A method, device, medium and product for managing natural resource spatial data

Abstract

The application relates to the technical field of data management, in particular to a natural resource space data management method and device, a medium and a product. The method comprises the following steps: acquiring a regional remote sensing image of a region to be managed, identifying regional features from the regional remote sensing image, and determining a regional type of the region to be managed based on the regional features; determining a corresponding resource space relationship network based on the regional type; determining boundary values of each concerned natural resource in the resource space relationship network from historical survey data, and superimposing each boundary value to a corresponding position in the resource space relationship network to obtain a displayed resource space relationship network; dividing actual survey data based on the concerned natural resources contained in the displayed resource space relationship network to obtain sub-actual survey data corresponding to each concerned natural resource; and adding each sub-actual survey data to the displayed resource space relationship network to obtain resource space data. The application facilitates improving the accuracy of natural resource data management.

Description

Technical Field

[0001] This application relates to the field of data management technology, and in particular to a method, device, medium, and product for managing spatial data of natural resources. Background Technology

[0002] Natural resources such as water, land, minerals, and biological resources are finite. Overexploitation and irrational use can lead to the depletion of natural resources, which may affect human long-term survival and development. Therefore, it is necessary to scientifically manage and rationally plan the development and utilization of natural resources to ensure their sustainability.

[0003] In related technologies, natural resources are generally surveyed and fed back using sensors so that relevant managers can understand and analyze the actual situation of natural resources. However, due to the wide variety of natural resources and the complex relationships between different types of natural resources, it may not be possible to effectively integrate massive amounts of natural resources when the survey results are fed back at the same time, which may affect the accuracy of natural resource data management. Summary of the Invention

[0004] To improve the accuracy of natural resource data management, this application provides a method, device, medium, and product for managing natural resource spatial data.

[0005] Firstly, this application provides a method for managing spatial data of natural resources, employing the following technical solution:

[0006] A method for managing spatial data of natural resources includes:

[0007] Acquire a remote sensing image of the area to be managed, identify regional features from the remote sensing image, and determine the area type of the area to be managed based on the regional features. The area type includes mineral area, water area, biological area, and land area.

[0008] Based on the region type, a corresponding resource spatial relationship network is determined. The resource spatial relationship network includes the natural resources of interest contained in the region to be managed under the corresponding region type, as well as the relationships between the various natural resources of interest.

[0009] Historical survey data of the area to be managed is obtained, the boundary values ​​of each natural resource of interest in the resource spatial relationship network are determined from the historical survey data, and each boundary value is superimposed on the corresponding position in the resource spatial relationship network to obtain the displayed resource spatial relationship network;

[0010] Obtain actual survey data, and based on the natural resources of interest contained in the displayed resource spatial relationship network, divide the actual survey data to obtain sub-actual survey data corresponding to each natural resource of interest;

[0011] Each sub-actual survey data is added to the displayed resource space relationship network to obtain resource space data, and the resource space data is then fed back.

[0012] By adopting the above technical solution, the regional type of the area to be managed can be accurately determined through regional characteristics. Then, the data display or management method of the area to be managed can be determined based on the regional type, instead of feeding back all the acquired natural resource survey data. While classifying the actual survey data, the classified data can also be displayed in partitions according to the resource spatial relationship network corresponding to the regional type. The resource spatial relationship network determined based on the regional type can comprehensively reflect the various natural resources of concern and their relationships within the area to be managed. Displaying and managing the actual survey data through the resource spatial relationship network makes it easier to grasp the overall distribution and resource status of the natural resources of concern within the area to be managed, and improves the intuitiveness of relevant management personnel when viewing the actual survey data. In addition, by overlaying the boundary values ​​corresponding to each natural resource of concern into the resource spatial relationship network, it is convenient to monitor the anomalies of the sub-actual survey data corresponding to each natural resource of concern, which not only improves the management accuracy but also helps to improve the anomaly response speed.

[0013] In one possible implementation, determining the corresponding resource spatial relationship network based on the region type includes:

[0014] Based on the region type and the preset resource mapping relationship, the natural resources of interest corresponding to the region type are determined. The preset resource mapping relationship is the correspondence between the region type and the natural resources of interest.

