A method and system for comprehensive land improvement evaluation and analysis

Abstract

The present invention provides a method and system for evaluating and analyzing comprehensive land improvement in a whole region, which belongs to the field of analysis; the problem of incomplete evaluation of land improvement projects is solved; the specific analysis method is as follows: step S1: obtaining original DEM data; step S2: obtaining a land improvement plan; defining a land improvement simulation algorithm in a blank project according to the land improvement plan to obtain a pre-blank project; substituting the original DEM data into the pre-blank project to obtain a simulation model; step S3: backing up the pre-blank project; obtaining new DEM data; substituting the new DEM data into the pre-blank project to obtain a reference model; comparing the reference model with the simulation model to obtain a land improvement evaluation result; step S4: feeding back the land improvement evaluation result to a user; the present invention compares the data before and after land improvement in a target area in combination with user requirements, judges the advantages and disadvantages of land improvement, and facilitates users to understand land conditions.

Description

Technical Field

[0001] The present invention discloses a method and system for evaluating and analyzing comprehensive land improvement in an entire region, and relates to the technical field of land analysis. Background Art

[0002] The existing land consolidation analysis methods or systems have the following deficiencies:

[0003] Strong data dependence: Land consolidation is highly dependent on accurate and comprehensive data support, and a large amount of manpower, material and financial resources are required in the data collection and processing stages.

[0004] Complexity of the indicator system: The complexity of the indicator system will increase the difficulty of operation, requiring professional personnel to operate and analyze; at the same time, the weight allocation, data interpretation and result judgment of the actual analysis and evaluation are still affected by subjective factors.

[0005] Insufficient consideration of regional differences: Although the existing methods have wide applicability, their evaluation indicators and weights need to be adjusted accordingly in different regions, different land types and different remediation objectives, and regional differences need to be strengthened.

[0006] Real-time updating challenges: With the deepening of land consolidation work and changes in the external environment, the evaluation methods and indicator systems need to be continuously updated and optimized. Summary of the invention

[0007] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a method and system for comprehensive land consolidation evaluation and analysis in the whole area, aiming to solve the problem of incomplete evaluation of land consolidation projects.

[0008] In order to achieve the above object, the present invention is implemented through the following technical solutions: A method for comprehensive land improvement evaluation and analysis in the whole area includes:

[0009] Step S1: Obtain the three-dimensional coordinate information of the target area before land consolidation, and process it using the SAR algorithm to obtain the original DEM data;

[0010] Step S2: Obtain a land consolidation plan for the target area; create a blank project in the GIS workspace; define the simulated consolidation process of land flatness, farmland division and river diversion for the target area in the blank project according to the land consolidation plan for the target area to obtain a pre-blank project; substitute the original DEM data into the pre-blank project to obtain a simulation model;

[0011] Step S3: back up the pre-blank project; obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with the SAR algorithm to obtain new DEM data; substitute the new DEM data into the pre-blank project to obtain a reference model; compare the reference model with the simulation model to obtain the land consolidation evaluation result;

[0012] Step S4: Feedback the land consolidation evaluation results to the user.

[0013] Furthermore, the specific steps of step S1 are as follows:

[0014] Step S11: using an automatic recording instrument such as a GPS, a total station or a theodolite to measure the target area and obtain the three-dimensional coordinate information of the target area;

[0015] Step S12: input the three-dimensional coordinates of the target area into the computer through serial communication, and process them with the SAR algorithm to obtain the original DEM data, and then proceed to step S2; the specific steps of step S12 include: step S121 to step S123;

[0016] Step S121: using the SARscape application interface and the ENVI application interface, geometric correction and radiation calibration processing are performed on the three-dimensional coordinate information in turn to obtain pre-processed data 1;

[0017] Step S122: Load the SARscape software application interface; use the SARscape tool,

[0018] / SARscape / Interferometry / InterferometricTools / Baseline Estimation tool, performs baseline estimation on preprocessed data 1 to obtain preprocessed data 2;

[0019] Step S123: Use the / SARscape / Basic / Intensity Processing / Coregistration tool in the SARscap tool to align the pre-processed data 2 to obtain the original DEM data.

[0020] Furthermore, the specific steps of step S2 are as follows:

[0021] Step S21: Obtain the land consolidation plan of the target area, and extract the consolidation standards and consolidation scope;

[0022] The remediation standards include: design elevation, design slope height, standard altitude, and slope range of farmland;

[0023] The scope of regulation includes: the design scope of farmland and the design flow of rivers;

[0024] Step S22: preprocessing the original DEM data;

[0025] Step S23: loading the GIS application interface and creating a blank project; in the blank project, setting a simulation algorithm for the land consolidation project to obtain a pre-blank project;

[0026] Step S24: Substitute the original DEM data into the pre-blank project to obtain a simulation model and proceed to step S3.

[0027] Furthermore, the specific steps of step S22 are as follows:

[0028] Step S221: Obtain the farmland distribution map of the target area; mark the location of the field in the original DME data according to the farmland distribution map, and use the DEM function to represent the elevation of the field; the DEM function of the field elevation is represented as follows:

[0029] Z i =f(x i ,y i ); where i represents 1 to n; (x i ,y i ) represents the plane coordinates corresponding to the i-th field; Z i is the elevation corresponding to the ith field; f() represents the DEM function;

[0030] Step S222: using the SOA factor to represent the ridgeline in the original DEM data; the specific steps of step S222 include: step S2221 to step S2223;

[0031] Step S2221: Positive terrain DEM data:

[0032] Use Rasterio library functions to process the original DEM data and extract the slope data from the original DEM data;

[0033] Step S2222: Inverse terrain DEM data:

[0034] Extract the maximum elevation value in the original DEM data, record it as HH; use the maximum elevation value HH to subtract all the elevation values ​​in the original DEMDEM data in turn to obtain the inverse terrain DEM;

[0035] Step S2223: Use the inverse terrain DEM to correct the slope aspect error SOA in the slope area. The correction formula is:

[0036] SOA=(([SOA1]+[SOA2])-Abs([SOA1]-[SOA2])) / 2;

[0037] Among them, S0A1 is the slope aspect variability of the original DEM data, that is, the positive terrain DEM data; SOA2 is the slope aspect variability of the inverse terrain DEM data, that is, the inverse terrain DEM data, and Abs represents the absolute value function;

