangular area of the m-th cultivated land patch in the grid is represented, and n is the total number of the cultivated land patches in the grid;
s416: the method for calculating the farmland proximity comprises the following specific formulas:
Wherein, Representing the proximity of cultivated land in the ith grid,/>Representing the shortest distance between the kth tilling patch and the nearest neighbor first tilling patch boundary in the ith grid,/>Indicating the number of the tilled areas in the ith grid.
In some embodiments, the step S42 includes:
s421: carrying out dimensionless treatment on the six original indexes, and obtaining positive index representation and negative index representation of the original indexes:
Wherein, Represents the normalized value of the original index, and if/>If the index is a forward index, the calculation mode is as shown in the formula (1), if/>The index is negative, and the calculation mode is according to the step (2); /(I)Representing the original value of the j index of the i-th grid; representing the original index/> Is the maximum value of (2); /(I)Representing the original index/>Is the minimum of (2);
s422: the original index coefficient is calculated, and the specific calculation formula is as follows:
Wherein, Index value/>, representing the j-th item of the ith gridA ratio of the index value to the sum of the index values of the jth item in all grids in the range of the eighth neighborhood grid set domain of the ith grid; /(I)Representation of e-based calculation/>Natural logarithm of (a); n represents the number of grids in the target area; /(I)A j-th original index coefficient representing an i-th grid;
S423: the standardized weighting value of the original index is calculated, and the specific calculation formula is as follows:
Wherein, Weights representing the original indicators; /(I)A normalized weighting value representing the jth original indicator of the ith mesh;
s424: the continuous farmland degree is calculated, and the specific calculation formula is as follows:
Wherein, Representing an optimal solution closeness value of the ith grid; /(I)Representing the worst approach value of the ith mesh; /(I)Representing a forward ideal state value; /(I)Representing a negative ideal state value; /(I)Representing the continuous farmland degree of the ith grid.
In a second aspect, the present invention provides a system for computing the continuous range of farmland in consideration of adaptive neighborhood, comprising:
the data acquisition module is used for acquiring the vector data of the cultivated map spots and preprocessing the vector data of the cultivated map spots;
The patch aggregation module is used for initially aggregating the cultivated land patches according to the adjacent relation between the cultivated land and the characteristic elements and according to different neighborhood radiuses;
The scale determining module is used for creating a cultivated land grid, iteratively creating a cultivated land self-adaptive multi-scale grid according to the area ratio of the cultivated land subset to the cultivated land complement in the grid, and determining an optimal scale cultivated land grid;
and the connection degree calculation module is used for calculating the connection degree of the cultivated land in the grid according to the established optimal-scale cultivated land grid.
In a third aspect, the present invention provides a computer comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a computing method as claimed in any one of the preceding claims when executing the computer program.
In a fourth aspect, the present invention provides a readable storage medium having stored thereon a computer program which when executed by a processor implements a computing method as claimed in any one of the preceding claims.
The beneficial effects of the application are as follows:
The method and the system for calculating the continuous tilling degree by considering the self-adaptive neighborhood can utilize the self-adaptive neighborhood to carry out local spatial aggregation on the tilling patch, establish the tilling self-adaptive multi-scale grid, further comprehensively consider the characteristics of the size, the position, the shape, the distance, the spatial relationship and the like of the tilling, consider the tilling condition of the area of eight neighborhood regions of the grid, and quantitatively calculate and measure the continuous tilling degree. This will provide a reference for the establishment of extensive high standard farmland construction and basic farmland definition improvement measures.
Drawings
FIG. 1 is a flow chart of a calculation method of the present application;
FIG. 2 is a sub-flowchart of step S1 of the present application;
FIG. 3 is a sub-flowchart of step S2 of the present application;
fig. 4 is a sub-flowchart of step S3 of the present application.