[0015] Based on the region type, bottom-level and top-level natural resources of concern are determined from the natural resources of concern, and each of the bottom-level and top-level natural resources of concern contains at least one natural resource of concern.

[0016] Identify the underlying influence relationships among all natural resources of interest in the underlying natural resources of interest, determine the underlying relationship identifier based on the underlying influence relationships, and determine the underlying relationship network based on the underlying natural resources of interest, the underlying relationship identifier, and the preset underlying spatial network;

[0017] Identify the upper-level influence relationships among all the natural resources of interest in the upper-level focus, determine the upper-level relationship identifier based on the upper-level influence relationships, and determine the upper-level relationship network based on the upper-level natural resources of interest, the upper-level relationship identifier, and the preset upper-level spatial network;

[0018] The resource space relationship network is determined based on the underlying relationship network and the upper-level relationship network.

[0019] By adopting the above technical solution, the corresponding natural resources of interest are determined according to the region type, rather than using the same natural resources of interest for all region types. Since different region types have different focuses on different natural resources, determining the corresponding natural resources of interest according to the region type makes it easier to manage and plan multiple natural resources. In addition, the underlying and upper-level relationship networks are determined by the relationship between various natural resources of interest. The multi-level relationship network structure helps to more comprehensively and deeply understand the influence relationship between different natural resources of interest.

[0020] In one possible implementation, the method further includes:

[0021] Identify the relationship hierarchy in the upper-level influence relationship, determine the relationship hierarchy in the upper-level influence relationship that is higher than the preset display hierarchy as a collapsible hierarchy, and determine the natural resources of interest corresponding to the collapsible hierarchy as collapsible natural resources;

[0022] When display interface information is detected, the highest relationship level in the current display interface is identified. Based on the highest relationship level and the preset display level interval, the displayable level is determined from the foldable levels, and the foldable natural resource corresponding to the displayable level is determined as the displayable natural resource.

[0023] The displayable hierarchy and the displayable natural resources are displayed.

[0024] By adopting the above technical solution, data folding at higher relationship levels facilitates the loading of information on the display interface, helping relevant staff to clearly view and understand the relationships between different natural resources of interest. In addition, the display content can be automatically adjusted by preset display level intervals to meet the access needs of relevant staff.

[0025] In one possible implementation, after determining the resource space data, the method further includes:

[0026] Based on the natural resources of interest contained in the resource spatial data, resource slicing is performed on the remote sensing image of the region to obtain a resource remote sensing slice corresponding to each natural resource of interest.

[0027] Each resource remote sensing slice is overlaid onto the resource spatial data to obtain overlaid resource spatial data, and the overlaid resource spatial data is then fed back.

[0028] By adopting the above technical solution, resource slicing is performed on regional remote sensing images to accurately locate and extract each natural resource of interest, thereby improving the visualization accuracy of resource spatial data. Furthermore, by overlaying each resource remote sensing slice onto the resource spatial data, more intuitive and richer survey results are provided to relevant personnel, enabling them to gain a more intuitive and comprehensive understanding of the actual situation of natural resources within the area to be managed.

[0029] In one possible implementation, the method further includes:

[0030] The system collects and analyzes the resource spatial data generated within a preset time period, and identifies the resource remote sensing slice corresponding to each natural resource in each resource spatial data.

[0031] Based on natural resources, all remote sensing slices of resources are integrated to obtain a remote sensing slice group corresponding to each natural resource of interest.

[0032] Import each resource remote sensing slice in the remote sensing slice group into the same layer according to the time sequence to obtain the resource change trend map corresponding to each remote sensing slice group;

[0033] When a trend viewing command is detected, all resource change trend charts will be provided as feedback.

[0034] By adopting the above technical solution, and integrating the remote sensing slices of resources determined within a preset time period, it is convenient to analyze the changing trend of any natural resource of interest within the preset time period. By analyzing the resource change trend map, it is also convenient to promptly detect abnormal changes in the corresponding natural resources of interest. The timely response mechanism for anomalies facilitates the timeliness and accuracy of relevant personnel in taking countermeasures.