[0038] Step S223: obtaining a farmland distribution map of the target area; marking the location of the field in the original DME data according to the farmland distribution map, and calculating the planned earthwork volume of the field; the specific steps of step S223 include: steps S2231 to S2234;

[0039] Step S2231: The number of grids in the field is recorded as n; the DEM algorithm in the ArcGIS Engine development kit is used to calculate the earthwork volume of the field:

[0040] Use (x i ,y i ) format, indicating the position of the 1st to nth fields; where i represents 1 to n; (x i ,y i ) represents the plane coordinates corresponding to the i-th field;

[0041] Step S2232: Get the original DEM data resolution, denoted as L; the grid size corresponding to the 1st to nth fields is L*L, that is, Δδ i =L*L; where Δδ i Indicates the grid size corresponding to the i-th field;

[0042] Step S2233: Obtain the design elevations corresponding to the 1st to nth plots in the land consolidation plan of the target area, denoted as H1 to H n ; Calculate the excavation volume Vexcavation of the field. The calculation formula of Vexcavation is as follows:

[0043] Vdig=liml→0(n→+∞)∑(f(x i ,y i )-H i )*Δδ i ;

[0044] Calculate the field fill volume Vfill, the calculation formula of Vfill is as follows:

[0045] Vfill=liml→0(n→0)∑(H i -f(xi,yi))*Δδ i ;

[0046] Where i represents 1 to n; H i represents the design elevation of the ith field;

[0047] Step S2234: Calculate the proposed field earthwork volume V, the calculation formula of V is: V = (Vfill + Vdig) / 2.

[0048] Furthermore, the specific steps of step S23 are as follows:

[0049] Step S231: Setting the implementation algorithm of GIS basic functions;

[0050] Spatial query: IFeatureLayer.Search algorithm;

[0051] Attribute query: IFeatureSelection.SelectFeatures algorithm;

[0052] Extract slope: ISurfaceOp.Slope algorithm;

[0053] Extract slope direction: ISurfaceOp.Aspect algorithm;

[0054] Extract contour lines: ISurfaceOp.Contour algorithm;

[0055] Step S232: setting the algorithms of GIS reclassification, vector-to-raster conversion, and raster-to-vector conversion; the specific steps of step S232 include: step S2321 to step S2323;

[0056] Step S2321: Reclassification: First, use the IRasterStatistics interface to count the maximum and minimum phase element values ​​of the grid data in the original DEM data; then use iNumberRemap to set the reclassification interval; and then use the IReclassOp.ReclassByRemap algorithm to achieve reclassification;

[0057] Step S2322: vector to raster conversion: IConversionOp.ToRasterDataset algorithm;

[0058] Step S2323: raster to vector conversion:

[0059] Determine the type of the converted layer; if it is a point layer, use

[0060] IConversionOp.RasterDataToPointFeatureData algorithm;

[0061] If converted to line layer: IConversionOp.RasterDataToLineFeatureData;

[0062] If it is a surface layer, use

[0063] IConversionOp.RasterDataToPolygonFeatureData algorithm;

[0064] Step S233: simulating land leveling and land reclamation, and dividing the farmland range; Step S233 includes: Step S2331 to Step S2335;

[0065] Step S2331: Obtain the designed slope height and standard altitude;

[0066] Step S2332: Extracting gentle slope area:

[0067] According to the grid size of the input original DEM data, the output grid size of the land leveling project is set. The ISurfaceOp.Slope algorithm and the reclassification function in the GIS basic function are used to compare the slopes and extract the areas with slopes less than the designed slope height, which are recorded as gentle slope areas.

[0068] Step S2333: Extract low altitude areas: extract areas below the standard altitude in the original DEM data as low altitude areas; use the INumberRemap interface to output the gentle slope areas and low altitude areas in vector format;

[0069] Step S2334: obtaining the design range of the farmland; according to the design range, using the IConstructCurve interface ConstructOffset algorithm to sequentially create two sets of parallel lines for the 1st to nth fields, indicating the field edge lines of the fields;

[0070] Step S2335: Obtain the slope range of the farmland, recorded as standard range 1; extract the area with a slope within standard range 1 in the gentle slope area, recorded as area to be divided 1; superimpose area 1 to be divided with the low-altitude area, use the FeatureToLine class in the Geoprocessor tool, and select the low-altitude area with a slope within standard range 1 and not on the ridge in the divided area 1 as the slope-to-field conversion area, recorded as the newly added field area;

[0071] Use the ISurfaceOp.Contour algorithm, take the area of ​​L*L as the division area, and mark the field edge line and field edge offset line in the newly added field area; where L represents the resolution of the original DEM data;

[0072] Step S234: Simulate water conservancy improvement.

[0073] Furthermore, the specific steps of step S234 are as follows:

[0074] Step S2341: Obtain the design flow of the river, recorded as the standard flow;

[0075] Use the surface runoff model in GIS to process the original DEM data, mark the river areas and non-depression areas in the target area; use the non-depression areas as water diversion areas;

[0076] Step S2342: Calculate the water flow direction of each grid and the accumulated flow volume; extract the grids whose accumulated flow volume is greater than the standard flow volume as the water flow path to obtain the planned river network;

[0077] The implementation algorithm of the new river network is as follows: No depression filling: IHydrologyOp.fill algorithm;

[0078] Calculation of water flow direction based on DEM without depressions: IHydrologyOp.FlowDirection algorithm;

[0079] Calculate the accumulated flow using the flow direction data: IHydrologyOp.FlowAccumulation algorithm;

[0080] Vectorize the planned river network: Use the self-written RasterToPolyline() function to extract the raster of the river network and obtain the planned river network; convert the planned river network into vectors; the code of the RasterToPolyline() function is as follows:

[0081] ILayer pLayer=pMap.get_Layer(layerIndex);

[0082] IRasterLayer rasterLayer=(IRasterLayer)pLayer;

[0083] IRaster pRaster=rasterLayer.Raster;

[0084] IGeoDataset.pGeodataset=pRaster asIGeoDataset.;

[0085] object Missing=Type.Missing;

[0086] IGeoDataset fill=pHydro.Fill(pGeodataset,ref Missing);

[0087] flowdir=pHydro.FlowDirection(fill,true,true);

[0088] flowacc=pHydro.FlowAccumulation(flowdir,ref Missing);

[0089] label4.Text = "Minimum confluence accumulation:"

[0090] +Calling.ZMinCal(flowacc); / / ZMinCal calculates the minimum value of the grid;

[0091] label5.Text = "Maximum confluence accumulation:"

[0092] +Calling.ZMaxCal(flowacc); / / ZMinCal calculates the maximum value of the grid;

[0093] IRaster flowaccRaster=(IRaster)flowacc;

[0094] IGeoDataset streamRaster=Calling.ReclassMax(flowaccRaster,"value",fileName,Convert.ToInt32(textBox1.Text));

[0095] streamGeo=Calling.RasterToPolyline(fileName,"ssddd",streamRa ster).

