Spatial evaluation method, system and device for off-road travel suitability of tracked vehicles

Abstract

The application discloses a kind of spatial evaluation method, system and device of off-road traffic suitability of tracked vehicle, comprising: evaluation element selection and analysis, and basic element is divided into specific specific factor, specific factor reflects different situations of basic element, according to basic element and specific factor, construct analytic hierarchy process model. Buffer zone and rasterization pretreatment are carried out to basic data using GIS software, and the weight value calculated by hierarchical model is given to each corresponding end evaluation factor. Spatial overlay analysis is carried out, and the threshold of the result is divided. The result is verified in situ, and the threshold division scheme is modified. The application has the advantages of: improving analysis efficiency, making the result more accurate.

Description

Technical Field

[0001] This invention relates to the field of environmental and spatial integrated analysis technology, and in particular to a spatial evaluation method, system and device for the off-road suitability of tracked vehicles. Background Technology

[0002] For vehicle mobility, road mobility is the main form of mobility. Vehicles are more efficient on roads with better conditions. However, in special circumstances such as military operations and earthquake relief, off-road mobility also plays a significant role. In particular, in military operations, the off-road mobility capability of vehicles is crucial to combat operations.

[0003] Tracked vehicles are designed to improve their adaptability to various road conditions and are crucial weapons in modern warfare. Their superior mobility and off-road capabilities are essential for navigating harsh battlefield environments. However, many factors limit the off-road capabilities of tracked vehicles, such as terrain slope, surface cover, and soil hardness. Therefore, studying the off-road performance of motor vehicles is of great significance and provides important reference for vehicle route planning. However, conducting real-world exercises with live vehicles not only requires substantial manpower, material resources, and financial investment, but also poses challenges to the safety of personnel and vehicles. Furthermore, it is not feasible to conduct real-world exercises in inaccessible areas, such as overseas locations.

[0004] The Analytic Hierarchy Process (AHP) is a multi-objective, multi-level comprehensive decision analysis method that organically combines qualitative analysis and quantitative calculation.

[0005] The steps of the Analytic Hierarchy Process (AHP) are generally as follows: establish a hierarchical analysis model of the system → compare factors at each level to construct a judgment matrix → calculate weights and perform consistency checks → determine the overall ranking of the importance weights of factors at each level.

[0006] The basic idea of ​​the Analytic Hierarchy Process (AHP) is to decompose a complex problem into several levels according to a recursive relationship, forming a hierarchical structure. Then, experts, scholars, and authorities are asked to compare the importance of each factor pairwise, express it quantitatively, and construct a pairwise comparison judgment matrix. The importance weights of each factor at each level are calculated and a consistency test is performed to obtain the combined weight value of the relative importance of the bottom level relative to the top level, and this is used as the basis for evaluating and selecting the solution.

[0007] The advantage of the Analytic Hierarchy Process (AHP) is that it can systematize, hierarchize, and simplify complex qualitative decision-making problems, and quantitative calculations can minimize the impact of subjective human factors on decision-making outcomes.

[0008] The Analytic Hierarchy Process (AHP) decomposes a problem into different components based on the ultimate goal, and then groups these components at different levels according to their interrelationships and hierarchical relationships, forming a multi-level analytical structure model. Elements at higher levels act as criteria, governing related elements at lower levels. Generally, there are three levels: ① The highest level, containing only one element, which is the ultimate goal to be achieved; hence, it is also called the goal level. ② The intermediate level, containing the intermediate steps taken to achieve the ultimate goal, consists of multiple levels. The criteria and sub-criteria needed to analyze the problem are included in this level; therefore, it is also called the criterion level or indicator level. ③ The lowest level, including various measures and decision-making schemes available to achieve the ultimate goal; therefore, it is also called the measure level, scheme level, or basic indicator level.