[0035] In one possible implementation, the method further includes:

[0036] When an abnormal natural resource is found, the abnormal level of the abnormal natural resource in the resource space data is identified. The abnormal natural resource is a natural resource of interest whose actual survey value is higher than the corresponding boundary value in the actual survey data.

[0037] Based on the influence relationship corresponding to the anomaly level, the associated resources are determined from the resource space data;

[0038] Based on the hierarchical difference between each associated resource and the abnormal natural resource, the association type of each associated resource is determined, and the association ratio is determined based on the number of associated resources of different association types. The association types include active association and passive association.

[0039] Based on the actual survey data and corresponding boundary values ​​of the aforementioned abnormal natural resources, the abnormal value difference is determined;

[0040] Based on the anomaly level, the correlation ratio, and the anomaly value difference, the anomaly value corresponding to the anomaly natural resource is determined, and the corresponding early warning level is determined based on the anomaly value.

[0041] By adopting the above technical solution, analyzing the relationship hierarchy of abnormal natural resources facilitates the identification of associated resources. Analyzing the quantity and type of associated resources facilitates the assessment of the abnormal impact range of the abnormal natural resources. Furthermore, by combining the abnormal value difference, abnormal level, and association ratio of the abnormal natural resources, the abnormal value of the abnormal natural resources is determined. A comprehensive assessment of the abnormal situation of the abnormal natural resources based on multidimensional data improves the accuracy of the abnormal assessment results. Finally, the corresponding early warning level is determined based on the abnormal situation, enabling relevant personnel to respond quickly and resolve existing abnormal situations according to the early warning method.

[0042] Secondly, this application provides an electronic device that adopts the following technical solution:

[0043] An electronic device comprising:

[0044] At least one processor;

[0045] Memory;

[0046] At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the aforementioned method for managing natural resource spatial data.

[0047] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution:

[0048] A computer-readable storage medium includes: a computer program storing a method for managing natural resource spatial data that can be loaded by a processor and executed by the aforementioned method.

[0049] Fourthly, this application provides a computer program product, which adopts the following technical solution:

[0050] A computer program product includes a computer program that, when executed by a processor, implements the aforementioned method for managing natural resource spatial data.

[0051] In summary, this application includes at least one of the following beneficial technical effects:

[0052] By leveraging regional characteristics, the regional type of the area to be managed can be accurately determined. Then, based on the regional type, the data display or management method for the area can be determined, rather than simply feeding back all acquired natural resource survey data. While classifying the actual survey data, the data can also be displayed in partitions according to the resource spatial relationship network corresponding to the regional type. The resource spatial relationship network determined by the regional type can comprehensively reflect various natural resources of interest within the area to be managed and their interrelationships. Displaying and managing the actual survey data through the resource spatial relationship network facilitates a holistic understanding of the distribution and status of the natural resources of interest within the area, improving the intuitiveness for relevant management personnel when viewing the actual survey data. Furthermore, by overlaying the boundary values ​​corresponding to each natural resource of interest into the resource spatial relationship network, it is convenient to monitor anomalies in the sub-actual survey data corresponding to each natural resource of interest, improving both management accuracy and anomaly response speed.

[0053] By slicing regional remote sensing images into resource slices, it is possible to accurately locate and extract each natural resource of interest, thereby improving the visualization accuracy of resource spatial data. Furthermore, by overlaying each resource remote sensing slice onto the resource spatial data, it is possible to provide relevant personnel with more intuitive and richer survey results, and also to enable them to have a more intuitive and comprehensive understanding of the actual situation of natural resources in the area to be managed. Attached Figure Description

[0054] Figure 1 This is a flowchart illustrating a method for managing spatial data of natural resources according to an embodiment of this application;

[0055] Figure 2 This is a flowchart illustrating a method for determining an early warning level in an embodiment of this application;

[0056] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0057] The following is in conjunction with the appendix Figure 1-3 This application will be described in further detail.

[0058] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0059] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0060] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0061] Specifically, this application provides a method for managing natural resource spatial data, executed by an electronic device. This electronic device can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this connection.

