Method and device for evaluating suitability of camping site selection area

Abstract

The invention discloses a suitability evaluation method and device for a site selection area of a camping site, and belongs to the technical field of camping site planning, and the method comprises the steps: obtaining a research area corresponding to the site selection area of the camping site, suitability factor data and limiting factor data; acquiring a historical camping area and a non-camping area in the research area; calculating a weight value of the suitability factor data based on the suitability factor data of the historical camping area and the suitability factor data of the non-camping area; setting a weight value of the limiting factor data as a preset value; and performing weighted summation on the suitability factor data and the limiting factor data based on the weight value of the suitability factor data and the weight value of the limiting factor data to obtain a score of the site selection area of the camping site. According to the method, the historical data of the research area is mined and analyzed, an objective and reliable basis is provided for scoring of the site selection area of the camping site, and the flexibility and adaptability of scoring are improved by setting the weight value of the limiting factor data as the preset value.

Description

Technical Field

[0001] The present application belongs to the technical field of campsite planning, and specifically relates to a method and device for evaluating the suitability of a campsite site selection area. Background Art

[0002] In recent years, outdoor camping activities have gradually become a popular leisure and entertainment activity for the public, and have become an emerging form of tourism. Scientific and accurate campsite site selection can significantly improve the tourism experience and economic benefits, enhance the experience of campers, not only provide a comfortable, safe and convenient environment, attract more tourists to camp, but also optimize the location of campsites, effectively utilize natural landscapes and existing resources, and improve the overall tourism quality and competitiveness. At the same time, in the site selection process, considering environmental factors such as ecologically sensitive areas, wildlife habitats and water source protection areas can significantly reduce the negative impact on the natural environment. By rationally planning campsites, the development of sustainable tourism can be promoted, and a win-win situation between ecological protection and tourism development can be achieved. In summary, the study of campsite site selection methods has important practical significance and broad application prospects. Scientific and reasonable campsite site selection methods are of great significance to achieving scientific decision-making, optimizing resource allocation and promoting sustainable tourism development, and provide strong support for relevant policy formulation and practice.

[0003] The existing camping site selection usually adopts the expert scoring method to select camping sites. The existing camping area evaluation method usually has one or more of the following shortcomings: 1. The evaluation index is single-level; 2. The applicable area is limited; 3. The subjective will of people occupies too much weight in the evaluation process and lacks objectivity. Summary of the invention

[0004] The purpose of this application is to provide a method and device for evaluating the suitability of a camping site selection area to solve the problem of difficulty in selecting a camping site.

[0005] According to a first aspect of an embodiment of the present application, a method for evaluating the suitability of a campsite selection area is provided, and the method may include:

[0006] Obtain the study area, suitability factor data, and restriction factor data corresponding to the campsite site selection area;

[0007] Obtaining historical campground areas and non-campground areas within the study area;

[0008] Calculating a weight value of the suitability factor data based on the suitability factor data of the historical camping area and the suitability factor data of the non-camping area;

[0009] Setting the weight value of the limiting factor data to a preset value;

[0010] The suitability factor data and the restriction factor data are weighted and summed based on the weight value of the suitability factor data and the weight value of the restriction factor data to obtain a score for the camping site selection area.

[0011] In some optional embodiments of the present application, calculating the weight value of the suitability factor data based on the suitability factor data of the historical camping area and the suitability factor data of the non-camping area includes:

[0012] Establishing a campsite location probability prediction model based on the suitability factor data of the historical campsite area and the suitability factor data of the non-campsite area;

[0013] Calculating the contribution of the suitability factor to the campsite site selection probability prediction model;

[0014] A weight value of the suitability factor is assigned based on the contribution degree.