[0009] After constructing the theoretical model, the next step, constructing the judgment matrix, is a crucial step in the analytic hierarchy process (AHP). Based on the established recursive hierarchical model, weights are assigned to the importance of each factor at a given level to a factor at the level above it, from highest to lowest, thus completing the construction of the judgment matrix. Let U = {u1, u2, ..., um} be the set of evaluation factors, and uij represent the relative importance of ui to uj. The matrix format is as follows:

[0010]

[0011] The importance weights of the matrix are assigned according to the table below:

[0012] Table 1. Matrix Scale and Its Meaning

[0013]

[0014]

[0015] Based on the judgment matrix, using linear algebra, the eigenvector corresponding to the largest eigenvalue of the judgment is accurately calculated. After normalizing the eigenvector, the ranking of the weights of a factor at a certain level corresponding to a factor at the next higher level (hierarchical weights) is obtained.

[0016] To determine whether the judgment matrix is ​​constructed reasonably and free from logical contradictions, a consistency check is required. First, the largest eigenvalue and corresponding eigenvector of each judgment matrix must be calculated. Then, the consistency index, random consistency index, and consistency ratio are calculated. If the consistency ratio is less than 0.1, the constructed judgment matrix is ​​considered reasonable, and the normalized eigenvectors become the weight vectors. Otherwise, the elements of the judgment matrix need to be readjusted until a satisfactory consistency ratio is achieved. The methods and steps typically used to check the consistency of the judgment matrix are as follows:

[0017] a. Calculate the consistency index CI:

[0018]

[0019] In the formula, λmax is the largest eigenvalue; m is the order of the judgment matrix.

[0020] b. Calculate the test coefficient CR:

[0021] CR = CI / RI

[0022] In the formula, RI is the average random consistency index of the judgment matrix. Low-order (<11) judgment matrices are usually obtained by looking up a table (Table 2). For high-order (>11) judgment matrices, further research or approximation methods are required.

[0023] Table 2. Average Random Consistency Index (RI) values ​​for the Analytic Hierarchy Process (AHP).

[0024]

[0025] When CR < 0.1, the judgment matrix can be considered to have satisfactory consistency, that is, the constructed judgment matrix is ​​considered to be reasonable; otherwise, the judgment matrix needs to be readjusted until satisfactory consistency is achieved.

[0026] Spatial analysis primarily uncovers the potential information of spatial targets through the joint analysis of spatial data and spatial models. The basic information of these spatial targets includes their spatial location, distribution, morphology, distance, orientation, and topological relationships. Among these, distance, orientation, and topological relationships constitute the spatial relationships between spatial targets; these are the spatial characteristics between geographic entities and can serve as the basis for data organization, querying, analysis, and reasoning. By classifying geospatial targets into different types—points, lines, and polygons—the morphological structures of these different types of targets can be obtained. Combining the spatial data and attribute data of spatial targets enables spatial calculations and analyses for many specific tasks.

[0027] Spatial analysis methods include spatial information measurement, spatial information classification, buffer analysis, overlay analysis, network analysis, and spatial statistical analysis. This method primarily uses buffer analysis and overlay analysis. Buffer analysis automatically creates buffer polygons of a certain width around geographic entities such as points, lines, and polygons. Proximity describes the degree of closeness between two geographic features, and its determination is an important tool in spatial analysis. Features along transportation routes or rivers have unique importance; the service radius of public facilities, relocation caused by the construction of large reservoirs, and the importance of railways, highways, and waterways to the economic development of the areas they traverse all involve proximity issues. Buffer analysis is one of the spatial analysis tools for solving proximity problems. A buffer is a range of influence or service area for a geographic spatial target. Most GIS software organizes geographic landscapes in a layered manner, extracting geographic landscapes by theme, with the entire data layer set of the same region expressing the content of the geographic landscape of that region. Overlay analysis in Geographic Information Systems (GIS) is an operation that overlays data layers composed of related theme layers to produce a new data layer, the result of which integrates the attributes of the original two or more layers of elements. Overlay analysis includes not only the comparison of spatial relationships, but also the comparison of attribute relationships. Summary of the Invention

[0028] To address the shortcomings of existing technologies, this invention provides a spatial evaluation method, system, and device for the suitability of tracked vehicles for off-road travel. Based on fundamental geographic and geological data, an improved analytic hierarchy process (AHP) is used to establish a theoretical analysis model. Through GIS buffer analysis and spatial overlay analysis, the influence of geographic and geological elements on tracked vehicle off-road travel is measured by weight values, thereby quantitatively analyzing and evaluating whether a region is suitable for tracked vehicle travel.