[0062] refer to Figure 1 , Figure 1 This is a flowchart illustrating a method for managing spatial data of natural resources according to an embodiment of this application. The method includes steps S110-S150, wherein:

[0063] Step S110: Obtain a remote sensing image of the area to be managed, identify regional features from the remote sensing image, and determine the area type of the area to be managed based on the regional features. The area types include mineral areas, water areas, biological areas, and land areas.

[0064] Specifically, the area to be managed is any area that requires spatial data management of natural resources. When the area corresponding to the area to be managed is not higher than the preset area, remote sensing images of the area can be collected by drone equipment and uploaded to electronic devices. When the area corresponding to the area to be managed is higher than the preset area, remote sensing images of the area can be obtained from a professional remote sensing platform after authorization. Some online remote sensing platforms generally provide a large number of rich remote sensing image resources, which can be downloaded and used as needed after authorization. The specific value of the preset area is not specifically limited in this embodiment of the application.

[0065] Different region types correspond to different regional characteristics, and there is a regional feature mapping relationship between regional features and region types. Based on this mapping relationship and the identified regional features, the corresponding region type can be determined. For example, when the identified regional features include geological structural features such as faults and folds; rock texture features such as coarse rock texture and granular rock texture; and topographic features such as mine pits and waste rock piles, the corresponding region type can be determined. The regional feature mapping relationship contains the regional features corresponding to all region types, which are determined by relevant personnel based on historical survey data and then uploaded to electronic devices. The specific content is not specifically limited in this embodiment of the application.

[0066] Regional types include, but are not limited to, mineral zones, water zones, biological zones, and land zones. Mineral zones typically possess abundant mineral resources, including metallic, non-metallic, and energy minerals. The development and utilization of mineral zones usually require consideration of environmental protection and sustainable development factors to ensure the rational use of mineral resources and the protection of the ecological environment. Water zones generally refer to areas covered by water bodies, which can include rivers, lakes, reservoirs, and oceans. Resource surveys in water zones facilitate better protection, utilization, and development. Biological zones are typically composed of diverse biological communities, including plants, animals, and microorganisms. Through the interdependence and mutual influence among multiple biological communities, a relatively complex ecosystem can be formed. Resource surveys in biological zones help ensure the ecological balance of these zones. Land zones generally possess specific soil characteristics and can include farmland, forests, and urban land. Resource surveys in land zones help improve the ecological functions of the land.

[0067] Step S120: Determine the corresponding resource spatial relationship network based on the region type. The resource spatial relationship network includes the natural resources of interest contained in the region to be managed under the corresponding region type, as well as the relationship between each natural resource of interest.

[0068] Specifically, different regional types correspond to different resource spatial networks. The corresponding resource spatial relationship network can be determined based on the regional type and the relationship network mapping relationship. This mapping relationship includes resource spatial relationship networks corresponding to different regional types; the specific content is not specifically limited in this embodiment. The resource relationship network contains multiple natural resources of interest and the relationships between each resource. For example, water resources and soil resources have a mutually influential relationship. Water resources have a significant impact on the moisture, salinity, fertility, and other characteristics of soil resources. Conversely, the condition of soil resources also affects the water retention and self-purification functions of water resources.

[0069] Furthermore, based on the region type, the corresponding resource spatial relationship network is determined, including:

[0070] Based on the region type and the preset resource mapping relationship, the natural resources of interest corresponding to the region type are determined. The preset resource mapping relationship is the correspondence between the region type and the natural resources of interest.

[0071] Specifically, the preset resource mapping relationship includes the natural resources of interest corresponding to different regional types. For example, in the process of resource exploration in biological areas, water resources, soil resources, biological resources and abiotic resources are generally surveyed. In the process of resource exploration in mineral areas, mineral resource types and mineral resource quality are generally surveyed. According to the preset resource mapping relationship, the natural resources of interest corresponding to different regional types can be determined. By determining the natural resources of interest corresponding to different regional types in a personalized way, rather than surveying the same natural resources under different regional types, it is easier to improve the matching degree between survey data and regional types.

[0072] Based on the region type, the bottom-level and top-level natural resources of concern are determined from the natural resources of concern, and each of the bottom-level and top-level natural resources of concern contains at least one natural resource of concern.