Detailed Description
The principles and features of the present invention are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
In order that the above-recited objects, features and advantages of the present application can be more clearly understood, a more particular description of the application will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It is to be understood that the depicted embodiments are some, but not all, embodiments of the present application. The specific embodiments described herein are to be considered in an illustrative rather than a restrictive sense. All other embodiments, which are obtained by a person skilled in the art based on the described embodiments of the application, fall within the scope of protection of the application.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The method for calculating the continuous farmland degree by considering the self-adaptive neighborhood comprises the following steps in combination with fig. 1 and fig. 2:
S1: acquiring the vector data of the cultivated map spots, and preprocessing the vector data of the cultivated map spots;
In some embodiments, in conjunction with fig. 2, which is a sub-flowchart of step S1 of the present application, the step S1 includes:
s11: land utilization vector data based on homeland investigation data comprises three subclasses of dry land, paddy field and watered land;
S12: space merging is carried out on adjacent dry lands, paddy fields and watered land patches, and a new cultivated land patch aggregation layer is generated;
S13: each cultivated land patch area is calculated.
Specifically, based on land utilization vector data in the homeland investigation data, farmland patch vector data is extracted according to attribute fields of which the values of land class codes are 0101, 0102 and 0103, and the farmland patch vector data comprises three subclasses of dry land, paddy field and watered land. And adding a fusion index field 'ID' into the extracted farmland patch vector data attribute table, and assigning the attribute field value as '01'. Then, selecting an integrated index attribute field (ID), and performing integration treatment on the three types of farmland patch vector data layers extracted in the S11 by using an element integration method to spatially integrate adjacent farmland, paddy field and watered land patches, generating a new farmland patch aggregation layer, and naming the new farmland patch aggregation layer as layer1. Looking up an attribute table of a layer1 of the farmland patch aggregation layer, if only one attribute record exists in the aggregation layer, but one farmland patch formed by aggregation of a plurality of non-adjacent independent farmland patches is corresponding, disassembling the non-adjacent independent farmland patches by adopting a method of splitting the multi-component elements, enabling each independent farmland patch to correspond to one attribute record, and naming the disassembled farmland patch aggregation layer as layer2. An Area attribute field "Area" is newly added in the attribute table of the layer2 of the layer, and the plaque Area of each cultivated land is calculated.
S2: performing initial aggregation on the cultivated land patches according to the adjacent relation between the cultivated land and the characteristic elements and according to different neighborhood radiuses;
in some embodiments, in conjunction with fig. 3, which is a sub-flowchart of step S2 of the present application, the step S2 includes:
S21: calculating the characteristic element patch widths among the farmland patches in the target area, and calculating the average value of all the characteristic element patch widths;
S22: taking the minimum width of all the characteristic element patches as an initial aggregation value, initially aggregating the cultivated land patches, adding one meter to the initial aggregation value according to each iteration, and iteratively aggregating the cultivated land patches; counting the total number of cultivated land patches after each polymerization;
S23: based on the number of the cultivated land patches before and after the aggregation, calculating the relative error of the cultivated land patches before and after the aggregation, calculating the average value of the relative error, converging the relative error according to an upward rounding principle, and selecting an aggregation threshold value, with the relative error closest to the average value of the relative error, as an optimal aggregation radius;
S24: and (3) aggregating the cultivated land patches according to the optimal aggregation radius, intersecting and inverting the cultivated land patches with the original cultivated land patches, extracting image patch data exceeding the range of the original cultivated land patches after aggregation, and erasing the cultivated land patch vector data formed by aggregation to obtain final cultivated land patch aggregation vector data.