[0029] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is as follows:

[0030] A spatial evaluation method for the off-road passability of tracked vehicles, specifically including the following steps:

[0031] Step 1: Selection and analysis of evaluation factors.

[0032] The basic elements selected for the thematic evaluation include: topographic slope, surface cover type, rock mass hardness, soil hardness, water bodies, roads, and geological hazards—a total of seven elements. These basic elements are further divided into specific factors, each reflecting different aspects of the basic elements.

[0033] Step 2: Construction of the hierarchical analysis model.

[0034] Based on the basic elements and specific factors selected in step one, construct a hierarchical analysis model.

[0035] The hierarchical analysis model is divided into three layers: the top layer, the middle layer, and the bottom layer.

[0036] The highest level has only one element, which refers to accessibility, denoted as A.

[0037] The intermediate layer refers to the factors influencing accessibility, the basic elements of step one, denoted as B. i , i = 1, 2, 3, ..., m, m is the total number of basic elements.

[0038] The lowest level refers to the specific factors influencing the factors in the previous level, denoted as C. j j = 1, 2, 3, ..., n, where n is the total number of evaluation factors.

[0039] Establish a judgment matrix for each level and perform a consistency check. Multiply the calculated weights of each factor in level C relative to a certain factor in level B by the weights of the corresponding factors in level B relative to level A to obtain the combined weights of each factor in level C relative to level A.

[0040] Step 3: Basic data processing and weighting.

[0041] Using GIS software, the basic data is buffered and rasterized for preprocessing, and the weight values ​​calculated by the hierarchical model are assigned to the corresponding end evaluation factors.

[0042] Step 4: Perform spatial overlay analysis and divide the results into thresholds.

[0043] The weighted geographic and geological data are spatially overlaid and analyzed to calculate the cumulative weight value of each unit pixel, resulting in the final evaluation raster data. An appropriate thresholding method is then used to classify the evaluation results into four categories: "good accessibility," "moderate accessibility," "poor accessibility," and "inaccessible."

[0044] Step 5: Verify the results in the field and modify the threshold division scheme.

[0045] On-site inspections of vehicle trafficability were conducted, and the evaluation results were used to reclassify any unreasonable thresholds, ensuring that the evaluation results were consistent with the actual situation.

[0046] Furthermore, the specific factors for step one are as follows:

[0047] The specific factors in terrain slope are classified into 0-5°, 5-10°, 10-15° and 15-25°, and areas with a slope greater than 25° are directly determined as impassable areas.

[0048] The specific factors in rock mass hardness are divided into: hard rock, relatively hard rock, relatively soft rock, soft rock, and extremely soft rock.

[0049] The specific factors in the water body are divided into multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km.

[0050] The specific factors of land cover are divided into six categories: forests, shrublands, grasslands, farmland, water bodies, and buildings.

[0051] The specific factors of soil hardness are divided into: rocky soil, hard soil, medium soil and soft soil.

[0052] The specific factors of the road are divided into multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km.

[0053] The specific factors of geological hazard points are divided into multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km.

[0054] The present invention also discloses a spatial evaluation system for the off-road suitability of tracked vehicles. This system can be used to implement the above-mentioned spatial evaluation method for the off-road suitability of tracked vehicles. Specifically, it includes: a data classification module, a hierarchical analysis model construction module, a basic data processing and weighting module, a result generation module, and a correction module.

[0055] Data Classification Module: Input basic element data, including: terrain slope, surface cover type, rock hardness, soil hardness, water bodies, roads, and geological hazards. The basic elements are then divided into specific factors, each reflecting different aspects of the basic elements.

[0056] Hierarchical Analysis Model Construction Module: Constructs a hierarchical analysis model based on the basic elements and specific factors selected in the data classification module.

[0057] The hierarchical analysis model is divided into three levels: the highest level, the middle level, and the lowest level.

[0058] Establish judgment matrices for each level and calculate the combined weights.

[0059] Basic data processing and weighting module: Utilizes GIS software to perform buffering and rasterization preprocessing on the basic data, and assigns the weight values ​​calculated by the hierarchical model to the corresponding end evaluation factors.