[0015] In some optional embodiments of the present application, a campsite location probability prediction model is established based on the suitability factor data of the historical campsite area and the suitability factor data of the non-campsite area, including:

[0016] Taking the suitability factor data of the historical camping area and the suitability factor data of the non-camping area as input variables, and taking whether it is a camping area as a label to construct a model training data set;

[0017] Training multiple initial classification models using the model training data set to obtain multiple site selection classification models;

[0018] Obtaining a performance indicator of each of the site selection classification models;

[0019] A campsite site selection probability prediction model is selected from the site selection classification model based on the performance index.

[0020] In some optional embodiments of the present application, the performance indicator includes an area under a curve;

[0021] The calculation formula for the area under the curve is as follows:

[0022]

[0023] Wherein, N is the suitability factor data of the non-camping area, P is the suitability factor data of the historical camping area, TN is the number of the historical camping areas correctly classified, and TP is the number of the non-camping areas correctly classified.

[0024] In some optional embodiments of the present application, the performance indicator includes classification accuracy;

[0025] The calculation formula of the classification accuracy is as follows:

[0026]

[0027] Wherein, TP is the number of the historical camping areas that are correctly classified, TN is the number of the non-camping areas that are correctly classified, FP is the number of the historical camping areas that are incorrectly classified, and FN is the number of the non-camping areas that are incorrectly classified.

[0028] In some optional embodiments of the present application, the calculation formula of the contribution value is as follows:

[0029]

[0030] in, is the contribution value of the i-th suitability factor data, S is a subset of the suitability factor data, N is a set of the suitability factor data, and f(S) is the output of the campsite location probability prediction model on the subset S of the suitability factor data.

[0031] In some optional embodiments of the present application, the campsite location probability prediction model includes one or more of the following models: random forest, gradient boosting regression tree, extreme gradient boosting.

[0032] In some optional embodiments of the present application, obtaining the historical camping area and non-camping area in the study area includes:

[0033] Initial historical campsites in the study area were web crawled;

[0034] spatially overlaying and matching the remote sensing image of the study area with the initial historical campsite;

[0035] The initial historical campsite that is successfully matched is used as a historical campsite;

[0036] A preset number of non-camping sites were randomly selected from the study area.

[0037] In some optional embodiments of the present application, the suitability factor data includes terrain data, ecological data and traffic data;

[0038] The terrain data includes elevation, slope, soil conditions and land type;

[0039] The ecological data include temperature, precipitation, air quality index and water resources;

[0040] The traffic data includes the distance between the camping area and the road, the distance between the camping area and the train station, and the distance between the camping area and the airport.

[0041] In some optional embodiments of the present application, the limiting factor data includes risk disaster data and ecological protection data;

[0042] The risk disaster data include landslides, ice and snow disasters and floods;

[0043] The ecological inclusion data includes natural ecological protection areas.

[0044] According to a second aspect of an embodiment of the present application, a device for evaluating the suitability of a camping site selection area is provided, comprising:

[0045] The first acquisition module acquires the research area, suitability factor data and restriction factor data corresponding to the camping site selection area;

[0046] A second acquisition module is used to acquire historical camping areas and non-camping areas within the study area;

[0047] A first data processing module, configured to calculate a weight value of the suitability factor data based on the suitability factor data of the historical camping area and the suitability factor data of the non-camping area;

[0048] A second data processing module, used for setting the weight value of the restriction factor data to a preset value;

[0049] A scoring module is used to perform weighted summation of the suitability factor data and the restriction factor data based on the weight value of the suitability factor data and the weight value of the restriction factor data to obtain a score for the camping site selection area.

[0050] According to a third aspect of an embodiment of the present application, an electronic device is provided, which may include:

[0051] processor;

[0052] a memory for storing processor-executable instructions;

[0053] The processor is configured to execute instructions to implement the method for evaluating the suitability of a camping site selection area as described in any one of the embodiments of the first aspect.

