Supplementary cultivated land space site selection method suitable for southwest mountainous area

Abstract

The invention relates to the technical field of land analysis, and discloses a supplementary cultivated land space site selection method suitable for southwest mountainous areas, comprising the following steps: constructing an intelligent site selection module group based on ArcGIS software, and performing supplementary cultivated land space site selection by the intelligent site selection module group; the intelligent site selection module group comprises a management adaptability analysis module used for extracting a first potential pattern spot meeting a management requirement; the occupation and compensation demand analysis module is used for obtaining a second potential pattern spot assigned with an occupation and compensation balance demand; the cultivation condition analysis module is used for acquiring third to fifth potential pattern spots of assigned cultivated land concentration contiguous degree, residential area proximity and water source proximity; the renovation cost analysis module is used for acquiring sixth to eighth potential pattern spots of the assignment gradient, the road accessibility and the renovation difficulty; and the space site selection analysis module is used for summarizing and calculating potential pattern spot scoring results of the target area. According to the method, an effective quantitative evaluation result can be provided for regional cultivated land occupation and supplement balance work.

Description

Technical Field

[0001] The present invention relates to the technical field of land analysis, and in particular to a spatial site selection method for supplementary cultivated land applicable to southwestern mountainous areas. Background Art

[0002] In order to implement the most stringent farmland protection system and firmly hold the red line of farmland protection, the Ministry of Natural Resources and the Ministry of Agriculture and Rural Affairs issued a document to establish a new mechanism of balance between occupation and compensation with the dynamic balance of the total amount of provincial farmland as the core. The implementation of this policy marks that my country has entered a new stage in farmland protection, emphasizing that under the premise of complying with the requirements of national land space planning and ecological and environmental protection, effective management measures should be taken to ensure that the amount of farmland does not decrease and the quality does not decrease. In this context, all types of non-farmland in the results of land change surveys can be used as a source of supplementary farmland, which provides a policy basis for local governments to flexibly adjust land use according to actual conditions.

[0003] At present, GIS analysis technology is widely used in the field of cultivated land management. The tools under the ArcGIS platform can provide more convenient data analysis technology support for cultivated land analysis. However, the application of the ArcGIS platform in existing technologies still remains at the level of relatively superficial single-function applications, which makes it difficult to directly match new policy needs and the needs of cultivated land analysis in special and complex areas. In addition, although there are a few cutting-edge technologies that have systematically developed cultivated land analysis technologies based on ArcGIS, there are still many defects that need to be improved. Taking the patent with publication number CN117952435A as an example, the patent discloses a method for evaluating the potential for cultivated land restoration, which can use ArcGIS to conduct cultivated land evaluation from multiple aspects. Although it has improved the application effect of ArcGIS to a certain extent, the following problems still exist:

[0004] 1. The analysis has low reference value. Without the premise of national land space planning and ecological environmental protection requirements, the evaluation results will conflict with policy management requirements, making the evaluation results ineffective or even misleading. The evaluation results based on this technology may lead to improper behaviors such as "deforestation and land reclamation" and "immediate construction after restoration".

[0005] 2. Large analysis errors. The data of indicators such as "restoration cost" and "public willingness" in this technology are derived from field surveys. The survey sampling method and sample size have a great impact on the evaluation results. In addition, the large variability of field survey results will also lead to deviations in the evaluation results.

[0006] 3. The necessity of development is seriously insufficient. Many indicators in this technology are derived from field surveys. If, based on extensive field surveys, the overall situation of the restoration potential of cultivated land in the target area can be investigated and whether rectification and restoration can be carried out, there is no need to conduct data analysis based on this survey. If it is based on a sampling field survey, it is very likely to be affected by subjective factors, and the generated data results will be highly unpredictable and difficult to use for actual reference.

[0007] 4. Poor applicability, and basically not feasible in the southwestern mountainous areas. For example, in the southwestern mountainous areas where mechanized agricultural production is relatively uncommon and the level of mechanization is relatively low, the proximity of roads (referring to rural roads, highways, etc., excluding narrow mechanized farming roads and field roads) is not the main factor affecting the conditions of cultivated land. In contrast, the engineering equipment required for the rectification and restoration of cultivated land requires road facilities. Therefore, the distance from the road to supplement the potential of cultivated land has a greater impact on the cost of transferring engineering equipment and opening roads, that is, the cost of rectification.

[0008] 5. Low operating efficiency. This technology integrates the use of various tools and operating steps in terms of technical thinking, but has not formed more efficient secondary development results. The specific operating steps are still mechanically processed and analyzed step by step, which has low work efficiency and does not provide a more efficient and convenient implementation method to achieve the purpose of the invention.

[0009] In summary, there is still an urgent need for a more reliable and efficient method for supplementary cultivated land spatial site selection that can match new policy demands and the needs of cultivated land analysis in special and complex areas. Summary of the invention

[0010] The present invention aims to provide a method for selecting the spatial location of supplementary cultivated land applicable to the mountainous areas in the southwest. It can quantitatively analyze the feasibility of rectification of non-cultivated agricultural land use areas through computer language, scientifically determine the spatial location of supplementary cultivated land and the timing of rectification and restoration, and provide effective quantitative evaluation results for the regional cultivated land occupation and compensation balance work.