[0096] Furthermore, the specific steps of step S3 are as follows:

[0097] Step S31: In the GIS workspace, a blank project is created for the second time as a new blank project; and the algorithm in step S23 is loaded into the new blank project for backup (backup of the pre-blank project);

[0098] Obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with SAR algorithm to obtain new DEM data;

[0099] Step S32: Substitute the new DEM data into the pre-blank project to obtain a reference model;

[0100] Step S33: using the shape diameter function to determine whether the reference model and the simulation model are similar;

[0101] If they are similar, it means that the land consolidation project in the target area is complete, and step S34 and subsequent steps are skipped. The land consolidation evaluation result is: excellent;

[0102] If not, the point distribution model is used to extract the area and elevation of all farmlands and the watershed of all rivers in the simulation model and the reference model, and then the process goes to step S34;

[0103] Step S34: The number of all farmlands in the simulation model is recorded as fc, and the areas corresponding to the first to fcth farmlands are recorded as ss1 to ss2. fc , the elevation is recorded as sh1~sh fc ; The total number of rivers is recorded as rc, and the basins corresponding to the first to the rc rivers are recorded as bs1 to bs rc ;

[0104] In the reference model, the total number of farmlands is denoted as fr; the area corresponding to the 1st to frth farmlands is denoted as ts1~ts fr , the elevation is recorded as th1~th fr ; The total number of rivers is denoted as rr, and the basins corresponding to the 1st to rrth rivers are denoted as rs1~rs rr .

[0105] Furthermore, the subsequent steps of step S34 are as follows:

[0106] Step S35: Define judgment formula 31: lim(∑ss i *sh i )→∑ts j *th j ; where i represents 1 to fc, in the simulation model, ss i and sh i Respectively represent the area and elevation of the i-th farmland; j represents 1~rc. In the reference model, ts j and j Respectively represent the area and elevation of the jth farmland;

[0107] Judgment formula 32: lim(∑bs i )→∑rs j ; Among them, bs i represents the watershed of the ith river in the simulation model; rs j represents the watershed of the jth river in the reference model;

[0108] Step S36: Substitute the data in step S34 into judgment formula 31 and judgment formula 32, summarize the satisfaction status, and determine the evaluation result;

[0109] If judgment formula 31 and judgment formula 32 are satisfied at the same time, the land consolidation evaluation result is: excellent;

[0110] If only judgment formula 31 is satisfied, and (∑bs i )>(∑rs j), then the land consolidation evaluation results are: good, widen the river channel;

[0111] If only judgment formula 31 is satisfied, and (∑bs i )<(∑rs j ), then the land consolidation evaluation results are: poor, strengthen the riverbed;

[0112] If only judgment formula 32 is satisfied, and (∑ss i *sh i )>(∑ts j *th j ), then the land consolidation evaluation result is: good, returning farmland to forest;

[0113] If only judgment formula 32 is satisfied, and (∑ss i *sh i )<(∑ts j *th j ), then the land consolidation evaluation results are: medium, opening up additional arable land;

[0114] If neither judgment formula 31 nor judgment formula 32 is satisfied, the land consolidation evaluation result is: poor, and land consolidation is performed again.

[0115] A comprehensive land improvement evaluation and analysis system includes:

[0116] Data acquisition module: used to obtain the three-dimensional coordinate information of the target area before land consolidation, and process it with SAR algorithm to obtain the original DEM data;

[0117] Simulation and remediation module: obtain the land remediation plan for the target area; create a blank project in the GIS workspace; define the simulated remediation process of land flatness, farmland division and river diversion in the target area in the blank project according to the land remediation plan for the target area to obtain a pre-blank project; substitute the original DEM data into the pre-blank project to obtain a simulation model;

[0118] Data comparison module: back up the pre-blank project; obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with the SAR algorithm to obtain new DEM data; substitute the new DEM data into the pre-blank project to obtain the reference model; compare the reference model with the simulation model to obtain the land consolidation evaluation results;

[0119] User interaction module: used to feed back land consolidation evaluation results to users.

[0120] Compared with the prior art, the present invention has the following beneficial effects:

[0121] Comprehensiveness: The present invention can comprehensively evaluate land consolidation from multiple dimensions, including but not limited to land use efficiency, ecological and environmental impact, farmers' interests, etc.; this comprehensiveness enables decision makers to have a more comprehensive understanding of the effectiveness of land consolidation and provide strong support for scientific decision-making.

[0122] Quantitative analysis: The present invention adopts the method of quantitative analysis to present various indicators in the form of data, making the evaluation results more objective and accurate; quantitative analysis also helps to make a horizontal comparison of land consolidation effects in different regions and find out the gaps and reasons.

[0123] Visual display: Through modern information technology, the present invention can display the evaluation results in intuitive forms such as charts and maps, making it easier for decision makers to quickly grasp the overall situation of land consolidation. BRIEF DESCRIPTION OF THE DRAWINGS

[0124] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0125] Figure 1 It is a schematic diagram of the method of the present invention;

[0126] Figure 2 It is a schematic diagram of the system of the present invention;

[0127] Figure 3 This is a schematic diagram of the GIS basic function menu of the present invention;

[0128] Figure 4 It is a schematic diagram of a field of the present invention. DETAILED DESCRIPTION

[0129] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and understandable, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0130] Embodiment 1

[0131] See also Figure 1 , a comprehensive land improvement evaluation and analysis method for the whole region includes:

[0132] It should be noted that the "target area" in the present invention refers to the area where the "present invention is applied to conduct comprehensive land improvement evaluation".