[0060] The results generation module performs spatial overlay analysis on the weighted geographic and geological data, calculates the cumulative weight value of each unit pixel, and obtains the final evaluation raster data. Using an appropriate thresholding method, the evaluation results are categorized into four classes: "Good Accessibility," "Medium Accessibility," "Poor Accessibility," and "Impossible Accessibility." The results are then generated and displayed on a map.

[0061] Correction module: Conduct on-site inspections of vehicle trafficability, evaluate the results, and reclassify any unreasonable threshold divisions to ensure that the evaluation results are consistent with the actual situation.

[0062] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-mentioned spatial evaluation method for off-road suitability of tracked vehicles.

[0063] The present invention also discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described spatial evaluation method for off-road suitability of tracked vehicles.

[0064] Compared with the prior art, the advantages of the present invention are as follows:

[0065] The Analytic Hierarchy Process (AHP) was used to systematically analyze the various influencing factors, scientifically and rationally assign corresponding weight values ​​to each factor, and combined with the spatial analysis function of GIS, the results of theoretical analysis were applied to spatial entities. The comprehensive evaluation gave the results of the thematic analysis, which improved the analysis efficiency and made the results more accurate. Attached Figure Description

[0066] Figure 1 This is a flowchart of the spatial evaluation method according to an embodiment of the present invention;

[0067] Figure 2 This is a schematic diagram of the hierarchical analysis model structure according to an embodiment of the present invention;

[0068] Figure 3 This is a weighted map of terrain slope elements according to an embodiment of the present invention;

[0069] Figure 4 This is a rock mass element weighting map according to an embodiment of the present invention;

[0070] Figure 5 This is a weighted map of water elements according to an embodiment of the present invention;

[0071] Figure 6 This is a weighted map of land cover elements according to an embodiment of the present invention;

[0072] Figure 7 This is a soil element weighting diagram according to an embodiment of the present invention;

[0073] Figure 8 This is a weighted map of road elements according to an embodiment of the present invention;

[0074] Figure 9 This is a weighted map of geological disaster elements according to an embodiment of the present invention;

[0075] Figure 10 This is a vehicle traffic suitability evaluation diagram according to an embodiment of the present invention. Detailed Implementation

[0076] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

[0077] like Figure 1 As shown, a spatial evaluation method for the off-road suitability of tracked vehicles includes the following steps:

[0078] Step 1: Selection and analysis of evaluation factors.

[0079] The basic elements selected for the thematic evaluation are: topographic slope, surface cover type, rock hardness, soil hardness, water body, road, and geological hazards.

[0080] Different slope conditions can have a significant impact on vehicle travel. Studies have shown that tracked vehicles are almost impossible to pass on slopes greater than 25°. In addition, due to other factors, areas with slopes above 25° are classified as impassable areas. Furthermore, the range of terrain slopes within 25° is subdivided into four types: 0-5°, 5-10°, 10-15°, and 15-25°.

[0081] The impact of ground cover on off-road passage of tracked vehicles is mainly manifested in its obstruction of vehicle movement. Based on the data obtained, ground cover is divided into six categories: forest, shrubland, grassland, farmland, water body and building.

[0082] The impact of roads on off-road traffic is considered as a proximity problem, and roads are classified into multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km.

[0083] The impact of water bodies on off-road access is considered as a proximity problem, and surface water is classified into multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km.

[0084] The impact of soil on vehicle traffic can be assessed by considering soil hardness. Soil can be classified into rocky soil, hard soil, medium soil, and soft soil based on its hardness.

[0085] The impact of rock masses on vehicle traffic can be assessed based on their hardness. Rock masses are classified into hard rock, relatively hard rock, relatively soft rock, soft rock, and extremely soft rock according to their hardness.

[0086] The impact of geological disasters on vehicle passability is considered as a proximity problem, and geological disaster sites are classified into multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km.

[0087] Step 2: Construction of the hierarchical analysis model.