[0054] The above technical solution of the present application has the following beneficial technical effects:

[0055] A method for evaluating the suitability of a campsite site selection area provided in an embodiment of the present application calculates the weight values ​​of suitability factor data by mining and analyzing the historical data of the study area, so that the weight values ​​of the suitability factor data can characterize the historical patterns and trends of campsite development, providing an objective and reliable basis for the scoring of campsite site selection areas, helping to improve the scientificity and accuracy of the scoring, and by setting the weight values ​​of the restriction factor data to preset values, it is possible to provide targeted site selection recommendations based on the needs of decision makers, helping to improve the flexibility and adaptability of the scoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flow chart of a method for evaluating the suitability of a camping site selection area in an exemplary embodiment of the present application;

[0057] Figure 2 is a flowchart of step S103 in an exemplary embodiment of the present application;

[0058] Figure 3 is a flowchart of step S1031 in an exemplary embodiment of the present application;

[0059] Figure 4 is a flowchart of step S102 in an exemplary embodiment of the present application;

[0060] Figure 5 is a flow chart of a method for evaluating the suitability of a camping site selection area in another exemplary embodiment of the present application;

[0061] Figure 6 It is a schematic diagram of the structure of a suitability evaluation device for a camping site selection area in an exemplary embodiment of the present application;

[0062] Figure 7 is a schematic diagram of the structure of an electronic device in an exemplary embodiment of the present application;

[0063] Figure 8 It is a schematic diagram of the hardware structure of an electronic device in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with specific implementations and with reference to the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present application. In addition, in the following description, the description of known structures and technologies is omitted to avoid unnecessary confusion of the concepts of the present application.

[0065] The accompanying drawings show schematic diagrams of layer structures according to embodiments of the present application. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clarity. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0066] Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0067] In the description of the present application, it should be noted that the terms "first", "second" and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0068] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0069] The study found that when establishing a campsite suitability model, the first thing to do is to determine the evaluation indicators. It is necessary to determine the various factors that affect the suitability of the campsite, which may include geographical location, traffic accessibility, terrain conditions, ecological environment, landscape quality, safety, etc. The evaluation indicators are divided into different categories, such as natural environment indicators, socioeconomic indicators, facility service indicators, etc., to facilitate systematic analysis. Secondly, each evaluation indicator is quantified to ensure that they can be objectively compared and evaluated. Finally, an evaluation model is established. According to the quantified indicators and the determined weights, a comprehensive evaluation model is established. Based on the suitability scores calculated by the evaluation model, all potential campsites are ranked and the areas with the highest scores are selected as campsites.

[0070] In conjunction with the accompanying drawings, the suitability evaluation method for a campsite selection area, the suitability evaluation device for a campsite selection area, and the electronic device provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

[0071] like Figure 1 As shown, in a first aspect of an embodiment of the present application, a method for evaluating the suitability of a camping site selection area is provided, and the method may include:

[0072] Step S101: obtaining the research area, suitability factor data and restriction factor data corresponding to the camping site selection area;

[0073] Step S102: Acquire historical camping areas and non-camping areas within the study area;

[0074] Step S103: Calculating weight values ​​of suitability factor data based on suitability factor data of historical camping areas and suitability factor data of non-camping areas;

[0075] Step S104: setting the weight value of the restriction factor data to a preset value;

[0076] Step S105: Based on the weight value of the suitability factor data and the weight value of the restriction factor data, weighted sum is performed on the suitability factor data and the restriction factor data to obtain a score for the campsite site selection area.

[0077] In this embodiment, the study area may be the area where the camping site selection area is located, the area of ​​the study area may be greater than or equal to 10 times the area of ​​the camping site selection area, and the study area may be greater than or equal to 50 times the area of ​​the camping site selection area. The study area may have the same topography and landform as the camping area. The ratio of the number of historical camping areas and non-camping areas may be 1:1, 1:2 or 1:4. The weight value of the suitability factor data is used to characterize the degree of influence of the suitability factor data on the camping site selection in the study area. The number of suitability factor data may be multiple, and those skilled in the art may select the suitability factor data according to actual needs. The suitability factor data may include terrain data, ecological data and traffic data; the terrain data includes elevation, slope, soil conditions and land type; the ecological data includes temperature, precipitation, air quality index and water resources; the traffic data includes the distance between the camping area and the road, the distance between the camping area and the railway station, and the distance between the camping area and the airport. The number of limiting factor data may be multiple, and those skilled in the art may select limiting factor data according to actual needs. The limiting factor data may include risk disaster data and ecological protection data; the risk disaster data include landslides, ice and snow disasters and floods; the ecological inclusion data include natural ecological protection areas. The preset value may be greater than the weight value of the suitability factor data. The score of the campsite site selection area can be obtained by weighted summation of the suitability factor data and the limiting factor data.