[0011] The basic scheme provided by the present invention is: a method for spatial site selection of supplementary cultivated land applicable to the southwestern mountainous areas, comprising the following steps: constructing an intelligent site selection module group based on ArcGIS software, and performing spatial site selection of supplementary cultivated land by the intelligent site selection module group;

[0012] The intelligent site selection module group includes a management adaptability analysis module, an occupation and compensation demand analysis module, a farming condition analysis module, a remediation cost analysis module and a spatial site selection analysis module;

[0013] The management adaptability analysis module is used to extract the non-cultivated agricultural map patches in the target area and pre-process them to obtain the first potential map patches that meet the management requirements;

[0014] The occupation and compensation demand analysis module is used to calculate the type of administrative village to which the target area belongs, and based on the type of administrative village and its corresponding annual change survey data, mark the first potential map spot to obtain the second potential map spot with the assigned occupation and compensation balance demand;

[0015] The farming condition analysis module is used to calculate the concentration and continuity of cultivated land through aggregation surface analysis based on the annual change survey data, and calculate the proximity of residential points and water sources through neighbor analysis to obtain the third potential map assigned to the concentration and continuity of cultivated land, the fourth potential map assigned to the proximity of residential points, and the fifth potential map assigned to the proximity of water sources;

[0016] The remediation cost analysis module is used to obtain the sixth potential map of assigned slope through slope measurement and spatial connection based on the annual change survey data; calculate road accessibility through neighbor analysis to obtain the seventh potential map of assigned road accessibility; and obtain the eighth potential map of assigned rectification difficulty through rectification difficulty rule screening;

[0017] The spatial site selection analysis module is used to set a spatial site selection evaluation index system and index weights applicable to the southwestern mountainous areas for supplementary cultivated land, and based on the first potential spot, the second potential spot, the third potential spot, the fourth potential spot, the fifth potential spot, the sixth potential spot, the seventh potential spot and the eighth potential spot, summarize and calculate the potential spot scoring results of the target area.

[0018] The working principle and advantages of the present invention are:

[0019] The present invention is a method for selecting the spatial location of supplementary cultivated land applicable to the mountainous areas in the southwest. It uses the non-cultivated agricultural land in the land change survey results as the evaluation unit. On the premise of meeting the requirements of land space planning and ecological environmental protection, it uses computer language to quantitatively analyze the feasibility of rectification and restoration of the land from three aspects: the demand for occupation and compensation balance, farming conditions, and the cost of rectification and restoration. It can determine the priority of supplementary cultivated land space and rectification and restoration, form the evaluation results of supplementary cultivated land space, and provide scientific and effective location guidance for the implementation of cultivated land rectification and restoration work in the region under the new mechanism of cultivated land occupation and compensation balance. In particular:

[0020] First, this plan can achieve accurate assessment of supplementary arable land resources and has strong applicability.

[0021] In terms of the demand for compensation, the changes in cultivated land in different villages were taken into consideration, and the demand scores for the supplementary cultivated land plots were reasonably conducted, which helped to determine the priority of supplementary cultivated land according to actual needs. In terms of farming conditions, the analysis of the concentration and continuity of cultivated land, the proximity of settlements and the proximity of water sources made it possible to accurately judge the suitability of farming for each plot. The remediation cost analysis started from the perspectives of slope, road accessibility and difficulty of rectification, and adopted quantitative indicators to accurately evaluate the remediation costs, eliminating the interference of subjective opinions in the on-site survey questionnaire on the evaluation results, and providing decision makers with an objective basis for the cost required for the remediation of each plot. In addition, this plan takes the plot as the basic unit, which is more feasible to implement.

[0022] Second, this scheme can realize efficient and intelligent spatial site selection analysis for supplementary cultivated land.

[0023] This solution realizes the deep integration of GIS technology in the assessment of the potential of supplementary cultivated land, and fully taps the huge potential of geographic information system (GIS) in the field of assessment of the potential of supplementary cultivated land. The constructed intelligent site selection module group is obtained through secondary development based on the ArcGIS platform. The model builder is used to deeply integrate the tools, and the preset operation logic code is used to turn the traditional step-by-step operation and manual processing into one-click import and one-step generation, realizing the efficient management and in-depth analysis of a large amount of spatial data, greatly improving the accuracy and efficiency of the assessment of the potential of supplementary cultivated land.

[0024] Third, the analysis results of this scheme are highly reliable, have high reference value, and have high development and application value.

[0025] The data sources used in this scheme are accurate, all legal data are used, and no survey or interview results of any form are involved. It can avoid the influence of human random factors on the evaluation and analysis results to the greatest extent, and provide decision makers with more accurate references for map site selection under the premise of reducing the workload in the early stage. Moreover, more importantly, this scheme combines the new mechanism of balance between cultivated land occupation and compensation, and innovatively takes compliance with national land space planning and ecological environmental protection requirements as a prerequisite for the analysis of supplementary cultivated land potential maps, so that it is consistent with the current national land space planning and ecological environmental protection policies, reflecting the exploration of the long-term utilization of cultivated land, and avoiding the problem of conflicts with policies and regulations when the implementing subject refers to the evaluation and analysis results of the present invention to carry out specific work, and has high development and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of a method flow of an embodiment of a method for selecting a supplementary cultivated land space applicable to a southwestern mountainous area of ​​the present invention;

[0027] Figure 2A schematic diagram of an intelligent site selection module group of an embodiment of a method for selecting a site for supplementary cultivated land in a southwestern mountainous area according to the present invention;

[0028] Figure 3 A schematic diagram of the operation logic of the management adaptability analysis module of an embodiment of a method for selecting a supplementary cultivated land space in a southwestern mountainous area according to the present invention;

[0029] Figure 4 It is a schematic diagram of the operation logic of the occupation and compensation demand analysis module of an embodiment of a method for selecting a spatial location for supplementary cultivated land applicable to the southwestern mountainous area of ​​the present invention;

[0030] Figure 5 A schematic diagram of the operation logic of a farming condition analysis module of an embodiment of a method for selecting a supplementary cultivated land space in a southwestern mountainous area according to the present invention;

[0031] Figure 6 It is a schematic diagram of the operation logic of the remediation cost analysis module of an embodiment of the method for selecting a supplementary cultivated land space in the southwestern mountainous area of ​​the present invention;

[0032] Figure 7 A schematic diagram of the operation logic of a spatial site selection analysis module of an embodiment of a method for spatial site selection of supplementary cultivated land applicable to mountainous areas in the southwest of the present invention;