[0088] Based on the evaluation elements and their detailed evaluation factors selected in Step One, a hierarchical analysis model is constructed. First, the problem to be solved is organized and hierarchically structured to construct a hierarchical analysis model. The model consists of three levels: the highest level, the middle level, and the lowest level. Figure 2 The highest layer has only one element, representing accessibility, denoted as A. The middle layer refers to factors influencing accessibility, such as terrain slope, surface cover, roads, and water bodies, denoted as B. i (i = 1, 2, 3, ..., m, where m is the total number of influencing factors). The lowest level refers to the specific factors of the influencing factors in the previous level. For example, terrain slope is further divided into 0-5°, 5-10°, 10-15°, and 15-25°, denoted as C. j (j = 1, 2, 3, ..., n, where n is the total number of evaluation factors).

[0089] Establish a judgment matrix for each level and perform a consistency check.

[0090] AB layer judgment matrix:

[0091]

[0092] B1 Element Judgment Matrix:

[0093] 0－5 1.00 3.00 5.00 8.00 0.5617 5－10 0.33 1.00 4.00 6.00 0.2851 10－15 0.20 0.25 1.00 3.00 0.1046 15－25 0.13 0.17 0.33 1.00 0.0485

[0094] B2 Element Judgment Matrix:

[0095]

[0096] B3 Element Judgment Matrix:

[0097]

[0098] B4 Element Judgment Matrix:

[0099]

[0100] B5 Element Judgment Matrix:

[0101]

[0102]

[0103] B6 Element Judgment Matrix:

[0104] 0.2 km 1.00 3.00 6.00 8.00 0.5755 0.5 km 0.33 1.00 4.00 6.00 0.2780 1 kilometer 0.17 0.25 1.00 3.00 0.0985 2 kilometers 0.13 0.17 0.33 1.00 0.0481

[0105] B7 Element Judgment Matrix:

[0106] 0.2 km 1.00 5.00 7.00 9.00 0.6546 0.5 km 0.20 1.00 3.00 6.00 0.2098 1 kilometer 0.14 0.33 1.00 3.00 0.0922 2 kilometers 0.11 0.17 0.33 1.00 0.0435

[0107] Write a program to calculate the eigenvalues ​​and eigenvectors of each judgment matrix, and then perform a consistency check on the calculation results.

[0108] Multiply the calculated weights of each factor in layer C relative to a certain factor in layer B by the weights of the corresponding factors in layer B relative to layer A to obtain the combined weights of each factor in layer C relative to layer A.

[0109] The overall weight information of the example model is as follows:

[0110]

[0111]

[0112] Step 3: Basic data processing and weighting.

[0113] The terrain slope data was generated using AsterGDem 30-meter spatial resolution data downloaded from the Geospatial Data Cloud (http: / / www.gscloud.cn / ). ArcGIS software was used to stitch and crop the data to produce slope data. The slope was then reclassified according to different levels, resulting in five categories: 0-5°, 5-10°, 10-15°, 15-25°, and greater than 25°. Weights were assigned to each category of factors. Figure 3 ).

[0114] Rock mass data were collected using 1:500,000 geological maps from the National Geological Archives (https: / / www.ngac.cn / ). Based on lithological descriptions, various rock stratigraphic data were transformed to express hardness. The data were then rasterized in ArcGIS software and assigned corresponding weights. Figure 4 ).

[0115] Surface water data was obtained from publicly available data downloaded using software such as Water Resources Reporting or 91-bitmap. GIS software was used to create multi-ring buffer zones of 0.2 km, 0.5 km, 1 km, and 2 km for linear water systems and areal water bodies, which were then rasterized and assigned corresponding weights. Figure 5 ).

[0116] Land cover uses publicly available online land use cover databases ( http: / / data.ess.tsingh The data downloaded from ua.edu.cn / fromglc10_2017v01.html was merged into corresponding categories, and then assigned corresponding weight values ​​to six categories: arbor forests, shrub forests, grasslands, farmland, water bodies, and buildings. Figure 6 Since land cover generally hinders vehicle traffic, all land cover factors are assigned negative gain weights.

[0117] Soil elements are derived from remote sensing data. The remote sensing interpretation first identifies the soil type, and then, based on general principles, classifies the soil data into hardness categories such as stony soil, hard soil, medium soil, and soft soil. After rasterization, corresponding weight values ​​are assigned. Figure 7 ).