[0078] A method for evaluating the suitability of a campsite site selection area provided in this embodiment calculates the weight values ​​of suitability factor data by mining and analyzing the historical data of the study area, so that the weight values ​​of the suitability factor data can characterize the historical patterns and trends of campsite development, providing an objective and reliable basis for the scoring of campsite site selection areas, helping to improve the scientificity and accuracy of the scoring, and by setting the weight values ​​of the restriction factor data to preset values, it is possible to provide targeted site selection recommendations based on the needs of decision makers, helping to improve the flexibility and adaptability of the scoring.

[0079] like Figure 2As shown, in some embodiments, step S103 may include:

[0080] Step S1031: establishing a campsite location probability prediction model based on the suitability factor data of historical campsite areas and the suitability factor data of non-campsite areas;

[0081] Step S1032: Calculate the contribution of the suitability factor to the campsite site selection probability prediction model;

[0082] Step S1033: assigning weight values ​​to suitability factors based on the contribution.

[0083] In this embodiment, the campsite site selection probability prediction model includes one or more of the following models: random forest, gradient boosting regression tree, extreme gradient boosting. The calculation formula of the contribution value is as follows:

[0084]

[0085] in, is the contribution value of the i-th suitability factor data, S is the subset of suitability factor data, N is the set of suitability factor data, and f(S) is the output of the campsite location probability prediction model on the subset S of suitability factor data.

[0086] like Figure 3 As shown, in some embodiments, step S1031 may include:

[0087] Step S10311: using the suitability factor data of the historical camping area and the suitability factor data of the non-camping area as input variables, and using whether it is a camping site as a label to construct a model training data set;

[0088] Step S10312: training multiple initial classification models using a model training data set to obtain multiple site selection classification models;

[0089] Step S10313: Obtaining performance indicators of each site selection classification model;

[0090] Step S10314: Select a campsite site selection probability prediction model from the site selection classification model based on the performance index.

[0091] In this embodiment, the performance index can be obtained by weighted summation of the area under the curve and the classification accuracy;

[0092] The area under the curve is calculated as follows:

[0093]

[0094] Where N is the suitability factor data for non-campsite areas, P is the suitability factor data for historical campsite areas, TN is the number of correctly classified historical campsite areas, and TP is the number of correctly classified non-campsite areas.

[0095] The calculation formula for classification accuracy is as follows:

[0096]

[0097] Where TP is the number of historical campground areas that were correctly classified, TN is the number of non-campground areas that were correctly classified, FP is the number of historical campground areas that were incorrectly classified, and FN is the number of non-campground areas that were incorrectly classified.

[0098] like Figure 4 As shown, in some embodiments, step S102 may include:

[0099] Step S1021: crawling the initial historical campsites in the study area through the Internet;

[0100] Step S1022: spatially overlay and match the remote sensing image of the study area with the initial historical campsite;

[0101] Step S1023: taking the successfully matched initial historical campsite as the historical campsite;

[0102] Step S1024: randomly select a preset number of non-camping sites from the study area.

[0103] like Figure 5 As shown, in some embodiments, the method for evaluating the suitability of a camping site selection area includes the following steps:

[0104] Step 1: Construction of campsite site suitability evaluation system

[0105] Step 1A: Construct a campsite location restriction factor layer.