[0033] Figure 8 It is a schematic diagram of a database of spatial potential spots of supplementary cultivated land according to an embodiment of a method for selecting a spatial location for supplementary cultivated land applicable to mountainous areas in the southwest of the country;

[0034] Fig. 9 This is a schematic diagram of the application of an intelligent site selection module group in an embodiment of a method for spatial site selection of supplementary cultivated land applicable to southwestern mountainous areas of the present invention. DETAILED DESCRIPTION

[0035] The following is a further detailed description through specific implementation methods:

[0036] The embodiment is basically as shown in the attached Figure 1 As shown: A method for spatial site selection of supplementary cultivated land applicable to mountainous areas in the southwest, comprising the following steps: constructing an intelligent site selection module group based on ArcGIS software, and using the intelligent site selection module group to perform spatial site selection of supplementary cultivated land;

[0037] The intelligent site selection module group includes a data extraction module, a management adaptability analysis module, an occupation and compensation demand analysis module, a farming condition analysis module, a remediation cost analysis module and a spatial site selection analysis module. Figure 2 shown.

[0038] In this embodiment, the operating logics of the data extraction module, management adaptability analysis module, occupation and compensation demand analysis module, farming condition analysis module, remediation cost analysis module and spatial site selection analysis module are prepared as corresponding pre-operation logic codes, and are set through Python scripts and built into the modules to facilitate the intelligent operation logic execution and tool calling of ArcGIS software.

[0039] The data extraction module is used to obtain annual change survey data and association analysis data.

[0040] In this embodiment, the annual change survey data includes the 2020 land change survey data of the target area (corresponding to the subsequent historical annual change survey data) and the latest annual land change survey data (corresponding to the subsequent latest annual change survey data). The association analysis data includes the DEM digital elevation data corresponding to the target area, the "three zones and three lines" demarcation results, the national land space planning results, the land acquisition database, the forestry special data, the river and lake area range data, the drinking water source first-level protection area range data, etc.

[0041] Among them, the historical annual change survey data is fixed to 2020. In actual application, the latest annual change survey data should use the current latest annual land change survey data. The latest annual change survey data used in the analysis in this example is the 2022 land change survey data.

[0042] like Figure 3 As shown, the management adaptability analysis module is used to extract the non-cultivation agricultural map spots in the target area and pre-process them to obtain the first potential map spots that meet the management requirements. The pre-processing includes merging, erasing, and breaking up the non-cultivation agricultural map spots.

[0043] Specifically, the management adaptability analysis module establishes a call link with the analysis tools, spatial analysis tools and data management tools of ArcGIS software; the management adaptability analysis module includes the following operation logic:

[0044] Step 1. Based on the annual change survey data, call the Spatial Analyst Tools, and based on the Extract By Attributes and Copy Features tools, select the non-agricultural land and management feature data in the land type map (DLTB) layer of the latest annual change survey data.

[0045] Specifically, in this embodiment, the management element data include the ecological protection red line in the "three zones and three lines" demarcation results, as well as the urban development boundary, land acquisition database, construction land in the planned land and sea (GHYDYH) layer of the national land space planning results, river and lake area, forestry special data, and first-level drinking water source protection zone.

[0046] Step 2, call the Data Management Tools, and based on the Dissolve tool, fuse the extracted non-agricultural land according to the land class name (DLMC) field to form a non-agricultural land base map; based on the Merge tool, merge the extracted management element data into one layer and form a management element collection.

[0047] Step 3, call the analysis tool (Analysis Tools), based on the erase tool (Erase), use the management element collection as the erasing element, erase the non-cultivated agricultural land base map patches, and form the target non-cultivated agricultural land base map patches that meet the management requirements.

[0048] Step 4, call the Data Management Tools, based on the Multipart To Singlepart tool and the Add Field tool, break up the target non-cultivated agricultural land base map into single parts, and add the Area field to it. The field type is double precision (DOUBLE), and calculate the geometric area of ​​each single part based on the field. The area unit is square meters to form a single part map (corresponding to the non-cultivated agricultural land base map_single part that meets the management requirements).

[0049] Step 5, call the Spatial Analyst Tools, based on the Extract By Attributes tool and the Copy Features tool, extract the spots with Area field values ​​greater than 400 in the single-component spots to form the first potential spots that meet management needs.

[0050] like Figure 4 As shown, the occupation and compensation demand analysis module is used to calculate the administrative village type to which the target area belongs, and based on the administrative village type and its corresponding annual change survey data, the first potential map is marked to obtain the second potential map with the assigned occupation and compensation balance demand.

[0051] Among them, the types of administrative villages include long-term utilization type, consolidation and protection type, gradual recovery type, and key remediation type.

[0052] The compensation demand analysis module establishes a call link with the analysis tools, spatial analysis tools and data management tools of ArcGIS software; the compensation demand analysis module includes the following operation logic:

[0053] Step 1, based on the annual change survey data, call the Spatial Analyst Tools, and use the Extract By Attributes and Copy Features tools to select the historical cultivated land in the DLTB layer of the historical annual change survey data, and select the latest cultivated land and village survey area (CJDCQ) layer in the DLTB layer of the latest annual change survey data;

[0054] Step 2, call the Analyst Tools, based on the Identity tool, use the village survey area (CJDCQ) as the identification element, mark the historical cultivated land and the latest cultivated land respectively, and obtain the historical cultivated land map spots marked with the village survey area (CJDCQ) and the latest cultivated land map spots marked with the village survey area;

[0055] Then, based on the summary statistics tool (Statistics), with the map land type area (TBDLMJ) as the statistical field, summary (SUM) as the statistical type, and the location unit name as the case grouping field, the historical cultivated land patches and the latest cultivated land patches were summarized and statistically analyzed respectively, and the statistical table of cultivated land by village based on the historical change survey data and the statistical table of cultivated land by village based on the latest change survey data were obtained.