[0118] Road elements were constructed using publicly available road network vector data downloaded from software such as Shuijingzhu or 91-bitmap. Multi-ring buffers of 0.2 km, 0.5 km, 1 km, and 2 km were created for each road element, followed by data rasterization and assignment of corresponding weight values. Figure 8 ).

[0119] Geological hazard elements are derived from remote sensing-interpreted geological hazard data. Multiple buffer zones of 0.2 km, 0.5 km, 1 km, and 2 km are established for geological hazard points, and after rasterization, corresponding weight values ​​are assigned. Figure 9 ).

[0120] Step 4: Perform spatial overlay analysis and divide the results into thresholds.

[0121] The weighted geographic and geological data are spatially overlaid to calculate the cumulative weight value of each unit pixel, resulting in the final evaluation raster data. Using Jenks' natural discontinuity grading method, the evaluation results are categorized into four classes: "Good Accessibility," "Medium Accessibility," "Poor Accessibility," and "Impossible Accessibility." Figure 10 ).

[0122] Step 5: Verify the results in the field and modify the threshold division scheme.

[0123] The suitability of vehicle traffic was assessed on-site. Based on the threshold classification results from step four, any unreasonable threshold classifications were reclassified to ensure that the evaluation results were consistent with the actual situation.

[0124] In another embodiment of the present invention, a spatial evaluation system for off-road suitability of tracked vehicles is provided. This system can be used to implement the above-mentioned spatial evaluation method for off-road suitability of tracked vehicles. Specifically, it includes: a data classification module, a hierarchical analysis model construction module, a basic data processing and weighting module, a result generation module, and a correction module.

[0125] Data Classification Module: Input basic element data, including: terrain slope, surface cover type, rock hardness, soil hardness, water bodies, roads, and geological hazards. The basic elements are then divided into specific factors, each reflecting different aspects of the basic elements.

[0126] Hierarchical Analysis Model Construction Module: Constructs a hierarchical analysis model based on the basic elements and specific factors selected in the data classification module.

[0127] The hierarchical analysis model is divided into three levels: the highest level, the middle level, and the lowest level.

[0128] Establish judgment matrices for each level and calculate the combined weights.

[0129] Basic data processing and weighting module: Utilizes GIS software to perform buffering and rasterization preprocessing on the basic data, and assigns the weight values ​​calculated by the hierarchical model to the corresponding end evaluation factors.

[0130] The results generation module performs spatial overlay analysis on the weighted geographic and geological data, calculates the cumulative weight value of each unit pixel, and obtains the final evaluation raster data. Using an appropriate thresholding method, the evaluation results are categorized into four classes: "Good Accessibility," "Medium Accessibility," "Poor Accessibility," and "Impossible Accessibility." The results are then generated and displayed on a map.

[0131] Correction module: Conduct on-site inspections of vehicle trafficability, evaluate the results, and reclassify any unreasonable threshold divisions to ensure that the evaluation results are consistent with the actual situation.

[0132] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment can be used in the operation of a spatial evaluation method for the off-road suitability of tracked vehicles, including the following steps:

[0133] Step 1: Selection and analysis of evaluation factors.

[0134] The basic elements selected for the thematic evaluation include: topographic slope, surface cover type, rock mass hardness, soil hardness, water bodies, roads, and geological hazards—a total of seven elements. These basic elements are further divided into specific factors, each reflecting different aspects of the basic elements.

[0135] Step 2: Construction of the hierarchical analysis model.

[0136] Based on the basic elements and specific factors selected in step one, construct a hierarchical analysis model.

[0137] The hierarchical analysis model is divided into three layers: the top layer, the middle layer, and the bottom layer.

[0138] The highest level has only one element, which refers to accessibility, denoted as A.

[0139] The intermediate layer refers to the factors influencing accessibility, the basic elements of step one, denoted as B. i , i = 1, 2, 3, ..., m, m is the total number of basic elements.

[0140] The lowest level refers to the specific factors influencing the factors in the previous level, denoted as C. j j = 1, 2, 3, ..., n, where n is the total number of evaluation factors.

[0141] Establish a judgment matrix for each level and perform a consistency check. Multiply the calculated weights of each factor in level C relative to a certain factor in level B by the weights of the corresponding factors in level B relative to level A to obtain the combined weights of each factor in level C relative to level A.