[0106] When constructing the campsite site suitability evaluation system, we first focus on the selection and analysis of the restrictive factor indicator layer to ensure that the site selection process can comprehensively evaluate and eliminate potential natural risks and ecological interference. The restrictive factor indicator layer includes risk disasters and ecological protection. The risk disaster indicator layer includes factors such as landslides, ice and snow disasters, and flood-prone areas. Ecological protection refers to natural ecological protection areas.

[0107] Step 1B: Construct a campsite location suitability factor layer.

[0108] On the basis of establishing limiting factors, we further construct the suitability factors for campsite site selection, comprehensively consider a series of key suitability factors, and select terrain data, ecological data, and transportation data as the suitability factor indicator layer. Terrain data is the cornerstone of evaluating the suitability of campsite site selection, and elevation, slope, soil conditions, and land type are considered as suitability factors; the quality of ecological data is directly related to the sustainable development of the campsite and the quality of tourists' experience, and factors such as temperature, precipitation, air quality index, and water resources are included in the suitability factors; convenient transportation facilities play a decisive role in the accessibility and tourist flow of the campsite, and the distance to the nearest road, railway station, and airport are used as suitability factors.

[0109] Step 1C: Construct a campsite site suitability evaluation system.

[0110] The restrictive factors and suitability factors are combined to construct a campsite site suitability evaluation system. According to the evaluation index system, relevant suitability factor data are collected and standardized to eliminate the impact of different data sources and different measurement units.

[0111] Step 2: Regional campsite data mining

[0112] Step 2A: Collect POI data of campsites within the study area based on web crawler technology

[0113] Using web crawler technology in Python and the API service provided by Amap, we developed an automated script to send customized query requests, extract POI data of historical campsites in the study area, parse the POI data, extract and export key information, such as POI name, longitude and latitude coordinates, detailed address, etc. Based on the coordinates of the exported data, we obtained the spatial distribution of the campsite POI data.

[0114] Step 2B: Campsite POI data cleaning

[0115] Using geographic information system technology, POI data and remote sensing image data are spatially superimposed to identify and delete camping sites in POI data that do not match the remote sensing image features, such as incorrectly marked buildings, and update the camping site POI dataset in the area. Feature matching failed

[0116] Step 3: Evaluation index weight allocation

[0117] Step 3A: Campsite location modeling based on multiple machine learning models

[0118] According to the updated POI data of historical campsite areas, the suitability factor data of the same number of non-campsite areas were obtained by random sampling to form a new comprehensive data set, which was divided into a model training set and a validation set at a ratio of 80% and 20%. The extracted suitability factor data of historical campsite areas and non-campsite areas were used as independent variables of the model, and the 0 or 1 value of whether each sample was a campsite was used as the dependent variable. Common machine learning models in classification tasks were selected, such as random forest, gradient boosting regression tree, extreme gradient boosting, etc. The training set was used to train each machine learning model, and the model parameters were adjusted to obtain the best performance. The prediction ability of the model was evaluated using the validation set.

[0119] Step 3B: Obtain the best learning model for the region based on multiple machine learning performances

[0120] Appropriate evaluation indicators, such as the area under the Receiver Operating Characteristic curve (ROC) curve (Area Under the Curve, AUC), classification accuracy, etc., are used to evaluate the predictive performance of the model.

[0121]

[0122] Where N is the suitability factor data for non-campsite areas, P is the suitability factor data for historical campsite areas, TN is the number of correctly classified historical campsite areas, and TP is the number of correctly classified non-campsite areas.

[0123]

[0124] Where TP is the number of historical campground areas that were correctly classified, TN is the number of non-campground areas that were correctly classified, FP is the number of historical campground areas that were incorrectly classified, and FN is the number of non-campground areas that were incorrectly classified.