[0073] Specifically, the importance of bottom-level and top-level natural resources differs depending on the region type. Natural resources with higher importance are considered bottom-level resources, while those with lower importance are considered top-level resources. For example, in a mineral region, the natural resources of concern include mineral resources, water resources, and land resources. However, mineral resources are the most important; therefore, mineral resources are considered bottom-level resources in a mineral region. Different region types have different resource level lists. Based on these lists, the resource levels corresponding to different natural resources of concern can be determined. Resources are then sorted according to their respective resource levels. The bottom-level and top-level natural resources of concern are determined based on the sorting results. The ratio of bottom-level to top-level natural resources of concern should not exceed a preset ratio, which can be 1:3 or 2:5. The specific preset ratio is not limited in this embodiment.

[0074] Identify the underlying influence relationships among all natural resources of concern in the underlying natural resources, determine the underlying relationship identifiers based on the underlying influence relationships, and determine the underlying relationship network based on the underlying natural resources of concern, the underlying relationship identifiers, and the preset underlying spatial network.

[0075] Specifically, the underlying focus on natural resources must include at least one natural resource. When there are at least two natural resources, the underlying influence relationship between them needs to be determined. This underlying influence relationship can be unidirectional, bidirectional, or parallel. Different underlying influence relationships correspond to different underlying relationship identifiers. The specific form of the underlying relationship identifier is not specifically limited in this embodiment, as long as the underlying influence relationship can be uniquely determined based on the identifier. The preset underlying spatial network contains resource points and relationship identifier points. The underlying natural resources are sequentially imported into the preset underlying spatial network. Then, based on the underlying influence relationship between these resources, the corresponding underlying relationship identifiers are imported into the corresponding relationship identifier points to obtain the underlying relationship network. Using a unified preset underlying relationship network to construct different underlying relationship networks facilitates the standardization of the underlying relationship network construction process and makes it easier to compare different underlying relationship networks.

[0076] Identify the upper-level influence relationships among all natural resources of concern in the upper-level concern, determine the upper-level relationship identifiers based on the upper-level influence relationships, and determine the upper-level relationship network based on the upper-level natural resources of concern, the upper-level relationship identifiers, and the preset upper-level spatial network.

[0077] Specifically, the method for determining the upper-level relationship network can refer to the method steps for determining the lower-level relationship network in the above embodiments, and will not be repeated here. The preset upper-level spatial network and the preset lower-level spatial network are in different dimensions. The preset lower-level spatial network can be in a planar dimension, while the preset upper-level spatial network is in a vertical dimension.

[0078] The resource spatial relationship network is determined based on the underlying and upper-level relationship networks.

[0079] Specifically, after identifying the underlying and upper-level relationship networks, spatial overlaying these networks yields the resource spatial relationship network. Since the underlying and upper-level networks exist in different dimensions, they can be spatially overlaid. By identifying the relationships between various natural resources of interest, the underlying and upper-level relationship networks are determined. This multi-layered network structure facilitates a more comprehensive and in-depth understanding of the influencing relationships between different natural resources of interest.

[0080] Step S130: Obtain historical survey data of the area to be managed, determine the boundary values ​​of each natural resource of interest in the resource spatial relationship network from the historical survey data, and overlay each boundary value onto the corresponding position in the resource spatial relationship network to obtain the displayed resource spatial relationship network.

[0081] Specifically, the historical survey data for the area to be managed refers to the survey data corresponding to the historical survey time period. The duration of the historical time period can be 3 months or 5 months, and the specific duration is not specifically limited in this embodiment. Based on the natural resource data of interest, the corresponding historical natural resource data is determined from the historical survey data. Then, based on the historical survey time included in the historical time period, the values ​​corresponding to each historical natural resource data are analyzed to determine the type of numerical change for each historical natural resource within the historical time period. The numerical change types include stable, rising, falling, and fluctuating. Corresponding boundary values ​​are determined based on different data change types. Specifically, when the numerical change type is stable, a historical survey time can be randomly determined from the historical time period, and the value of the historical survey data corresponding to that historical time time is determined as the boundary value; when the numerical change type is rising, the boundary value is determined from the historical survey data... Within a given time period, a first target historical time period with a higher than a first preset rising frequency is determined. A historical survey time is randomly selected from the first target historical time period, and the value of the historical survey data corresponding to that historical survey time is defined as the boundary value. When the data change type is decreasing, a second target historical time period with a higher than a second preset rising frequency is determined from the historical time period. A historical survey time is randomly selected from the second target historical time period, and the value of the historical survey data corresponding to that historical survey time is defined as the boundary value. The first preset rising frequency is higher than the second preset rising frequency, and the specific frequency value can be set by relevant technical personnel according to actual needs. When the data change type is fluctuating, the peak value of any pair of peak historical survey data and the trough value of trough historical survey data can be determined. The average value of the peak value and the trough value is calculated to determine the corresponding boundary value.