[0133] Step S1: Obtain the three-dimensional coordinate information of the target area before land consolidation, and process it with the SAR algorithm to obtain the original DEM (digital elevation model) data;

[0134] The specific steps of step S1 are as follows:

[0135] Step S11: Using an automatic recording instrument such as a GPS, a total station or a theodolite, the target area (including direction, distance and height difference) is measured to obtain three-dimensional coordinate information of the target area;

[0136] Step S12: Input the three-dimensional coordinates of the target area (or each area within it) into the computer through serial communication, and process it with the SAR algorithm to obtain the original DEM (digital elevation model) data, and then enter step S2;

[0137] Step S121: using the SARscape application interface and the ENVI application interface, geometric correction and radiation calibration processing are performed on the three-dimensional coordinate information in turn to obtain pre-processed data 1;

[0138] Step S122: Load the SARscape software application interface; use the SARscape tool,

[0139] / SARscape / Interferometry / InterferometricTools / Baseline Estimation tool, performs baseline estimation on preprocessed data 1 to obtain preprocessed data 2;

[0140] Step S123: Use the / SARscape / Basic / Intensity Processing / Coregistration tool in the SARscap tool to align the pre-processed data 2 to obtain the initial DEM (digital elevation model) data.

[0141] Step S2: Obtain a land consolidation plan for the target area; create a blank project in the GIS workspace; define the simulated consolidation process of land flatness, farmland division and river diversion for the target area in the blank project according to the land consolidation plan for the target area to obtain a pre-blank project; substitute the original DEM data into the pre-blank project to obtain a simulation model;

[0142] The specific steps of step S2 are as follows:

[0143] Step S21: Obtain the land consolidation plan of the target area (of the user), and extract the consolidation standards and consolidation scope;

[0144] The remediation standards include: design elevation (of fields), design slope height (in plain areas), standard altitude (in target areas), and slope range of farmland;

[0145] The scope of regulation includes: the design scope of farmland and the design flow of rivers;

[0146] It should be noted that the "land consolidation plan for the target area" in the present invention refers to the land consolidation standards for the target area; the land consolidation standards include but are not limited to the number and slope height of farmland, the flatness of the land, the consolidation standards and consolidation scope of water conservancy and other areas;

[0147] The remediation standards and remediation scopes listed in the present invention are only examples. Users and relevant technical personnel can adjust the remediation standards and remediation scopes according to actual needs.

[0148] Step S22: preprocessing the original DEM (digital elevation model) data;

[0149] Step S221: Obtain the farmland distribution map of the target area; mark the location of the field in the original DME data according to the farmland distribution map, and use the DEM function to represent the elevation of the field; the DEM function of the field elevation is represented as follows:

[0150] Z i =f(x i ,y i ); where i represents 1 to n; (x i ,y i ) represents the plane coordinates corresponding to the i-th field; Z i is the elevation corresponding to the ith field; f() represents the DEM function;

[0151] Step S222: using the SOA factor to represent the ridgeline in the original DEM data;

[0152] Step S2221: Positive terrain DEM data:

[0153] Use Rasterio (geographic information processing library) library functions to process the original DEM data and extract the slope data from the original DEM data;

[0154] It should be noted that the "slope aspect data" in the present invention refers to the elevation values ​​corresponding to each area in the target area (the number of grids in the original DEM data) and the extension direction of the terrain.

[0155] Step S2222: Inverse terrain DEM data:

[0156] Extract the maximum elevation value in the original DEM data, recorded as HH; use the maximum elevation value HH to subtract all the elevation values ​​in the original DEM data in turn to obtain the inverse terrain DEM; (the inverse terrain DEM is the opposite terrain of the original DEM, and the original highest point is the lowest point in the inverse terrain data)

[0157] Step S2223: Use the inverse terrain DEM to correct the slope aspect error SOA in the slope area. The correction formula is:

[0158] SOA=(([SOA1]+[SOA2])-Abs([SOA1]-[SOA2])) / 2;

[0159] Among them, S0A1 is the slope aspect variability of the original DEM data, that is, the positive terrain DEM data; SOA2 is the slope aspect variability of the inverse terrain DEM data, that is, the inverse terrain DEM data, and Abs represents the absolute value function;

[0160] Step S223: obtaining a farmland distribution map of the target area; marking the location of the field in the original DME data according to the farmland distribution map, and calculating the planned earthwork volume of the field;

[0161] Step S2231: The number of grids in the field is recorded as n; the DEM algorithm in the ArcGIS Engine development kit is used to calculate the earthwork volume of the field:

[0162] Use (x i ,y i ) format (Gauss-Krüger coordinates), indicating the positions of the 1st to nth fields; where i represents 1 to n; (x i ,y i ) represents the plane coordinates corresponding to the i-th field;

[0163] Step S2232: Get the original DEM data resolution, denoted as L; the grid size corresponding to the 1st to nth fields is L*L, that is, Δδ i =L*L; where Δδ i Indicates the grid size corresponding to the i-th field;

[0164] Step S2233: Obtain the design elevations corresponding to the 1st to nth plots in the land consolidation plan of the target area, denoted as H1 to H n ; Calculate the excavation volume Vexcavation of the field. The calculation formula of Vexcavation is as follows:

[0165] Vdig=liml→0(n→+∞)∑(f(x i ,y i )-H i )*Δδ i ;

[0166] Calculate the field fill volume Vfill, the calculation formula of Vfill is as follows:

[0167] Vfill=liml→0(n→0)∑(H i -f(xi,yi))*Δδ i ;

[0168] Where i represents 1 to n; H i represents the design elevation of the ith field;

[0169] Step S2234: Calculate the proposed field earthwork volume V, where V is calculated using the formula: V = (Vfill + Vdig) / 2;

[0170] Step S23: Please refer to Figure 3 , load the GIS application interface and create a blank project; in the blank project, set the simulation algorithm of the land consolidation project (in the target area) to obtain the pre-blank project;

[0171] Step S231: Setting the implementation algorithm of GIS basic functions;

[0172] Spatial query: IFeatureLayer.Search algorithm;