[0125] Step 3C: Use interpretable machine learning techniques to obtain evaluation factor weights

[0126] By comparing the performance of various machine learning models, we identified the best campsite location probability prediction model on the regional campsite dataset, and used SHAP (SHapley Additive exPlanations) technology to determine the contribution of each suitability factor data to the predicted variable. The SHAP value provides a unified measure to evaluate the importance of suitability factor data. Based on the results of the SHAP value analysis, weights are assigned to each suitability factor data, which reflect the importance and contribution level of the suitability factor data in the model prediction. The Shapley value can be obtained as follows:

[0127]

[0128] in, is the contribution value of the i-th suitability factor data, S is the subset of suitability factor data, N is the set of suitability factor data, and f(S) is the output of the campsite location probability prediction model on the subset S of suitability factor data.

[0129] Step 4: Determination of comprehensive evaluation model for regional campsite site selection

[0130] Step 4A: Establish a comprehensive evaluation model based on the evaluation indicators and determined weights.

[0131] Based on the constructed suitability evaluation system and the weights of each evaluation factor, a comprehensive evaluation model is established, in which the weight of the restrictive factor data is set to zero, and the weight value of the suitability factor data is obtained according to step 3C. The weighted overlay method is used to combine the weight of each suitability factor data with its corresponding spatial distribution data for comprehensive scoring. The formula for weighted overlay is:

[0132]

[0133] S is the comprehensive score, x i is the i-th suitability factor data, w i is x i The weight of .

[0134] Step 5: Verification of the comprehensive evaluation model for regional campsite site selection

[0135] Step 5A: Calculate suitability scores for campsites within the study area.

[0136] The comprehensive evaluation model for campsite site selection is applied to the selected campsite site selection area. The suitability of the campsite site selection area at each location in the area is scored through the model's built-in algorithm and weight allocation.

[0137] Step 5B: Get the best camping site based on the suitability score ranking results.

[0138] The model output results were visualized to form a spatial distribution map of the suitability of campsites in the study area, and the suitability scores output by the model were ranked and analyzed to identify campsite site selection areas with high scores as the best campsites.

[0139] Step 5C: Conduct field visits to verify the practical applicability of the evaluation system.

[0140] According to the final model evaluation results, field investigations are conducted to verify the actual applicability of the evaluation system. Based on field observations, the evaluation indicators and weights in the comprehensive evaluation model can be adjusted.

[0141] The suitability evaluation method for camping site selection area provided in this embodiment has the following advantages:

[0142] 1. Comprehensively consider the restrictive factors and suitable factors of campsites and build a regional suitability evaluation system

[0143] The evaluation system can provide a more comprehensive assessment by comprehensively considering multiple constraint factor data and suitability factor data. By incorporating constraint factor data (such as ecological protection areas and disaster risk areas), it can not only identify and exclude high-risk areas, reduce the natural and man-made risks that may be encountered during campsite development, but also protect the environment and cultural heritage and promote the ecological sustainability of campsite site selection.

[0144] 2. Fully tap into the prior knowledge of existing campsites to facilitate scientific decision-making during site selection

[0145] This method provides a more objective and reliable basis by fully mining and analyzing the existing campsite data and identifying historical patterns and trends in a data-driven way based on a large amount of historical data. This method based on empirical analysis improves the scientific nature of site selection decisions and provides decision makers with more accurate and targeted site selection recommendations.

[0146] 3. Use explainable machine learning methods to obtain factor weights, which is more objective and scientific.

[0147] Traditional weight determination methods usually rely on the subjective judgment of experts, while machine learning methods automatically learn weights from data through algorithms, reducing the bias caused by human factors and improving objectivity and scientificity. Machine learning models learn weights through training data and have better generalization capabilities, so they can more accurately predict the suitability of campsites in unknown situations and improve the accuracy and reliability of site selection decisions. As time goes by and data accumulates, machine learning models can continuously update and adjust weights. This dynamic adjustment capability makes them more advantageous in the complex and changing real world.

[0148] 4. Model correction based on field observations provides decision makers with more flexible and reliable decision support

[0149] This method allows decision makers to dynamically adjust the weight distribution of each factor in the evaluation index system according to the actual situation and needs of different regions, providing flexibility and adaptability. Compared with traditional methods, this comprehensive evaluation model can quickly adjust and optimize indicators and weight distribution based on field verification results, thereby improving the effectiveness and reliability of decision-making.