[0056] Step 3, call the Data Management Tools, based on the Join Field tool, use the historical change survey data cultivated land village statistics table and the latest change survey data cultivated land village statistics table as the connection table, connect the cultivated land area statistics to the village survey area, and obtain the village survey area with cultivated land area (corresponding to the latest annual change survey data village survey area_attached with two years of cultivated land area).

[0057] Then, based on the Add Field tool, add the area change quantity (MJBHSL) and area change ratio fields (MJBHBL) for the village survey area, with the field type of double precision (DOUBLE), and add the field of occupation and compensation balance change type (ZBPHBHLX), with the field type of text (TEXT). And based on the Calculate Field tool (CalculateField), calculate the area change quantity and area change ratio based on the field, and the calculation expression is as follows:

[0058] MJBHSL = TBDLMJ1-TBDLMJ2;

[0059] MJBHBL=(TBDLMJ1-TBDLMJ2) / TBDLMJ2;

[0060] Among them, TBDLMJ1 is the cultivated land area according to the latest annual changed survey data, and TBDLMJ2 is the cultivated land area according to the changed survey data in 2020.

[0061] Then, based on the Calculate Field tool, according to the area change quantity and area change ratio, according to the preset standard - according to the quantity change ±100 mu or the change ratio ±5%, the administrative villages are divided into long-term utilization type, consolidation protection type, gradual recovery type, and key remediation type. Then, the administrative village type to which the target area belongs is calculated, and the latest village survey area layer is obtained;

[0062] Step 4, call the analysis tool (Analyst Tools), based on the identification tool (Identity) therein, use the latest village-level survey area layer as the identification element to identify the first potential map spot, and obtain the second potential map spot with the assigned occupation and compensation balance demand.

[0063] like Figure 5 As shown, the farming condition analysis module is used to calculate the concentration and continuity of cultivated land through aggregation surface analysis based on annual change survey data, and calculate the proximity of residential points and water sources through neighbor analysis to obtain the third potential map assigned with the concentration and continuity of cultivated land, the fourth potential map assigned with the proximity of residential points, and the fifth potential map assigned with the proximity of water sources.

[0064] The farming condition analysis module establishes a call link with the mapping tool, analysis tool, spatial analysis tool and data management tool of ArcGIS software; the farming condition analysis module includes the following operation logic:

[0065] Step 1. Based on the annual change survey data, call the Spatial Analyst Tools, and based on the Extract By Attributes and Copy Features tools, select the cultivated land, rural homestead and land water patches in the land type patch (DLTB) layer of the annual change survey data.

[0066] Step 2, call the data management tool (Data Management Tools), and based on the merge tool (Merge) therein, merge the first potential map and the cultivated land into a merged map (corresponding to "merge of cultivated land and supplementary cultivated land potential").

[0067] Step 3, call the Cartography Tools, based on the AggregatePolygons tool, set the aggregation distance to 8m, aggregate the merged spots to form an aggregation result.

[0068] Step 4, call the Data Management Tools, and based on the Add Field tool (Add Field), add the aggregated area (Area_JH) and concentrated connectivity (JZLPD) fields in the aggregation results, where the field type of the aggregated area is double precision (DOUBLE), and the field type of the concentrated connectivity is text (TEXT); and calculate the aggregated area (in square meters) and concentrated connectivity based on the fields.

[0069] Specifically, using the Calculate Field tool of the Data Management Tools, based on the aggregation results, the villages were divided into areas of less than 5 mu, 5 to 20 mu, 20 to 50 mu, and more than 50 mu according to the standards of 5 / 20 / 50 mu.

[0070] Step 5, call the analysis tool (Analyst Tools), based on the identification tool (Identity) therein, use the aggregation results as the identification factor to identify the first potential map, and obtain the third potential map with the assigned cultivated land concentration and continuity.

[0071] Step 6, call the analysis tool (Analyst Tools), based on the neighbor analysis tool (Near), take the rural homestead as the neighboring element, calculate the straight-line distance between the first potential spot and the nearest rural homestead, and form the first potential spot_homestead distance.

[0072] Step 7, call the Data Management Tools, and use the Add Field tool to add a field - Settlement Distance (JMDJL) in the first potential map_Homestead Distance, with the field type of text (TEXT); and use the Calculate Field tool to calculate the Settlement Distance (JMDJL), and assign values ​​of within 50 meters, beyond 50 meters, within 100 meters, beyond 100 meters, within 200 meters, and beyond 200 meters to the Settlement Distance (JMDJL) field according to the 50 / 100 / 200 meter classification reference index table, respectively, to obtain the fourth potential map with assigned settlement proximity.

[0073] Step 8, call the analysis tool (Analyst Tools), based on the neighbor analysis tool (Near), take the land water patch as the neighboring element, calculate the straight-line distance from the first potential patch to the nearest land water, and form the first potential patch_water source distance.

[0074] Step 9, call the Data Management Tools, and based on the Add Field tool, add a field - Water Source Distance (SYJL) in the first potential map_Water Source Distance, and the field type is text (TEXT); and based on the Calculate Field tool, calculate the water source distance, and assign values ​​of within 50 meters, beyond 50 meters, within 100 meters, beyond 100 meters, within 200 meters, and beyond 200 meters in the field Water Source Distance (SYJL) according to the 50 / 100 / 200 meter classification reference index table, respectively, to obtain the fifth potential map with assigned water source proximity.

[0075] like Figure 6 As shown, the remediation cost analysis module is used to obtain the sixth potential map of assigned slope through slope measurement and spatial connection based on the annual change survey data; calculate the road accessibility through neighbor analysis to obtain the seventh potential map of assigned road accessibility; and obtain the eighth potential map of assigned rectification difficulty through rectification difficulty rule screening.