Specifically, the field ridge, facility agricultural land, bare land, ditch, pit water surface, rural road, water area, garden, woodland, grassland element patch widths between the plowing patches in the target area are calculated, and the average value of all the element patch widths is calculated. Furthermore, the minimum width of the elements is used as an initial value of aggregation, the arcGIS aggregation tool (AGGREGATE POLYGONS) is used for carrying out iterative aggregation on the farmland patches based on different distances, the total number of the farmland patches after each aggregation is counted (namely, the minimum width is used as the initial value of aggregation, 1 meter is added continuously, the operation is repeated, all the farmland patches are subjected to iterative aggregation, and the patch number corresponding to each aggregation width is calculated). Based on the number of the cultivated land patches before and after the polymerization, calculating the relative error of the cultivated land patches before and after the polymerization, calculating the average value of the relative error, and selecting the threshold value corresponding to the relative error closest to the average relative error as the optimal polymerization radius threshold value according to the principle that the relative error is not smaller and is rounded until the polymerized patch number gradually converges. And finally, carrying out plaque aggregation and edge optimization treatment on the cultivated land. And (2) intersecting and inverting the cultivated land patch formed by the optimal threshold aggregation with the cultivated land patch extracted in the step (S1), extracting image patch data exceeding the range of the original cultivated land patch after aggregation, and erasing the cultivated land patch vector data formed by aggregation by utilizing the data to obtain final cultivated land patch aggregate vector data, so as to ensure that the area and the range of the aggregated cultivated land and the original cultivated land patch are unchanged.
S3: and (3) creating a cultivated land grid, iteratively creating a cultivated land self-adaptive multi-scale grid according to the area ratio of the cultivated land subset to the cultivated land complement in the grid, and determining the optimal scale cultivated land grid.
In some embodiments, in conjunction with the sub-flowchart of fig. 4, step S3, the step S3 includes:
s31: establishing a grid maximum scale of the cultivated land patches of the target area by taking four points of the circumscribed enveloping rectangular frame of all the cultivated land patches in the target area as references;
s32: and determining the optimal scale of each cultivated land patch corresponding to the grid based on the ratio of the cultivated land area occupied ratio in the grid to the cultivated land complement area occupied ratio in the grid.
Specifically, firstly, a fishing net creating tool is utilized to create the maximum grid scale of the farmland patch of the target area by taking the four-way point of the circumscribed enveloping rectangular frame of all the farmland patches in the target area as a reference. And calculating the area ratio of each cultivated land patch in the grid, if the area ratio of each cultivated land patch in the grid is equal to 100%, namely, the grid is completely covered by cultivated lands in a seamless manner, stopping dividing, otherwise, further subdividing the grid into four-way trees, dividing the grid into smaller sub-grids, and sequentially calculating the ratio of the area ratio of each cultivated land in the grid to the area ratio of the cultivated land complement area in the grid. Further, an initial mesh minimum scale is determined according to the percentile method. For a target area, firstly calculating the farmland patch area, the farmland patch perimeter and the ratio of the farmland patch perimeter to the area in the Layer3 of the area; then sequencing the three indexes from small to large respectively, taking the corresponding numerical values of the positions of the three indexes corresponding to 5% respectively by using a percentile method, and rounding the three indexes according to the principle of small size and big size; further, a ratio of the area of the cultivated land within the grid to the area of the complement of cultivated land within the grid is calculated. Further, an optimal dimension of the grid is determined based on a ratio of an area of the cultivated land within the grid to an area of the complementary area of the cultivated land within the grid. Taking the dimension of the divided grids as an abscissa, taking the ratio of the area occupied by the cultivated land in the grids to the area occupied by the complementary collecting area of the cultivated land in the grids and the total number of grids divided into the current dimension as an ordinate, fitting a change curve graph of continuously decreasing the ratio of the area occupied by the cultivated land in the grid to the area occupied by the complementary area of the cultivated land in the grid along with the continuous decrease of the grid scale. Then, the slopes of the two curves are calculated, the grid scale corresponding to the intersection inflection point with the gentle slope of the two curves is obtained, and the grid scale is determined as the optimal scale.
S4: and calculating the continuous farmland degree in the grid according to the established optimal-scale farmland grid.