[0142] Step 3: Basic data processing and weighting.

[0143] Using GIS software, the basic data is buffered and rasterized for preprocessing, and the weight values ​​calculated by the hierarchical model are assigned to the corresponding end evaluation factors.

[0144] Step 4: Perform spatial overlay analysis and divide the results into thresholds.

[0145] The weighted geographic and geological data are spatially overlaid and analyzed to calculate the cumulative weight value of each unit pixel, resulting in the final evaluation raster data. An appropriate thresholding method is then used to classify the evaluation results into four categories: "good accessibility," "moderate accessibility," "poor accessibility," and "inaccessible."

[0146] Step 5: Verify the results in the field and modify the threshold division scheme.

[0147] On-site inspections of vehicle trafficability were conducted, and the evaluation results were used to reclassify any unreasonable thresholds, ensuring that the evaluation results were consistent with the actual situation.

[0148] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory). This computer-readable storage medium is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0149] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the spatial evaluation method for off-road suitability of tracked vehicles in the above embodiments; one or more instructions in the computer-readable storage medium are loaded by the processor and executed as follows:

[0150] Step 1: Selection and analysis of evaluation factors.

[0151] The basic elements selected for the thematic evaluation include: topographic slope, surface cover type, rock mass hardness, soil hardness, water bodies, roads, and geological hazards—a total of seven elements. These basic elements are further divided into specific factors, each reflecting different aspects of the basic elements.

[0152] Step 2: Construction of the hierarchical analysis model.

[0153] Based on the basic elements and specific factors selected in step one, construct a hierarchical analysis model.

[0154] The hierarchical analysis model is divided into three layers: the top layer, the middle layer, and the bottom layer.

[0155] The highest level has only one element, which refers to accessibility, denoted as A.

[0156] The intermediate layer refers to the factors influencing accessibility, the basic elements of step one, denoted as B. i , i = 1, 2, 3, ..., m, m is the total number of basic elements.

[0157] The lowest level refers to the specific factors influencing the factors in the previous level, denoted as C. j j = 1, 2, 3, ..., n, where n is the total number of evaluation factors.

[0158] Establish a judgment matrix for each level and perform a consistency check. Multiply the calculated weights of each factor in level C relative to a certain factor in level B by the weights of the corresponding factors in level B relative to level A to obtain the combined weights of each factor in level C relative to level A.

[0159] Step 3: Basic data processing and weighting.

[0160] Using GIS software, the basic data is buffered and rasterized for preprocessing, and the weight values ​​calculated by the hierarchical model are assigned to the corresponding end evaluation factors.

[0161] Step 4: Perform spatial overlay analysis and divide the results into thresholds.

[0162] The weighted geographic and geological data are spatially overlaid and analyzed to calculate the cumulative weight value of each unit pixel, resulting in the final evaluation raster data. An appropriate thresholding method is then used to classify the evaluation results into four categories: "good accessibility," "moderate accessibility," "poor accessibility," and "inaccessible."

[0163] Step 5: Verify the results in the field and modify the threshold division scheme.

[0164] On-site inspections of vehicle trafficability were conducted, and the evaluation results were used to reclassify any unreasonable thresholds, ensuring that the evaluation results were consistent with the actual situation.

[0165] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0166] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0167] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0168] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0169] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the implementation methods of the present invention, and should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of the present invention.