[0076] The remediation cost analysis module establishes a call link with the conversion tool, analysis tool, spatial analysis tool and data management tool of ArcGIS software; the remediation cost analysis module includes the following operation logic:

[0077] Step 1, based on the DEM digital elevation data of the target area, call the spatial analysis tool (Spatial Analyst Tools), based on the slope tool (Slope), measure the slope of each raster pixel in the DEM digital elevation data, and form a raster slope map; then based on the reclassification tool (Reclassify), take the slope field (Value) of the raster slope map as the reclassification field, according to the old value 0-2 is assigned to the new value 1, the old value 2-6 is assigned to the new value 2, the old value 6-15 is assigned to the new value 3, the old value 15-25 is assigned to the new value 4, and the old value above 25 is assigned to the new value 5. The raster slope map of the target area is reclassified to obtain the raster slope map_reclassification;

[0078] Step 2, call the Conversion Tools, and based on the Raster To Polygon tool, reclassify the raster slope map into a vector slope map.

[0079] Step 3, call the data management tool, based on the Add Field tool (Add Field) and the Calculate Field tool (Calculate Field), add a field on the first potential map - unique FID (WY_FID), the field type is text (TEXT), and the calculated field value is OBJECTID.

[0080] Step 4, calling the analysis tool, based on the identification tool (Identity) therein, using the vector slope map as the identification element, identifies the first potential map spot, and obtains the first potential map spot with the slope marked.

[0081] Step 5, call the data management tool, based on the sorting tool and the delete identical item tool (DeleteIdentical), sort the Shape_area field of the first potential map with marked slope in descending order (DESCENDING), and delete the identical items based on the unique FID field, so that the first potential map with marked slope only retains the slope value with the largest area ratio of each unique map, which is regarded as the slope value of each unique map.

[0082] Then, based on the spatial join tool (Spatial Join), the first potential spot with marked slope is taken as the connecting element, the first potential spot is taken as the target element, the connection operation is JION_ONE_TO_ONE, the matching option is CONTAINS, and the slope values ​​of each unique spot are connected to the first potential spot to obtain the sixth potential spot with assigned slope.

[0083] Here, after marking the slope, each first potential spot may be assigned multiple values ​​of 1 / 2 / 3 / 4 / 5. By sorting the Shape_area field in descending order and deleting the same items with the unique FID field, the spot with the largest area can be retained, and the slope value of this spot is regarded as the slope value of the original spot.

[0084] For example, after marking the slope, map spot A (FID field value is 1, slope value 3, area 50 square meters), map spot C (FID field value is 1, slope value 4, area 30 square meters), and map spot D (FID field value is 1, slope value 5, area 20 square meters) are divided into three maps. After sorting and deleting the same items, only map spot B (FID field value is 1, slope value 3, area 50 square meters) will be retained. Then, using the FID field value as the connection identification field, map spot A will be assigned a slope value of 3, and the sixth potential map spot with assigned slope will be obtained.

[0085] Step 6. Based on the annual change survey data, call the spatial analysis tool, and based on the attribute extraction tool and copy feature tool, select the roads in the land class map layer of the annual change survey data.

[0086] Step 7, call the analysis tool, based on the nearest neighbor analysis tool (Near), take the road as the neighboring element, calculate the straight-line distance between the first potential spot and the nearest road, and form the first potential spot_road distance.

[0087] Step 8, call the data management tool, based on the Add Field tool (Add Field), add a field - Road Distance (DLJL) in the first potential map_Road Distance; and based on the Calculate Field tool (CalculateField), calculate the road accessibility, and assign values ​​of within 50 meters, outside 50 meters and within 100 meters, outside 100 meters and within 200 meters, and outside 200 meters in the field Road Distance (DLJL) according to the 50 / 100 / 200 meter classification reference index table, respectively, to obtain the seventh potential map with assigned road accessibility.

[0088] Step 9, call the data management tool, based on the Add Field tool (Add Field), add a field - Difficulty of Rectification (ZGNYD) in the first potential map; then based on the Attribute Extraction Tool (SelectLayerByAttribute), filter the field - Land Class Name (DLMC) in the first potential map, and assign a value to the field - Difficulty of Rectification according to the Difficulty of Rectification rule (i.e., shrub forest and other woodland are assigned as easy to recover, tree forest and bamboo forest are assigned as relatively easy to recover, orchards, tea gardens and other gardens are assigned as relatively difficult to recover, and other land classes are assigned as impossible to recover), and obtain the eighth potential map with assigned Difficulty of Rectification.

[0089] like Figure 7 As shown, the spatial site selection analysis module is used to set the spatial site selection evaluation index system and index weights applicable to the southwestern mountainous area based on the hierarchical analysis method and the expert scoring method, and summarize and calculate the potential spot scoring results of the target area based on the first potential spot, the second potential spot, the third potential spot, the fourth potential spot, the fifth potential spot, the sixth potential spot, the seventh potential spot and the eighth potential spot.

[0090] The potential patch scoring results of the spatial site selection analysis module are divided into four categories based on the natural breakpoint method, namely priority restoration, gradual restoration, suspended restoration and irrecoverable. Patch sites with higher scores are divided into priority restoration or gradual restoration categories, and patch sites with lower scores are divided into suspended restoration or irrecoverable categories, which can provide clear patch site selection guidance and time schedule for the work of farmland occupation and compensation balance in the target area.

[0091] The spatial site selection module also aggregates the potential spot scoring results to form a database of potential spots for supplementing cultivated land space, such as Figure 8 shown.

[0092] Specifically, in this embodiment, the evaluation index system for the spatial site selection of supplementary cultivated land applicable to the southwestern mountainous areas is shown in Table 1, the judgment results of each index based on the hierarchical analysis method and the expert scoring method are shown in Table 2 and Table 3 respectively, and the set index weights are shown in Table 4.