In some embodiments, the step S4 includes:
s41: according to the established optimal-scale cultivated land grid, calculating original indexes of the cultivated land continuous sheet degree in the grid, wherein the original indexes comprise cultivated land area indexes, cultivated land gathering degree, cultivated land connecting degree, cultivated land crushing degree, cultivated land compactness and cultivated land proximity;
In some embodiments, the step S41 includes:
S411: calculating an index of the cultivated land area, wherein the specific formula is as follows:
Wherein, Representing the cultivated area index of the ith grid,/>Representing the cultivated land area of the ith grid, and S represents the total cultivated land area in the eight neighborhood grid set domain;
Specifically, each grid in the target area and 8 adjacent grids around the grid form an eight-neighborhood grid set domain. Then, the cultivated area index is calculated by the ratio of the cultivated area in each grid to the total cultivated area in the set of neighbor grids. It should be noted that if there are no eight adjacent grids connected to each other around the grid, the grid and 8 grids nearest to the grid are taken to form an eight-neighborhood grid set domain.
S412: the farmland gathering degree is calculated, and the specific formula is as follows:
Wherein, Representing the cultivated land concentration of the ith grid,/>Representing the area of the grid l plowing plaque,/>Representing the area of the grid k farmland plague,/>Representing the average value of all plowing plaque areas in the range of the grid set domain of the eight neighborhood grids of grid l and grid k,/>The element value of the spatial weight matrix of the cultivated land is represented by n, which is the grid number;
Specifically, firstly, calculating the number of grids in a target area and the area of the plowed land plaque in each grid; and then, searching the aggregate domain range of the eight neighborhood grids for each grid in turn, and calculating the average value of all the plowing plaque areas in the aggregate domain range one by one. Further, by a multi-scale grid eight-neighborhood space adjacent judging method, the adjacent relation between the grid and surrounding multi-scale grids is calculated, a multi-scale grid cultivated land space adjacent matrix is constructed based on the adjacent relation, and further cultivated land concentration is calculated.
S413: the cultivated land connectivity is calculated, and the specific formula is as follows:
Wherein, For the cultivated land connectivity of the ith grid,/>For the area of the cultivated land patch I,/>The area of the cultivated land patch k is n is the total number of cultivated land patches in the grid, and S is the total area of cultivated lands in the grid;
Specifically, for each grid in the target area, firstly calculating the number of the cultivated land patches and the total area of the cultivated land patches in the grid, then calculating the product of each pair of the cultivated land patch areas in the grid, and summing the products of all pairs of the cultivated land patch areas in the grid.
S414: the cultivated land crushing degree is calculated, and the specific formula is as follows:
Wherein, Representing the cultivated land breaking degree of the ith grid,/>Representing the number of plowing patches in the ith grid,/>Representing the total area of cultivated land in the ith grid;
specifically, the crushing degree of the grid cultivated land is calculated, and the ratio of the number of cultivated land patches in each grid in the target area to the cultivated land area is directly used for representing.
S415: the cultivated land compactness is calculated, and the specific formula is as follows:
Wherein, Representing the compactness of the cultivated land in the ith grid,/>Representing the area of the mth tilling area within the grid,The external rectangular area of the m-th cultivated land patch in the grid is represented, and n is the total number of the cultivated land patches in the grid;
specifically, firstly, calculating the ratio of each cultivated map spot to the circumscribed rectangular area of each grid in a target area, and accumulating the ratios; and dividing the accumulated value by the total number of the cultivated land patches in the grid to obtain the cultivated land compactness.
S416: the method for calculating the farmland proximity comprises the following specific formulas:
Wherein, Representing the proximity of cultivated land in the ith grid,/>Representing the shortest distance between the kth tilling patch and the nearest neighbor first tilling patch boundary in the ith grid,/>Indicating the number of the tilled areas in the ith grid.
Specifically, first, for each of the tilling areas in the target area grid, the shortest distance between each of the tilling areas and the boundary of the other tilling areas is calculated. And summing the shortest distance of the cultivated land patches in each grid, and then calculating the reciprocal of the average value of the shortest distances of all the cultivated land patches.
S42: and calculating the continuous cropping degree of the cultivated land according to the original index.