[0173] Attribute query: IFeatureSelection.SelectFeatures algorithm;

[0174] Extract slope: ISurfaceOp.Slope algorithm;

[0175] Extract slope direction: ISurfaceOp.Aspect algorithm;

[0176] Extract contour lines: ISurfaceOp.Contour algorithm;

[0177] Step S232: setting GIS reclassification, vector-to-raster, and raster-to-vector algorithms;

[0178] Step S2321: Reclassification: First, use the IRasterStatistics interface to count the maximum and minimum phase element values ​​of the grid data in the original DEM data; then use iNumberRemap to set the reclassification interval; and then use the IReclassOp.ReclassByRemap algorithm to achieve reclassification;

[0179] Step S2322: vector to raster conversion: IConversionOp.ToRasterDataset algorithm;

[0180] Step S2323: raster to vector conversion:

[0181] Determine the type of the converted layer; if (the type of the converted layer) is a point layer, use

[0182] IConversionOp.RasterDataToPointFeatureData algorithm;

[0183] If converted to line layer: IConversionOp.RasterDataToLineFeatureData;

[0184] If (type of the latter layer) is a surface layer, use

[0185] IConversionOp.RasterDataToPolygonFeatureData algorithm;

[0186] Step S233: simulating land leveling and land reclamation, and dividing the farmland area;

[0187] Step S2331: Please refer to Table 1 to define the function menu of the land leveling project in GIS. The function menu is as follows:

[0188]

[0189]

[0190] Table 1

[0191] Obtain the design slope height and standard elevation of the land consolidation plan for the target area;

[0192] Step S2332: Extracting gentle slope area:

[0193] According to the grid size of the input original DEM data, the output grid size of the land leveling project is set. The ISurfaceOp.Slope algorithm and the reclassification function in the GIS basic function are used to compare the slopes and extract the areas with slopes less than the designed slope height, which are recorded as gentle slope areas.

[0194] Step S2333: Extract low altitude areas: extract areas below the standard altitude in the original DEM data as low altitude areas; use the INumberRemap interface to output the gentle slope areas and low altitude areas in vector format; the process of extracting ridge lines using the SOA method is the same as the process of (using the SOA factor to represent the ridge lines in the original DEM data);

[0195] Step S2334: Obtain the design scope of the farmland (land consolidation plan of the target area); according to the design scope, use the IConstructCurve interface ConstructOffset algorithm to create two sets of parallel lines for the 1st to nth fields in sequence, indicating the field edge lines of the fields;

[0196] Step S2335: Obtain the slope range of the farmland, recorded as standard range 1; extract the area with a slope within standard range 1 in the gentle slope area, recorded as area to be divided 1; superimpose area 1 to be divided with the low-altitude area, use the FeatureToLine class in the Geoprocessor tool, and select the low-altitude area with a slope within standard range 1 and not on the ridge in the divided area 1 as the slope-to-field conversion area, recorded as the newly added field area;

[0197] See also Figure 4 , using the ISurfaceOp.Contour algorithm, taking the area of ​​L*L as the division area, mark the field edge line and field edge offset line in the newly added field area; where L represents the resolution of the original DEM data;

[0198] Step S234: simulating water conservancy regulation;

[0199] Step S2341: Obtain the design flow of the river, recorded as the standard flow;

[0200] Use the surface runoff model in GIS to process the original DEM data, mark the river areas and non-depression areas in the target area; use the non-depression areas as water diversion areas;

[0201] Step S2342: Calculate the water flow direction of each grid and the accumulated flow volume; extract the grids whose accumulated flow volume is greater than the standard flow volume as the water flow path to obtain the planned river network;

[0202] The implementation algorithm of the new river network is as follows: No depression filling: IHydrologyOp.fill algorithm;

[0203] Calculation of water flow direction based on DEM without depressions: IHydrologyOp.FlowDirection algorithm;

[0204] Calculate the accumulated flow using the flow direction data: IHydrologyOp.FlowAccumulation algorithm;

[0205] Vectorize the planned river network: Use the self-written RasterToPolyline() function to extract the raster of the river network and obtain the planned river network; convert the planned river network into vectors; the code of the RasterToPolyline() function (main logic processing) is as follows:

[0206] ILayer pLayer=pMap.get_Layer(layerIndex);

[0207] IRasterLayer rasterLayer=(IRasterLayer)pLayer;

[0208] IRaster pRaster=rasterLayer.Raster;

[0209] IGeoDataset.pGeodataset=pRaster asIGeoDataset.;

[0210] object Missing=Type.Missing;

[0211] IGeoDataset fill=pHydro.Fill(pGeodataset,ref Missing);

[0212] flowdir=pHydro.FlowDirection(fill,true,true);

[0213] flowacc=pHydro.FlowAccumulation(flowdir,ref Missing);

[0214] label4.Text = "Minimum confluence accumulation:"

[0215] +Calling.ZMinCal(flowacc); / / ZMinCal calculates the minimum value of the grid;

[0216] label5.Text = "Maximum confluence accumulation:"

[0217] +Calling.ZMaxCal(flowacc); / / ZMinCal calculates the maximum value of the grid;

[0218] IRaster flowaccRaster=(IRaster)flowacc;

[0219] IGeoDataset streamRaster=Calling.ReclassMax(flowaccRaster,"value",fileName,Convert.ToInt32(textBox1.Text));

[0220] streamGeo=Calling.RasterToPolyline(fileName,"ssddd",streamRa ster);

[0221] Step S24: Substitute the original DEM data into the pre-blank project to obtain a simulation model and proceed to step S3.