[0150] like Figure 6 As shown, in a second aspect of the embodiment of the present application, a device for evaluating the suitability of a camping site selection area is provided, comprising:

[0151] The first acquisition module 11 acquires the research area, suitability factor data and restriction factor data corresponding to the camping site selection area;

[0152] The second acquisition module 12 is used to obtain historical camping areas and non-camping areas within the study area;

[0153] A first data processing module 13 is used to calculate the weight value of the suitability factor data based on the suitability factor data of the historical camping area and the suitability factor data of the non-camping area;

[0154] The second data processing module 14 is used to set the weight value of the restriction factor data to a preset value;

[0155] The scoring module 15 is used to perform weighted summation of the suitability factor data and the restriction factor data based on the weight value of the suitability factor data and the weight value of the restriction factor data to obtain a score for the camping site selection area.

[0156] The suitability evaluation device for the camping site selection area in the embodiment of the present application may also be a component, an integrated circuit, or a chip in a terminal. The device may be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device may be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc., and the non-mobile electronic device may be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0157] The suitability evaluation device for campsite selection area provided in the embodiment of the present application can implement each process implemented by the suitability evaluation method for campsite selection area provided in any of the above embodiments, and will not be described again here to avoid repetition.

[0158] Alternatively, if Figure 7 As shown, the embodiment of the present application also provides an electronic device 1100, including a processor 1101, a memory 1102, and a program or instruction stored in the memory 1102 and executable on the processor 1101. When the program or instruction is executed by the processor 1101, each process of the above-mentioned camping site area suitability evaluation method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0159] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0160] Figure 8 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of the present application.

[0161] The electronic device 1200 includes but is not limited to: a radio frequency unit 1201, a network module 1202, an audio output unit 1203, an input unit 1204, a sensor 1205, a display unit 1206, a user input unit 1207, an interface unit 1208, a memory 1209, and a processor 1210 and other components.

[0162] Those skilled in the art will appreciate that the electronic device 1200 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 1210 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 8 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0163] It should be understood that in the embodiment of the present application, the input unit 1204 may include a graphics processor (Graphics Processing Unit, GPU) 12041 and a microphone 12042, and the graphics processor 12041 processes the image data of the static picture or video obtained by the image capture device (such as a camera) in the video capture mode or the image capture mode. The display unit 1206 may include a display panel 12061, and the display panel 12061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1207 includes a touch panel 12071 and other input devices 12072. The touch panel 12071 is also called a touch screen. The touch panel 12071 may include two parts: a touch detection device and a touch controller. Other input devices 12072 may include, but are not limited to, a physical keyboard, a function key (such as a volume control button, a switch button, etc.), a trackball, a mouse, and a joystick, which will not be repeated here. The memory 1209 can be used to store software programs and various data, including but not limited to applications and operating systems. The processor 1210 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor may not be integrated into the processor 1210.

[0164] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned camping site selection area suitability evaluation method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0165] The processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0166] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned campsite site suitability evaluation method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0167] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0168] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0169] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0170] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A method for evaluating the suitability of a camping site selection area, characterized in that: include: Obtain the study area, suitability factor data, and restriction factor data corresponding to the campsite site selection area; Obtaining historical campground areas and non-campground areas within the study area; Calculating a weight value of the suitability factor data based on the suitability factor data of the historical camping area and the suitability factor data of the non-camping area; Setting the weight value of the limiting factor data to a preset value; The suitability factor data and the restriction factor data are weighted and summed based on the weight value of the suitability factor data and the weight value of the restriction factor data to obtain a score for the camping site selection area.