In some embodiments, the S42 includes:
s421: carrying out dimensionless treatment on the six original indexes, and obtaining positive index representation and negative index representation of the original indexes:
Wherein, Represents the normalized value of the original index, and if/>If the index is a forward index, the calculation mode is as shown in the formula (1), if/>The index is negative, and the calculation mode is according to the step (2); /(I)Representing the original value of the j index of the i-th grid; /(I)Representing the original index/>Is the maximum value of (2); /(I)Representing the original index/>Is the minimum of (2);
Specifically, 6 original index calculation results of the cultivated land area index, the cultivated land concentration, the cultivated land connectivity, the cultivated land crushing degree, the cultivated land compactness and the cultivated land proximity are subjected to dimensionless treatment by adopting a maximum value and minimum value normalization method, and the original index values are uniformly mapped to between 0 and 1, so that the comparison among the index values used for the subsequent cultivated land continuous calculation is more reasonable and convenient. Wherein 5 indexes of the cultivated land area index, the cultivated land concentration degree, the cultivated land connection degree, the cultivated land proximity degree and the cultivated land compactness degree are positive indexes, and the cultivated land crushing degree is a negative index. The standardized processing methods of the positive and negative indexes are respectively shown in the above formula (1) and the above formula (2).
S422: the original index coefficient is calculated, and the specific calculation formula is as follows:
Wherein, Index value/>, representing the j-th item of the ith gridA ratio of the index value to the sum of the index values of the jth item in all grids in the range of the eighth neighborhood grid set domain of the ith grid; /(I)Representation of e-based calculation/>Natural logarithm of (a); n represents the number of grids in the target area; /(I)A j-th original index coefficient representing an i-th grid;
S423: the standardized weighting value of the original index is calculated, and the specific calculation formula is as follows:
Wherein, Weights representing the original indicators; /(I)A normalized weighting value representing the jth original indicator of the ith mesh;
Specifically, the duty ratio of the jth index value of the ith grid in the target area is calculated Firstly, calculating the sum of j index values in all grids in the range of an eighth neighborhood grid set domain of an i-th grid in a target area, and recording the sum as/>Then, the sum/>, of the j index value of the ith grid and the j index value of all grids in the eight neighborhood grid set domain of the target grid is calculatedIs expressed as/>。
Furthermore, e is taken as the baseIs expressed as/>Next, calculate/>And/>Is expressed as/>. Then, for all grids/>Summing to obtain/>And is denoted as R. Next, calculating the inverse number of the reciprocal of the natural logarithm of the grid number in the target area, and recording as k; finally, the product of R and k is calculated and recorded as/>The j-th original index coefficient of the i-th mesh is represented.
Further, a score index weight value representing the continuous cropping degree is calculated. First, calculateAnd/>Difference/>Then, calculate its cumulative sum/>. Finally, by/>And/>The ratio of (2) calculates the weight/>, of the original index。
Further, a normalized weighting value of the index representing the continuous cropping is calculated. First, calculateAnd by the difference and/>Multiplying to obtain 6 original index standardized weighted values/>, which represent continuous sheet degree of cultivated land. Then, the maximum value and the minimum value of each index standardization weighted value are calculated respectively and marked as/>, respectively、/>。
S424: the continuous farmland degree is calculated, and the specific calculation formula is as follows:
Wherein, Representing an optimal solution closeness value of the ith grid; /(I)Representing the worst approach value of the ith mesh; /(I)Representing a forward ideal state value; /(I)Representing a negative ideal state value; /(I)Representing the continuous farmland degree of the ith grid.
Specifically, an optimal solution and a worst solution of the standardized weighting values of the 6 index marks representing the continuous cropping degree are determined. First, 4 original indexes of the cultivated land area index, the cultivated land concentration, the cultivated land connectivity and the cultivated land proximity are used as the maximum value of the forward indexesAnd 2 original indexes of the crushing degree of the cultivated land and the compactness degree of the cultivated land are used as minimum values of negative indexesDefined as the forward ideal state value, i.e. the optimal solution, denoted/>.5 Original indexes of the cultivated land area index, the cultivated land concentration degree, the cultivated land connectivity degree, the cultivated land proximity degree and the cultivated land compactness degree are used as the minimum value/>And maximum value/>, using cultivated land crushing degree as negative indexDefined as the negative ideal value, i.e. the worst solution, denoted/>。
And further, calculating the optimal solution close value and the worst solution close value of each grid-cultivated land continuous degree in the target area according to the 6 index standardized weighted values and the optimal solution and the worst solution. Firstly, normalizing weighted values of an optimal solution and each index, calculating the square sum of differences of the optimal solution and the weighted values of each index, and then opening square root to obtain an optimal solution close value of the comprehensive value of each index of each grid in a target area; similarly, based on the worst solution and the standardized weighted value of each index, calculating the sum of squares of the difference between the worst solution and the weighted value of each index, and then opening the square root to obtain the worst solution close value of the comprehensive value of each index of each grid in the target area.