[0222] Step S3: back up the pre-blank project; obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with the SAR algorithm to obtain new DEM data; substitute the new DEM data into the pre-blank project to obtain a reference model; compare the reference model with the simulation model to obtain the land consolidation evaluation result;

[0223] The specific steps of step S3 are as follows:

[0224] Step S31: In the GIS workspace, a blank project is created for the second time as a new blank project; and the algorithm in step S23 is loaded into the new blank project for backup (backup of the pre-blank project);

[0225] Obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with SAR algorithm to obtain new DEM data;

[0226] Step S32: Substitute the new DEM data into the pre-blank project to obtain a reference model;

[0227] Step S33: using a shape diameter function (SDF) to determine whether the reference model and the simulation model (are similar in shape);

[0228] If they are similar, it means that the land consolidation project in the target area is complete, and steps S34 to S36 are skipped. The land consolidation evaluation result is: excellent;

[0229] If not, a point distribution model (PDM) is used to extract the area and elevation of all farmlands and the watershed of all rivers in the simulation model and the reference model, and then the process goes to step S34;

[0230] Step S34: The number of all farmlands in the simulation model is recorded as fc, and the areas corresponding to the first to fcth farmlands are recorded as ss1 to ss2. fc , the elevation is recorded as sh1~sh fc ; The total number of rivers is recorded as rc, and the basins corresponding to the first to the rc rivers are recorded as bs1 to bs rc ;

[0231] In the reference model, the total number of farmlands is denoted as fr; the area corresponding to the 1st to frth farmlands is denoted as ts1~ts fr , the elevation is recorded as th1~th fr ; The total number of rivers is denoted as rr, and the basins corresponding to the 1st to rrth rivers are denoted as rs1~rs rr ;

[0232] Step S35: Define judgment formula 31: lim(∑ss i *sh i )→∑ts j *th j ; where i represents 1 to fc, in the simulation model, ss i and sh iRespectively represent the area and elevation of the i-th farmland; j represents 1~rc. In the reference model, ts j and j Respectively represent the area and elevation of the jth farmland;

[0233] Judgment formula 32: lim(∑bs i )→∑rs j ; Among them, bs i represents the watershed of the ith river in the simulation model; rs j represents the watershed of the jth river in the reference model;

[0234] Step S36: Substitute the data in step S34 into judgment formula 31 and judgment formula 32, and summarize the satisfaction conditions (of judgment formula 31 and judgment formula 32) to determine the evaluation result;

[0235] If judgment formula 31 and judgment formula 32 are satisfied at the same time, it means that the land consolidation project in the target area is complete, and the land consolidation evaluation result is: excellent;

[0236] If only judgment formula 31 is satisfied, and (∑bs i )>(∑rs j ), it means that the river flow in the target area is reduced and the river channel needs to be widened. The land consolidation evaluation results are: good, widen the river channel;

[0237] If only judgment formula 31 is satisfied, and (∑bs i )<(∑rs j ), it means that the river flow in the target area is excessive and the riverbed needs to be reinforced. The land consolidation evaluation results are: poor, reinforce the riverbed;

[0238] If only judgment formula 32 is satisfied, and (∑ss i *sh i )>(∑ts j *th j ), it means that there are too many cultivated areas in the target area and it is necessary to convert farmland into forest. The evaluation result of land consolidation is: good, convert farmland into forest;

[0239] If only judgment formula 32 is satisfied, and (∑ss i *sh i )<(∑ts j *th j ), it means that there is less arable land in the target area and additional arable land needs to be developed. The evaluation results of land consolidation are: medium, additional arable land needs to be developed;

[0240] If neither judgment formula 31 nor judgment formula 32 is satisfied, it means that there are too many cultivated areas in the target area and the riverbed needs to be reinforced. The land consolidation evaluation result is: poor, and land consolidation should be carried out again.

[0241] Step S4: Feedback the land consolidation evaluation results to the user.

[0242] Embodiment 2

[0243] See also Figure 2 A comprehensive land improvement evaluation and analysis system includes: a data acquisition module, a simulation integration module, a data comparison module, a user interaction module, a database and a server; wherein the data acquisition module, the simulation integration module, the data comparison module and the user interaction module are connected to the database and the server respectively.

[0244] Data acquisition module: used to obtain the three-dimensional coordinate information of the target area before land consolidation, and process it with SAR algorithm to obtain the original DEM data;

[0245] Simulation and remediation module: obtain the land remediation plan for the target area; create a blank project in the GIS workspace; define the simulated remediation process of land flatness, farmland division and river diversion in the target area in the blank project according to the land remediation plan for the target area to obtain a pre-blank project; substitute the original DEM data into the pre-blank project to obtain a simulation model;

[0246] Data comparison module: back up the pre-blank project; obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with the SAR algorithm to obtain new DEM data; substitute the new DEM data into the pre-blank project to obtain the reference model; compare the reference model with the simulation model to obtain the land consolidation evaluation results;

[0247] User interaction module: used to feed back land consolidation evaluation results to users.