Claims

1. A spatial evaluation method for the off-road passability of tracked vehicles, characterized in that, Specifically, the following steps are included: Step 1: Selection and analysis of evaluation factors; The basic elements selected for the thematic evaluation include: topographic slope, surface cover type, rock mass hardness, soil hardness, water body, roads, and geological hazards, totaling seven basic elements; and the basic elements are further divided into specific factors, which reflect different situations of the basic elements; for the topographic slope element, areas with a slope greater than 25° are directly identified as impassable areas. Step 2: Construction of the Hierarchical Analysis Model; Based on the basic elements and specific factors selected in step one, construct a hierarchical analysis model; The hierarchical analysis model consists of three layers: the top layer, the middle layer, and the bottom layer. The highest level has only one element, which refers to accessibility, denoted as A; The intermediate layer refers to the factors influencing accessibility, the basic elements of step one, denoted as B. i , i = 1, 2, 3, ..., m, m is the total number of basic elements; The lowest level refers to the specific factors influencing the factors in the previous level, denoted as C. j j = 1, 2, 3, ..., n, where n is the total number of evaluation factors; A judgment matrix is ​​established for each level, and a consistency check is performed. The weights of each factor in level C relative to a certain factor in level B are multiplied by the weights of the corresponding factors in level B relative to level A to obtain the combined weights of each factor in level C relative to level A. The combined weights are assigned according to the promoting or hindering effect of each specific factor on the off-road passage of tracked vehicles, and are divided into positive gain weights or negative gain weights. Step 3: Basic data processing and weighting; Using GIS software, the basic data is buffered and rasterized preprocessed. For water bodies, roads and geological disaster points, multi-ring buffers are generated as their specific factors. The weight values ​​calculated by the hierarchical model are assigned to the corresponding end evaluation factors. Step 4: Perform spatial overlay analysis and determine the threshold values ​​for the results; The weighted geographic and geological data are spatially overlaid and analyzed to calculate the cumulative weight value of each unit pixel, thus obtaining the final evaluation raster data. An appropriate threshold division method is used to divide the evaluation results into four categories: "good accessibility", "medium accessibility", "poor accessibility" and "inaccessible". Step 5: Verify the results in the field and modify the threshold division scheme; On-site inspections of vehicle trafficability were conducted, and the evaluation results were used to reclassify any unreasonable thresholds, ensuring that the evaluation results were consistent with the actual situation.

2. The spatial evaluation method for off-road passability of tracked vehicles according to claim 1, characterized in that: The specific factors for step one are as follows: The specific factors in terrain slope are classified into 0-5°, 5-10°, 10-15° and 15-25°, and areas with a slope greater than 25° are directly determined to be impassable areas; The specific factors in rock mass hardness are divided into: hard rock, relatively hard rock, relatively soft rock, soft rock, and extremely soft rock; The specific factors in the water body are divided into multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km. The specific factors of land cover are divided into six categories: forests, shrublands, grasslands, farmland, water bodies, and buildings; The specific factors of soil hardness are divided into: rocky soil, hard soil, medium soil and soft soil; The specific factors of the road are divided into: multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km; The specific factors of geological hazard points are divided into multi-ring buffer zones of 0.2 km, 0.5 km, 1 km and 2 km.

3. A spatial evaluation system for the off-road suitability of tracked vehicles, characterized in that: This system can be used to implement the spatial evaluation method for off-road passability of tracked vehicles as described in claim 1 or 2. The system includes: a data classification module, a hierarchical analysis model construction module, a basic data processing and weighting module, a result generation module, and a correction module. Data classification module: Input basic element data, including: terrain slope, surface cover type, rock hardness, soil hardness, water body, roads, and geological hazards; and divide the basic elements into specific factors, which reflect the different situations of the basic elements; Hierarchical Analysis Model Construction Module: Constructs a hierarchical analysis model based on the basic elements and specific factors selected in the data classification module; The hierarchical analysis model consists of three layers: the top layer, the middle layer, and the bottom layer. Establish judgment matrices for each level and calculate the combined weights; Basic data processing and weighting module: Utilizes GIS software to perform buffering and rasterization preprocessing on basic data, and assigns the weight values ​​calculated by the hierarchical model to the corresponding end evaluation factors; Results generation module: Performs spatial overlay analysis on the weighted geographic and geological data, calculates the cumulative weight value of each unit pixel, and obtains the final evaluation raster data; uses an appropriate threshold division method to divide the evaluation results into four categories: "good accessibility", "medium accessibility", "poor accessibility" and "inaccessible"; and generates and displays the results on the map. Correction module: Conduct on-site inspections of vehicle trafficability, evaluate the results, and reclassify any unreasonable threshold divisions to ensure that the evaluation results are consistent with the actual situation.

4. A computer device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the spatial evaluation method for off-road suitability of tracked vehicles as described in claim 1 or 2.

5. A computer-readable storage medium, characterized in that: The system contains a computer program that, when executed by a processor, implements the spatial evaluation method for off-road suitability of tracked vehicles as described in claim 1 or 2.

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