And calculating the sum of the optimal close value and the worst close value of each index integrated value of each grid in the target area, and finally obtaining the cultivated land connection degree of each grid in the target area through the ratio of the worst close value and the sum of the optimal close value and the worst close value of the target area.
The second aspect of the present invention also provides a system for calculating the continuous cropping of a farmland in consideration of adaptive neighborhood, comprising:
the data acquisition module is used for acquiring the vector data of the cultivated map spots and preprocessing the vector data of the cultivated map spots;
The patch aggregation module is used for initially aggregating the cultivated land patches according to the adjacent relation between the cultivated land and the characteristic elements and according to different neighborhood radiuses;
The scale determining module is used for creating a cultivated land grid, iteratively creating a cultivated land self-adaptive multi-scale grid according to the area ratio of the cultivated land subset to the cultivated land complement in the grid, and determining an optimal scale cultivated land grid;
and the connection degree calculation module is used for calculating the connection degree of the cultivated land in the grid according to the established optimal-scale cultivated land grid.
The third aspect of the present invention also provides a computer comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the computing method as claimed in any one of the preceding claims when executing the computer program.
The fourth aspect of the present invention also provides a readable storage medium having stored thereon a computer program, characterized in that the program, when executed by a processor, implements a computing method as described in any of the above.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
In the embodiments provided in the present disclosure, it should be understood that the disclosed apparatus/computer device and method may be implemented in other manners. For example, the apparatus/computer device embodiments described above are merely illustrative, e.g., the division of modules or elements is merely a logical functional division, and there may be additional divisions of actual implementations, multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present disclosure may implement all or part of the flow of the method of the above-described embodiments, or may be implemented by a computer program to instruct related hardware, and the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of the method embodiments described above. The computer program may comprise computer program code, which may be in source code form, object code form, executable file or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the jurisdiction's jurisdiction and the patent practice, for example, in some jurisdictions, the computer readable medium does not include electrical carrier signals and telecommunication signals according to the jurisdiction and the patent practice.
Those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the application and form different embodiments.
Those skilled in the art will appreciate that the descriptions of the various embodiments are each focused on, and that portions of one embodiment that are not described in detail may be referred to as related descriptions of other embodiments.
Although the embodiments of the present application have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and alterations without departing from the spirit and scope of the present application, and such modifications and alterations fall within the scope of the appended claims, which are to be construed as merely illustrative of the present application, but the scope of the application is not limited thereto, and various equivalent modifications and substitutions will be readily apparent to those skilled in the art within the scope of the present application, and are intended to be included within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
The present invention is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and these modifications and substitutions are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (9)
1. The farmland continuous degree calculation method considering the self-adaptive neighborhood is characterized by comprising the following steps of:
S1: acquiring the vector data of the cultivated map spots, and preprocessing the vector data of the cultivated map spots;
s2: performing initial aggregation on the cultivated land patches according to the adjacent relation between the cultivated land and the characteristic elements and according to different neighborhood radiuses;
The step S2 comprises the following steps:
S21: calculating the characteristic element patch widths among the farmland patches in the target area, and calculating the average value of all the characteristic element patch widths;
S22: taking the minimum width of all the characteristic element patches as an initial aggregation value, initially aggregating the cultivated land patches, adding one meter to the initial aggregation value according to each iteration, and iteratively aggregating the cultivated land patches; counting the total number of cultivated land patches after each polymerization;
S23: based on the number of the cultivated land patches before and after the aggregation, calculating the relative error of the cultivated land patches before and after the aggregation, calculating the average value of the relative error, converging the relative error according to an upward rounding principle, and selecting an aggregation threshold value, with the relative error closest to the average value of the relative error, as an optimal aggregation radius;
s24: aggregating the cultivated land patches according to the optimal aggregation radius, intersecting and inverting the cultivated land patches with the original cultivated land patches, extracting image patch data exceeding the range of the original cultivated land patches after aggregation, and erasing the cultivated land patch vector data formed by aggregation to obtain final cultivated land patch aggregation vector data;
s3: creating a cultivated land grid, iteratively creating a cultivated land self-adaptive multi-scale grid according to the area ratio of the cultivated land subset to the cultivated land complement in the grid, and determining an optimal scale cultivated land grid;
s4: and calculating the continuous farmland degree in the grid according to the established optimal-scale farmland grid.