[0248] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technical personnel in this field according to actual conditions. For example, if there are weight coefficients and proportional coefficients, their set sizes are to quantify each parameter to obtain a specific value, which is convenient for subsequent comparison. Regarding the size of the weight coefficient and the proportional coefficient, it is sufficient as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0249] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for comprehensive land management evaluation and analysis, characterized in that: Analytical methods include: Step S1: Obtain the three-dimensional coordinate information of the target area before land consolidation, and process it using the SAR algorithm to obtain the original DEM data; Step S2: Obtain a land consolidation plan for the target area; create a blank project in the GIS workspace; define the simulated consolidation process of land flatness, farmland division and river diversion for the target area in the blank project according to the land consolidation plan for the target area to obtain a pre-blank project; substitute the original DEM data into the pre-blank project to obtain a simulation model; Step S3: back up the pre-blank project; obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with the SAR algorithm to obtain new DEM data; substitute the new DEM data into the pre-blank project to obtain a reference model; compare the reference model with the simulation model to obtain the land consolidation evaluation result; Step S4: Feedback the land consolidation evaluation results to the user; The specific steps of step S2 are as follows: Step S21: Obtain the land consolidation plan of the target area, and extract the consolidation standards and consolidation scope; The remediation standards include: design elevation, design slope height, standard altitude, and slope range of farmland; The scope of regulation includes: the design scope of farmland and the design flow of rivers; Step S22: preprocessing the original DEM data; Step S23: loading the GIS application interface and creating a blank project; in the blank project, setting a simulation algorithm for the land consolidation project to obtain a pre-blank project; Step S24: Substitute the original DEM data into the pre-blank project to obtain a simulation model and proceed to step S3; The specific steps of step S22 are as follows: Step S221: Obtain the farmland distribution map of the target area; mark the location of the field in the original DME data according to the farmland distribution map, and use the DEM function to represent the elevation of the field; the DEM function of the field elevation is represented as follows: Z i =f(x i ,y i ); where i represents 1 to n; (x i ,y i ) represents the plane coordinates corresponding to the i-th field; Z i is the elevation corresponding to the ith field; f() represents the DEM function; Step S222: using the SOA factor to represent the ridgeline in the original DEM data; The specific steps of step S222 include: Step S2221: Positive terrain DEM data: Use Rasterio library functions to process the original DEM data and extract the slope data from the original DEM data; Step S2222: Inverse terrain DEM data: Extract the maximum elevation value in the original DEM data, record it as HH; use the maximum elevation value HH to subtract all the elevation values ​​in the original DEMDEM data in turn to obtain the inverse terrain DEM; Step S2223: Use the inverse terrain DEM to correct the slope aspect error SOA in the slope area. The correction formula is: SOA=(([SOA1]+[SOA2])-Abs([SOA1]-[SOA2])) / 2; Among them, S0A1 is the slope aspect variability of the original DEM data, that is, the positive terrain DEM data; SOA2 is the slope aspect variability of the inverse terrain DEM data, that is, the inverse terrain DEM data, and Abs represents the absolute value function; Step S223: obtaining a farmland distribution map of the target area; marking the location of the field in the original DME data according to the farmland distribution map, and calculating the planned earthwork volume of the field; The specific steps of step S223 include: Step S2231: The number of grids in the field is recorded as n; the DEM algorithm in the ArcGIS Engine development kit is used to calculate the earthwork volume of the field: Use (x i ,y i ) format, indicating the position of the 1st to nth fields; where i represents 1 to n; (x i ,y i ) represents the plane coordinates corresponding to the i-th field; Step S2232: Get the original DEM data resolution, denoted as L; the grid size corresponding to the 1st to nth fields is L*L, that is, Δδ i =L*L; where Δδ i Indicates the grid size corresponding to the i-th field; Step S2233: Obtain the design elevations corresponding to the 1st to nth fields, denoted as H1 to H n ; Calculate the excavation volume Vexcavation of the field. The calculation formula of Vexcavation is as follows: $V_{excavation}=\lim_{l\rightarrow0(n\rightarrow+\infty)}\sum(f(x i ,y i ) - H i )*\Delta\delta i ; Calculate the field fill volume Vfill, the calculation formula of Vfill is as follows: $V_{fill}=\lim_{l\rightarrow0}(n\rightarrow0)\sum(H i -f(x_i,y_i))*\Delta\delta i ; Where i represents 1 to n; H i represents the design elevation of the ith field; Step S2234: Calculate the proposed field earthwork volume V, the calculation formula of V is: V = (Vfill + Vdig) / 2.

2. The method for comprehensive land management evaluation and analysis according to claim 1 is characterized in that: The specific steps of step S1 are as follows: Step S11: measuring the target area to obtain the three-dimensional coordinate information of the target area; Step S12: input the three-dimensional coordinates of the target area into the computer through serial communication, and process them using the SAR algorithm to obtain the original DEM data, and then proceed to step S2; The specific steps of step S12 include: Step S121: using the SARscape application interface and the ENVI application interface, geometric correction and radiation calibration processing are performed on the three-dimensional coordinate information in turn to obtain pre-processed data 1; Step S122: Load the SARscape software application interface; use the SARscape tool, / SARscape / Interferometry / InterferometricTools / Baseline Estimation tool, performs baseline estimation on preprocessed data 1 to obtain preprocessed data 2; Step S123: Use the / SARscape / Basic / Intensity Processing / Coregistration tool in the SARscap tool to align the pre-processed data 2 to obtain the original DEM data.

3. The method for comprehensive land management evaluation and analysis according to claim 1 is characterized in that: The specific steps of step S23 are as follows: Step S231: Setting the implementation algorithm of GIS basic functions; Spatial query: IFeatureLayer.Search algorithm; Attribute query: IFeatureSelection.SelectFeatures algorithm; Extract slope: ISurfaceOp.Slope algorithm; Extract slope direction: ISurfaceOp.Aspect algorithm; Extract contour lines: ISurfaceOp.Contour algorithm; Step S232: setting GIS reclassification, vector-to-raster, and raster-to-vector algorithms; The specific steps of step S232 include: Step S2321: Reclassification: First, use the IRasterStatistics interface to count the maximum and minimum phase element values ​​of the grid data in the original DEM data; then use iNumberRemap to set the reclassification interval; and then use the IReclassOp.ReclassByRemap algorithm to achieve reclassification; Step S2322: vector to raster conversion: IConversionOp.ToRasterDataset algorithm; Step S2323: raster to vector conversion: Determine the type of the converted layer; if it is a point layer, use IConversionOp.RasterDataToPointFeatureData algorithm; If converted to line layer: IConversionOp.RasterDataToLineFeatureData; If it is a surface layer, use IConversionOp.RasterDataToPolygonFeatureData algorithm; Step S233: simulating land leveling and land reclamation, and dividing the farmland area; Step S233 includes: Step S2331: Obtain the designed slope height and standard altitude; Step S2332: Extracting gentle slope area: According to the grid size of the input original DEM data, the output grid size of the land leveling project is set. The ISurfaceOp.Slope algorithm and the reclassification function in the GIS basic function are used to compare the slopes and extract the areas with slopes less than the designed slope height, which are recorded as gentle slope areas. Step S2333: Extract low altitude areas: extract areas below the standard altitude in the original DEM data as low altitude areas; use the INumberRemap interface to output the gentle slope areas and low altitude areas in vector format; Step S2334: obtaining the design range of the farmland; according to the design range, using the IConstructCurve interface ConstructOffset algorithm to sequentially create two sets of parallel lines for the 1st to nth fields, representing the field edge lines of the fields; Step S2335: Obtain the slope range of the farmland, recorded as standard range 1; extract the area with a slope within standard range 1 in the gentle slope area, recorded as area to be divided 1; superimpose area 1 to be divided with the low-altitude area, use the FeatureToLine class in the Geoprocessor tool, and select the low-altitude area with a slope within standard range 1 and not on the ridge in the divided area 1 as the slope-to-field conversion area, recorded as the newly added field area; Use the ISurfaceOp.Contour algorithm, take the area of ​​L*L as the division area, and mark the field edge line and field edge offset line in the newly added field area; where L represents the resolution of the original DEM data; Step S234: Simulate water conservancy improvement.