2. A method for evaluating the suitability of a camping site selection area according to claim 1, characterized in that: Calculating the weight value of the suitability factor data based on the suitability factor data of the historical camping area and the suitability factor data of the non-camping area includes: Establishing a campsite location probability prediction model based on the suitability factor data of the historical campsite area and the suitability factor data of the non-campsite area; Calculating the contribution of the suitability factor to the campsite site selection probability prediction model; A weight value of the suitability factor is assigned based on the contribution degree.

3. A method for evaluating the suitability of a camping site selection area according to claim 2, characterized in that: A campsite location probability prediction model is established based on the suitability factor data of the historical campsite area and the suitability factor data of the non-campsite area, including: Taking the suitability factor data of the historical camping area and the suitability factor data of the non-camping area as input variables, and taking whether it is a camping area as a label to construct a model training data set; Training multiple initial classification models using the model training data set to obtain multiple site selection classification models; Obtaining a performance indicator of each of the site selection classification models; A campsite site selection probability prediction model is selected from the site selection classification model based on the performance index.

4. A method for evaluating the suitability of a camping site selection area according to claim 3, characterized in that: The performance indicators include area under the curve; The calculation formula for the area under the curve is as follows: Wherein, N is the suitability factor data of the non-camping area, P is the suitability factor data of the historical camping area, TN is the number of the historical camping areas correctly classified, and TP is the number of the non-camping areas correctly classified.

5. A method for evaluating the suitability of a camping site selection area according to claim 3, characterized in that: The performance indicators include classification accuracy; The calculation formula of the classification accuracy is as follows: Wherein, TP is the number of the historical camping areas that are correctly classified, TN is the number of the non-camping areas that are correctly classified, FP is the number of the historical camping areas that are incorrectly classified, and FN is the number of the non-camping areas that are incorrectly classified.

6. A method for evaluating the suitability of a camping site selection area according to claim 2, characterized in that: The calculation formula of the contribution value is as follows: in, is the contribution value of the i-th suitability factor data, S is a subset of the suitability factor data, N is a set of the suitability factor data, and f(S) is the output of the campsite location probability prediction model on the subset S of the suitability factor data.

7. A method for evaluating the suitability of a camping site selection area according to claim 2, characterized in that: The campsite location probability prediction model includes one or more of the following models: random forest, gradient boosting regression tree, extreme gradient boosting.

8. A method for evaluating the suitability of a camping site selection area according to claim 1, characterized in that: Obtain historical campground areas and non-campground areas within the study area, including: Initial historical campsites in the study area were web crawled; spatially overlaying and matching the remote sensing image of the study area with the initial historical campsite; The initial historical campsite that is successfully matched is used as a historical campsite; A preset number of non-camping sites were randomly selected from the study area.

9. A method for evaluating the suitability of a camping site selection area according to claim 1, characterized in that: The suitability factor data include terrain data, ecological data and traffic data; The terrain data includes elevation, slope, soil conditions and land type; The ecological data include temperature, precipitation, air quality index and water resources; The traffic data includes the distance between the camping area and the road, the distance between the camping area and the train station, and the distance between the camping area and the airport.

10. A method for evaluating the suitability of a camping site selection area according to claim 1, characterized in that: The limiting factor data include risk disaster data and ecological protection data; The risk disaster data include landslides, ice and snow disasters and floods; The ecological inclusion data includes natural ecological protection areas.

11. A device for evaluating the suitability of a camping site selection area, characterized in that: include: The first acquisition module acquires the research area, suitability factor data and restriction factor data corresponding to the camping site selection area; A second acquisition module is used to acquire historical camping areas and non-camping areas within the study area; A first data processing module, configured to calculate a weight value of the suitability factor data based on the suitability factor data of the historical camping area and the suitability factor data of the non-camping area; A second data processing module, used for setting the weight value of the limiting factor data to a preset value; A scoring module is used to perform weighted summation of the suitability factor data and the restriction factor data based on the weight value of the suitability factor data and the weight value of the restriction factor data to obtain a score for the camping site selection area.

12. An electronic device, characterized in that: include: A processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements a method for evaluating the suitability of a camping site selection area as described in any one of claims 1 to 10.

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