2. The method for calculating the continuous tillage degree by considering the adaptive neighborhood according to claim 1, wherein the step S1 comprises:
s11: land utilization vector data based on homeland investigation data comprises three subclasses of dry land, paddy field and watered land;
S12: space merging is carried out on adjacent dry lands, paddy fields and watered land patches, and a new cultivated land patch aggregation layer is generated;
S13: each cultivated land patch area is calculated.
3. The method for calculating the continuous tillage degree by considering the adaptive neighborhood according to claim 1, wherein the step S3 comprises:
s31: establishing a grid maximum scale of the cultivated land patches of the target area by taking four points of the circumscribed enveloping rectangular frame of all the cultivated land patches in the target area as references;
s32: and determining the optimal scale of each cultivated land patch corresponding to the grid based on the ratio of the cultivated land area occupied ratio in the grid to the cultivated land complement area occupied ratio in the grid.
4. The method for calculating the continuous tillage degree by considering the adaptive neighborhood according to claim 1, wherein the step S4 comprises:
s41: according to the established optimal-scale cultivated land grid, calculating original indexes of the cultivated land continuous sheet degree in the grid, wherein the original indexes comprise cultivated land area indexes, cultivated land gathering degree, cultivated land connecting degree, cultivated land crushing degree, cultivated land compactness and cultivated land proximity;
s42: and calculating the continuous cropping degree of the cultivated land according to the original index.
5. The method for computing the continuous cropping of a farmland in consideration of adaptive neighborhood according to claim 4, wherein said S41 comprises:
S411: calculating an index of the cultivated land area, wherein the specific formula is as follows:
Wherein/> Representing the cultivated area index of the ith grid,/>Representing the cultivated land area of the ith grid, and S represents the total cultivated land area in the eight neighborhood grid set domain;
s412: the farmland gathering degree is calculated, and the specific formula is as follows:
Wherein/> Representing the cultivated land concentration of the ith grid,/>Representing the area of the grid l plowing plaque,/>Representing the area of the grid k farmland plague,/>Representing the average value of all plowing plaque areas in the range of the grid set domain of the eight neighborhood grids of grid l and grid k,/>The element value of the spatial weight matrix of the cultivated land is represented by n, which is the grid number;
s413: the cultivated land connectivity is calculated, and the specific formula is as follows:
Wherein/> For the cultivated land connectivity of the ith grid,/>For the area of the cultivated land patch I,/>The area of the cultivated land patch k is n is the total number of cultivated land patches in the grid, and S is the total area of cultivated lands in the grid;
s414: the cultivated land crushing degree is calculated, and the specific formula is as follows:
Wherein/> Representing the cultivated land breaking degree of the ith grid,/>Representing the number of plowing patches in the ith grid,/>Representing the total area of cultivated land in the ith grid;
S415: the cultivated land compactness is calculated, and the specific formula is as follows:
Wherein/> Representing the compactness of the cultivated land in the ith grid,/>Representing the area of the mth tilling area in the grid,/>The external rectangular area of the m-th cultivated land patch in the grid is represented, and n is the total number of the cultivated land patches in the grid;
s416: the method for calculating the farmland proximity comprises the following specific formulas:
Wherein/> Representing the proximity of cultivated land in the ith grid,/>The shortest distance between the kth cultivated land patch and the nearest first cultivated land patch boundary in the ith grid is represented, n is the total number of cultivated land patches in the grid, and k, l and m represent the sequence numbers of the selected cultivated land patches.