4. The method for comprehensive land management evaluation and analysis according to claim 3 is characterized in that: The specific steps of step S234 are as follows: Step S2341: Obtain the design flow of the river, recorded as the standard flow; Use the surface runoff model in GIS to process the original DEM data and mark the river areas and non-depression areas in the target area; Use areas without depressions as water diversion areas; Step S2342: Calculate the water flow direction of each grid and the accumulated flow volume; extract the grids whose accumulated flow volume is greater than the standard flow volume as the water flow path to obtain the planned river network; The implementation algorithm of the new river network is as follows: No depression filling: IHydrologyOp.fill algorithm; Calculation of water flow direction based on DEM without depressions: IHydrologyOp.FlowDirection algorithm; Calculate the cumulative runoff using flow direction data: IHydrologyOp.FlowAccumulation algorithm; Vectorize the planned river network: Use the self-written RasterToPolyline() function to extract the raster of the river network and obtain the planned river network; convert the planned river network into vectors; The code of the RasterToPolyline() function is as follows: ILayer pLayer=pMap.get_Layer(layerIndex); IRasterLayer rasterLayer=(IRasterLayer)pLayer; IRaster pRaster=rasterLayer.Raster; IGeoDataset.pGeodataset=pRaster asIGeoDataset.; object Missing=Type.Missing; IGeoDataset fill=pHydro.Fill(pGeodataset,ref Missing); flowdir=pHydro.FlowDirection(fill,true,true); flowacc=pHydro.FlowAccumulation(flowdir,ref Missing); label4.Text="Minimum confluence accumulation:" +Calling.ZMinCal(flowacc); / / ZMinCal calculates the minimum value of the grid; label5.Text="Maximum confluence accumulation:" +Calling.ZMaxCal(flowacc); / / ZMinCal calculates the maximum "value" of the grid value; IRaster flowaccRaster=(IRaster)flowacc; IGeoDataset streamRaster=Calling.ReclassMax(flowaccRaster,"value",fileName,Convert.ToInt32(textBox1.Text)); streamGeo=Calling.RasterToPolyline(fileName,"ssddd",streamRaster).

5. The method for comprehensive land management evaluation and analysis according to claim 1 is characterized in that: The specific steps of step S3 are as follows: Step S31: back up the pre-blank project; obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with the SAR algorithm to obtain new DEM data; Step S32: Substitute the new DEM data into the pre-blank project to obtain a reference model; Step S33: using the shape diameter function to determine whether the reference model and the simulation model are similar; If they are similar, it means that the land consolidation project in the target area is complete, and step S34 and subsequent steps are skipped. The land consolidation evaluation result is: excellent; If not, the point distribution model is used to extract the area and elevation of all farmlands and the watershed of all rivers in the simulation model and the reference model, and then the process goes to step S34; Step S34: The number of all farmlands in the simulation model is recorded as fc, and the areas corresponding to the first to fcth farmlands are recorded as ss1 to ss2. fc , the elevation is recorded as sh1~sh fc ; The total number of rivers is recorded as rc, and the basins corresponding to the first to the rc rivers are recorded as bs1~bs rc ; In the reference model, the total number of farmlands is denoted as fr; the area corresponding to the 1st to frth farmlands is denoted as ts1~ts fr , the elevation is recorded as th1~th fr ; The total number of rivers is denoted as rr, and the basins corresponding to the 1st to rrth rivers are denoted as rs1~rs rr .

6. The method for comprehensive land management evaluation and analysis according to claim 5 is characterized in that: The subsequent steps of step S34 are as follows: Step S35: Define judgment formula 31: lim(∑ss i *sh i )→∑ts j *th j ; where i represents 1 to fc, in the simulation model, ss i and sh i Respectively represent the area and elevation of the i-th farmland; j represents 1~rc. In the reference model, ts j and j They represent the area and elevation of the jth farmland respectively; Judgment formula 32: lim(∑bs i )→∑rs j ; Among them, bs i represents the watershed of the ith river in the simulation model; rs j represents the watershed of the jth river in the reference model; Step S36: Substitute the data in step S34 into judgment formula 31 and judgment formula 32, summarize the satisfaction status, and determine the evaluation result; If judgment formula 31 and judgment formula 32 are satisfied at the same time, the land consolidation evaluation result is: excellent; If only judgment formula 31 is satisfied, and (∑bs i )>(∑rs j ), then the land consolidation evaluation results are: good, widen the river channel; If only judgment formula 31 is satisfied, and (∑bs i )<(∑rs j ), then the land consolidation evaluation results are: poor, strengthen the riverbed; If only judgment formula 32 is satisfied, and (∑ss i *sh i )>(∑ts j *th j ), then the land consolidation evaluation result is: good, returning farmland to forest; If only judgment formula 32 is satisfied, and (∑ss i *sh i )<(∑ts j *th j ), then the land consolidation evaluation results are: medium, opening up additional arable land; If neither judgment formula 31 nor judgment formula 32 is satisfied, the land consolidation evaluation result is: poor, and land consolidation is performed again.

7. A system for evaluating and analyzing comprehensive land management in a whole region, applicable to any one of the methods for evaluating and analyzing comprehensive land management in a whole region according to claims 1 to 6, characterized in that: The analysis system comprises: Data acquisition module: used to obtain the three-dimensional coordinate information of the target area before land consolidation, and process it with SAR algorithm to obtain the original DEM data; Simulation and remediation module: obtain the land remediation plan for the target area; create a blank project in the GIS workspace; define the simulated remediation process of land flatness, farmland division and river diversion in the target area in the blank project according to the land remediation plan for the target area to obtain a pre-blank project; substitute the original DEM data into the pre-blank project to obtain a simulation model; Data comparison module: back up the pre-blank project; obtain the three-dimensional coordinate information of the target area after land consolidation, and process it with the SAR algorithm to obtain new DEM data; substitute the new DEM data into the pre-blank project to obtain the reference model; compare the reference model with the simulation model to obtain the land consolidation evaluation results; User interaction module: used to feed back land consolidation evaluation results to users.

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