[0093] Table 1 Evaluation index system for spatial selection of supplementary cultivated land in southwestern mountainous areas

[0094]

[0095]

[0096] Table 2 AHP single indicator criterion judgment matrix

[0097]

[0098] Table 3 Hierarchical analysis results and consistency test results based on the judgment matrix of single indicator criteria

[0099]

[0100] Table 4 Single indicator weight results

[0101] index Weight value Concentration and continuation of cultivated land 0.3175 slope 0.2476 Priority of balance 0.1530 Road accessibility 0.1235 Proximity to residential areas 0.0945 Proximity to water sources 0.0320 Land Type 0.0319

[0102] In practical applications, the application of this intelligent site selection module group can realize highly intelligent spatial site selection analysis for supplementary cultivated land.

[0103] Specifically, after determining the target area to be analyzed, for example, if the target area is determined to be a certain area in the southwestern mountainous area, use the data extraction module to obtain the 2020 land change survey data of the target area, the latest year (for example, 2023) land change survey data, DEM digital elevation data, "three zones and three lines" demarcation results, national land space planning results, land acquisition database, forestry special data, river and lake area scope, drinking water source first-level protection zone and other data; or import the above data into the data extraction module (for example, Fig. 9 As shown), then enable other modules in the intelligent site selection module group to gradually generate the first potential map spot to the eighth potential map spot.

[0104] Finally, the spatial site selection analysis module summarizes and calculates the assignment results of the spatial potential patches of supplementary cultivated land in the target area; the assigned occupation and compensation balance demand patches obtained by the occupation and compensation demand analysis module, the various assigned patches (cultivated land concentration and continuity, residential proximity, water source proximity) obtained by the farming conditions analysis module, and the various assigned patches (slope, road accessibility, difficulty of rectification) obtained by the remediation cost analysis module are summarized and calculated according to their respective weights.

[0105] Finally, the natural breakpoint method was used to divide the scoring results into four categories: priority restoration, gradual restoration, delayed restoration, and irreversible restoration, forming a database of spatial potential patches of supplementary cultivated land. Patches with higher scores were classified as priority restoration or gradual restoration, and patches with lower scores were classified as delayed restoration or irreversible restoration.

[0106] This embodiment provides a method for selecting the location of supplementary cultivated land in the mountainous areas of the southwest. It can combine the natural geographical pattern of the region, coordinate various types of space such as agricultural production, industrial development, afforestation, etc., to ensure the quality of supplementary cultivated land and ensure long-term stable use. It can quantitatively analyze the feasibility of rectification of non-cultivated agricultural land map patches through computer language, scientifically determine the time sequence of supplementary cultivated land space and rectification and restoration, and provide effective quantitative evaluation results for the balance of regional cultivated land occupation and compensation. In particular:

[0107] First, this plan can achieve accurate assessment of supplementary arable land resources and has strong applicability.

[0108] In terms of demand for land occupation and compensation, the changes in cultivated land in different villages were taken into consideration, and the demand for land replenishment was reasonably scored, which helped to determine the priority of land replenishment according to actual demand. The priority of land replenishment was increased in areas with large outflow of cultivated land, and decreased in areas with small outflow of cultivated land, so as to keep the overall layout of cultivated land stable and ensure that high-quality cultivated land was restored and replenished in time after outflow, which was in line with the principle of "restoring high-quality cultivated land as the main and reclaiming new cultivated land as the supplement" in the reform policy of balanced land occupation and compensation.

[0109] In terms of farming conditions, the analysis of the concentration and continuity of cultivated land, the proximity of settlements and the proximity of water sources enables accurate judgment of the suitability of each plot for farming. Plots close to settlements and water sources with high concentration and continuity of cultivated land have more advantages in farming and can be given priority in subsequent farmland rectification and restoration work.

[0110] The cost analysis of remediation starts from the perspectives of slope, road accessibility and difficulty of remediation, and uses quantitative indicators to accurately evaluate the cost of remediation, eliminating the interference of subjective opinions in the field survey questionnaire on the evaluation results, and providing decision makers with an objective basis for the cost of remediation of each plot. The plots with gentle slopes, close to roads and low difficulty of remediation have relatively low remediation costs, which are more conducive to the development of supplementary arable land.

[0111] Second, this scheme can realize efficient spatial site selection analysis for supplementary cultivated land.

[0112] This solution is secondary developed based on the ArcGIS platform. The model builder is used to build a data processing model to integrate the content of the technical solution, forming five data processing modules: management adaptability analysis module, management adaptability analysis results compilation module, occupation and compensation demand analysis module, farming condition analysis module, and remediation cost analysis module. The specific and tedious operations such as data extraction, data conversion, data analysis, data calculation, parameter setting, and Python script setting are visualized and automated, and integrated into a one-click operation toolbox, which turns the original operation steps of dozens of tools into one tool, greatly simplifying the workflow of GIS data processing, saving data processing time, and reducing the possibility of human errors in complex operations, thereby improving work efficiency and accuracy.

[0113] More importantly, this solution has achieved the deep integration of GIS technology in the assessment of the potential of supplementary cultivated land, and fully tapped the huge potential of geographic information system (GIS) in the field of assessment of the potential of supplementary cultivated land. The constructed intelligent site selection module group, combined with the preset operation logic code, has transformed the traditional step-by-step operation and manual processing into one-click import and one-step generation, realizing the efficient management and in-depth analysis of a large amount of spatial data, greatly improving the accuracy and efficiency of the assessment of the potential of supplementary cultivated land.