6. The method for computing the continuous cropping of a farmland in consideration of adaptive neighborhood according to claim 5, wherein said S42 comprises:
s421: carrying out dimensionless treatment on the six original indexes, and obtaining positive index representation and negative index representation of the original indexes:
Wherein/> Represents the normalized value of the original index, and if/>If the index is a forward index, the calculation mode is as shown in the formula (1), if/>The index is negative, and the calculation mode is according to the step (2); /(I)Representing the original value of the j index of the i-th grid; /(I)Representing the original index/>Is the maximum value of (2); /(I)Representing the original index/>Is the minimum of (2);
s422: the original index coefficient is calculated, and the specific calculation formula is as follows:
Wherein/> Index value representing jth item of ith gridA ratio of the index value to the sum of the index values of the jth item in all grids in the range of the eighth neighborhood grid set domain of the ith grid; /(I)Representation of e-based calculation/>Natural logarithm of (a); n represents the number of grids in the target area; /(I)A j-th original index coefficient representing an i-th grid;
S423: the standardized weighting value of the original index is calculated, and the specific calculation formula is as follows:
Wherein/> Weights representing the original indicators; /(I)A normalized weighting value representing the jth original indicator of the ith mesh;
s424: the continuous farmland degree is calculated, and the specific calculation formula is as follows:
Wherein, Representing an optimal solution closeness value of the ith grid; /(I)Representing the worst approach value of the ith mesh; /(I)Representing a forward ideal state value; /(I)Representing a negative ideal state value; /(I)Representing the continuous farmland degree of the ith grid.
7. A tilling area connectivity calculation system that considers an adaptive neighborhood, comprising:
the data acquisition module is used for acquiring the vector data of the cultivated map spots and preprocessing the vector data of the cultivated map spots;
The patch aggregation module is used for initially aggregating the cultivated land patches according to the adjacent relation between the cultivated land and the characteristic elements and according to different neighborhood radiuses;
The plaque aggregation module includes:
The characteristic calculation sub-module is used for calculating characteristic element patch widths among the farmland patches in the target area and calculating an average value of all the characteristic element patch widths;
The iterative aggregation sub-module is used for performing initial aggregation on the cultivated land patches by taking the minimum width in all the characteristic element patches as an aggregation initial value, adding one meter to the aggregation initial value according to each iteration, and performing iterative aggregation on the cultivated land patches; counting the total number of cultivated land patches after each polymerization;
The error convergence sub-module is used for calculating the relative error of the cultivated land plaque numbers before and after the aggregation based on the cultivated land plaque numbers before and after the aggregation, calculating the average value of the relative error, converging the relative error according to an upward rounding principle, and selecting an aggregation threshold value, with the relative error closest to the average value of the relative error, as an optimal aggregation radius;
The intersecting and inverting submodule is used for aggregating the cultivated land patch according to the optimal aggregation radius, intersecting and inverting the cultivated land patch with the original cultivated land patch, extracting image patch data exceeding the original cultivated land patch range after aggregation, and erasing the cultivated land patch vector data formed by aggregation to obtain final cultivated land patch aggregation vector data;
The scale determining module is used for creating a cultivated land grid, iteratively creating a cultivated land self-adaptive multi-scale grid according to the area ratio of the cultivated land subset to the cultivated land complement in the grid, and determining an optimal scale cultivated land grid;
and the connection degree calculation module is used for calculating the connection degree of the cultivated land in the grid according to the established optimal-scale cultivated land grid.
8. A computer comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the computing method of any of claims 1-6 when the computer program is executed.
9. A readable storage medium having stored thereon a computer program which, when executed by a processor, implements the computing method of any of claims 1-6.
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