[0114] In the above integration process, the writing of tool codes, the arrangement of operation logic, and the combing of operation objects are all the innovations and difficulties of the present invention. In terms of tool code writing, by building multiple pre-operation logic codes into the integration tool, the data processing results of each section are sorted out so that they can be directly called by the next section code, eliminating the steps of manually sorting the results and then transferring to the next operation in the traditional method, and realizing the full automation of the processing process of the present invention. In terms of operation logic arrangement, based on the original intention of the present invention for full automation processing, there are a large number of basic tools reused and cross-mixed in the internal operation process of the integration tool. If the basic tools are used improperly or the arrangement position is not logical, it may lead to inaccurate data results or even the inability of the integration tool to run. Therefore, the reasonable calling and correct arrangement of the basic tools is one of the difficulties of the present invention, and the present invention provides the best solution for it. In terms of operation object combing, in order to ensure the accuracy of the results, the present invention uses all digital legal data, with diverse data sources, and correctly combs the data. In the process of repeated calling, the correct and necessary part of the data is extracted to ensure that the basic tools can run in an orderly manner. This is one of the difficulties of the present invention; and the present invention ensures the accuracy of the data in the whole application process through layer-by-layer data association.

[0115] Third, the analysis results of this plan are highly reliable, have high reference value, and have high development value.

[0116] In this scheme, the spatial site selection analysis module integrates the analysis results of the previous modules, determines the weights according to the scientific analytic hierarchy process and expert scoring method, and classifies through the natural breakpoint method, providing a scientific decision-making basis for the site selection of cultivated land rectification and restoration plots. Government departments or relevant decision-making agencies can formulate targeted cultivated land occupation and compensation balance plans based on the classification results in the cultivated land spatial potential plot results database, arrange resources reasonably, improve the efficiency and scientific nature of cultivated land occupation and compensation balance work, and ensure the quality and long-term stable utilization of supplemented cultivated land.

[0117] More importantly, this plan is implemented under the premise of complying with the requirements of national land space planning and ecological environmental protection. The management adaptability analysis module processes the data at the beginning, removes the spots that do not meet the management requirements, ensures that the final evaluation results are consistent with the policy management requirements, avoids decision-making errors caused by non-compliance with the policy, and helps to scientifically and rationally utilize land resources and avoid unreasonable land use layout damage while adhering to the red line of cultivated land protection.

[0118] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field are aware of all the common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement the scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for the ordinary technicians in the relevant field to implement this application. It should be pointed out that for the technicians in this field, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A spatial site selection method for supplementary cultivated land in the southwestern mountainous areas, characterized in that: The following steps are involved: An intelligent site selection module group is constructed based on ArcGIS software, and the intelligent site selection module group is used to select the site for supplementary cultivated land space; The intelligent site selection module group includes a management adaptability analysis module, an occupation and compensation demand analysis module, a farming condition analysis module, a remediation cost analysis module and a spatial site selection analysis module; The management adaptability analysis module is used to extract the non-cultivated agricultural map patches in the target area and pre-process them to obtain the first potential map patches that meet the management requirements; The occupation and compensation demand analysis module is used to calculate the type of administrative village to which the target area belongs, and based on the type of administrative village and its corresponding annual change survey data, mark the first potential map spot to obtain the second potential map spot with the assigned occupation and compensation balance demand; The farming condition analysis module is used to calculate the concentration and continuity of cultivated land through aggregation surface analysis based on the annual change survey data, and calculate the proximity of residential points and water sources through neighbor analysis to obtain the third potential map assigned to the concentration and continuity of cultivated land, the fourth potential map assigned to the proximity of residential points, and the fifth potential map assigned to the proximity of water sources; The remediation cost analysis module is used to obtain the sixth potential map of assigned slope through slope measurement and spatial connection based on the annual change survey data; calculate road accessibility through neighbor analysis to obtain the seventh potential map of assigned road accessibility; and obtain the eighth potential map of assigned rectification difficulty through rectification difficulty rule screening; The spatial site selection analysis module is used to set a spatial site selection evaluation index system and index weights applicable to the southwestern mountainous areas for supplementary cultivated land, and based on the first potential spot, the second potential spot, the third potential spot, the fourth potential spot, the fifth potential spot, the sixth potential spot, the seventh potential spot and the eighth potential spot, summarize and calculate the potential spot scoring results of the target area.

2. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 1 is characterized in that: The management adaptability analysis module establishes a call link with the analysis tools, spatial analysis tools and data management tools of ArcGIS software; the management adaptability analysis module includes the following operation logic: Based on the annual change survey data, call the spatial analysis tool, and use the attribute extraction tool and copy feature tool to select the non-cultivated agricultural land and management element data in the land class map layer of the annual change survey data; Call the data management tool, and based on the fusion tool therein, fuse the extracted non-agricultural land according to the land type name field to form a non-agricultural land base map; based on the merge tool therein, merge the extracted management element data into one layer and form a management element collection; Call the analysis tool, and based on the erase tool therein, use the management element collection as the erase element to erase the non-cultivated agricultural land base map patches, and form the target non-cultivated agricultural land base map patches that meet the management requirements; Call the data management tool, and use the multi-component to single-component tool and the add field tool to break up the target non-cultivated agricultural land base map into single components, add the Area field to it, and calculate the geometric area of ​​each single component based on the field to form a single component map; Call the spatial analysis tool, based on the attribute extraction tool and the copy feature tool, extract the spots with Area field values ​​greater than 400 in the single-part spots, and form the first potential spots that meet management needs.

3. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 1 is characterized in that: The compensation demand analysis module establishes a call link with the analysis tools, spatial analysis tools and data management tools of ArcGIS software; the compensation demand analysis module includes the following operation logic: Based on the annual change survey data, call the spatial analysis tool, and based on the Extract by Attribute tool and Copy Feature tool, select the historical cultivated land in the land type map patch layer of the historical annual change survey data, and select the latest cultivated land and village survey area in the land type map patch layer of the latest annual change survey data; Call the analysis tool, based on the identification tool, take the village survey area as the identification element, mark the historical cultivated land and the latest cultivated land respectively, and obtain the historical cultivated land spots marked with the village survey area and the latest cultivated land spots marked with the village survey area; then based on the summary statistics tool, take the map area as the statistical field, summarize the historical cultivated land spots and the latest cultivated land spots respectively, and obtain the statistical table of cultivated land by village in the historical change survey data and the statistical table of cultivated land by village in the latest change survey data; Call the data management tool, and based on the connection field tool, use the historical change survey data cultivated land village statistics table and the latest change survey data cultivated land village statistics table as the connection table, connect the cultivated land area statistics to the village survey area, and obtain the village survey area with cultivated land area; then use the add field tool to add the area change quantity and area change ratio fields to the village survey area, and calculate the area change quantity and area change ratio based on the fields; Then, based on the calculation field tool, according to the area change amount and area change ratio, according to the preset standards, the administrative village type to which the target area belongs is calculated, and the latest village-level survey area layer is obtained; The analysis tool is called, and based on the identification tool therein, the first potential map is identified with the latest village-level survey area layer as the identification element, and the second potential map with the assigned occupation and compensation balance demand is obtained.

4. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 1 is characterized in that: The farming condition analysis module establishes a call link with the mapping tool, analysis tool, spatial analysis tool and data management tool of ArcGIS software; the farming condition analysis module includes the following operation logic: Based on the annual change survey data, call the spatial analysis tool, and use the Extract by Attribute tool and Copy Feature tool to select the cultivated land, rural homestead and land water spots in the land type spot layer of the annual change survey data; Calling the data management tool, and merging the first potential map and the cultivated land into a merged map based on the merge tool therein; Call the mapping tool, based on the aggregation surface tool, set the aggregation distance to 8m, aggregate the merged spots to form the aggregation results; Call the data management tool, and use the Add Field tool in it to add the aggregation area and concentration connectivity fields to the aggregation results, and calculate the aggregation area and concentration connectivity based on the fields; The analysis tool is called, and based on the identification tool therein, the first potential map is identified with the aggregation results as the identification factor, and the third potential map with the assigned cultivated land concentration and continuity is obtained.

5. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 4 is characterized in that: The farming condition analysis module also includes the following operating logic: Call the analysis tool, based on the neighbor analysis tool, take the rural homestead as the neighboring element, calculate the straight-line distance between the first potential spot and the nearest rural homestead, and form the first potential spot_homestead distance; Call the data management tool, and based on the Add Field tool, add a field - Residential Point Distance - to the first potential map - Homestead Distance; and based on the Calculate Field tool, calculate the residential point distance to obtain the fourth potential map that assigns the proximity of the residential point; Call the analysis tool, based on the neighbor analysis tool, take the land water patch as the neighboring element, calculate the straight-line distance between the first potential patch and the nearest land water, and form the first potential patch_water source distance; Call the data management tool, and based on the add field tool, add the field - water source distance in the first potential map - water source distance; and based on the calculate field tool, calculate the water source distance to obtain the fifth potential map with assigned water source proximity.

6. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 1 is characterized in that: The intelligent site selection module group also includes a data extraction module; the data extraction module is used to obtain annual change survey data and association analysis data.

7. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 1 is characterized in that: The remediation cost analysis module establishes a call link with the conversion tool, analysis tool, spatial analysis tool and data management tool of ArcGIS software; the remediation cost analysis module includes the following operation logic: Based on the DEM digital elevation data of the target area, the spatial analysis tool is called, and based on the slope tool therein, the slope of each raster pixel in the DEM digital elevation data is calculated to form a raster slope map; then based on the reclassification tool therein, the slope field of the raster slope map is used as the reclassification field, and the raster slope map of the target area is reclassified to obtain the raster slope map_reclassification; Call the conversion tool, and based on the Raster to Polygon tool, convert the raster slope map_reclassification into a vector slope map; Call the data management tool, and based on the Add Field tool and Calculate Field tool, add a field - unique FID to the first potential map, and calculate the value of the field; Calling the analysis tool, based on the identification tool therein, using the vector slope map as an identification element, identifies the first potential map spot, and obtains the first potential map spot with the slope marked; Call the data management tool, and based on the sorting tool and the delete identical items tool, sort the Shape_area field of the first potential spot marked with the slope in descending order, and delete the identical items based on the unique FID field, so that the first potential spot marked with the slope only retains the slope value with the largest area proportion of each unique spot, which is regarded as the slope value of each unique spot; then based on the spatial connection tool, take the first potential spot marked with the slope as the connection element, and the first potential spot as the target element, connect the slope values ​​of each unique spot to the first potential spot, and obtain the sixth potential spot with the assigned slope.

8. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 7 is characterized in that: The remediation cost analysis module also includes the following operating logic: Based on the annual change survey data, call the spatial analysis tool, and use the Extract by Attribute tool and Copy Feature tool to select the roads in the land class map layer of the annual change survey data; Call the analysis tool, based on the neighbor analysis tool, take the road as the neighboring element, calculate the straight-line distance between the first potential spot and the nearest road, and form the first potential spot_road distance; Call the data management tool, and based on the add field tool, add the field - road distance in the first potential map_road distance; and based on the calculate field tool, calculate the road accessibility to obtain the seventh potential map with assigned road accessibility.

9. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 7 is characterized in that: The remediation cost analysis module also includes the following operating logic: Call the data management tool, and based on the Add Field tool, add a field - Difficulty of Rectification - in the first potential map; then based on the Extract by Attribute tool, filter the field - Land Class Name in the first potential map, and assign a value to the field - Difficulty of Rectification according to the Difficulty of Rectification rule, to obtain the eighth potential map with assigned Difficulty of Rectification.

10. The method for selecting a supplementary cultivated land space in the southwestern mountainous area according to claim 1 is characterized in that: The potential map scoring results of the spatial site selection analysis module are divided into four categories based on the natural breakpoint method, namely priority restoration, gradual restoration, suspended restoration and irrecoverable restoration; the spatial site selection module also summarizes the potential map scoring results to form a database of potential map results for supplementary cultivated land space.

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