[0082] After determining the boundary values ​​of each natural resource of interest using the above method, each boundary value is overlaid at the corresponding position in the resource spatial relationship network using data overlay technology, thus obtaining a displayed resource spatial relationship network.

[0083] Step S140: Obtain actual survey data. Based on the natural resources of interest contained in the displayed resource spatial relationship network, divide the actual survey data to obtain sub-actual survey data corresponding to each natural resource of interest.

[0084] Step S150: Add each sub-actual survey data to the displayed resource spatial relationship network to obtain resource spatial data, and then feed back the resource spatial data.

[0085] Specifically, the actual survey data refers to the data obtained from the survey during the current survey cycle. The specific survey methods may include remote sensing images, UAV equipment, or on-site surveys. The specific survey methods are not specifically limited in this application embodiment. However, the actual survey data may contain multiple natural resources, and there may be overlaps between the survey data of different natural resources. Based on the determined display resource spatial relationship network, the sub-actual survey data corresponding to each natural resource of interest is determined from the actual survey data. By filling each sub-actual survey data into the corresponding point of the resource spatial data, the resource spatial data of the area to be managed can be obtained.

[0086] In this embodiment of the application, the regional type of the area to be managed can be accurately determined through regional features. Then, the data display or management method of the area to be managed is determined based on the regional type, instead of feeding back the acquired natural resource survey data together. While classifying the actual survey data, the classified data can also be displayed in partitions according to the resource spatial relationship network corresponding to the regional type. The resource spatial relationship network determined based on the regional type can comprehensively reflect the various natural resources of concern and their relationships within the area to be managed. Displaying and managing the actual survey data through the resource spatial relationship network makes it easier to grasp the distribution and resource status of the natural resources of concern within the area to be managed as a whole, and improves the intuitiveness of relevant management personnel when viewing the actual survey data. In addition, by overlaying the boundary values ​​corresponding to each natural resource of concern in the resource spatial relationship network, it is easy to monitor the anomalies of the sub-actual survey data corresponding to each natural resource of concern, which not only improves the management accuracy but also helps to improve the anomaly response speed.

[0087] Furthermore, to enhance the accessibility for relevant staff, the method provided in this application embodiment also includes:

[0088] Identify the relationship hierarchy in the upper-level influence relationships, and determine the relationship hierarchy in the upper-level influence relationships that is higher than the preset display hierarchy as a collapsible hierarchy. The natural resources of interest corresponding to the collapsible hierarchy are determined as collapsible natural resources. When display interface information is detected, identify the highest relationship hierarchy in the current display interface. Based on the interval between the highest relationship hierarchy and the preset display hierarchy, determine the displayable hierarchy from the collapsible hierarchy, and determine the collapsible natural resources corresponding to the displayable hierarchy as displayable natural resources. Display the displayable hierarchy and displayable natural resources.

[0089] Specifically, the upper-level influence relationship includes multiple natural resources of interest and the influence relationships between each natural resource of interest. Therefore, the upper-level influence relationship can be regarded as a binary tree structure. Different relationship levels can represent the depth of the binary tree. The higher the relationship level, the closer the node of the natural resource of interest is to the leaf node. In order to provide an intuitive access interface, relationship levels higher than the preset display level will be collapsed. For example, when the preset display level is 5, relationship levels higher than 5 will be identified as collapsible levels, and the natural resources of interest corresponding to the collapsible levels will be identified as collapsible natural resources. That is, when it is detected that relevant personnel need to access the resource space data, the collapsible levels will be hidden and collapsed to highlight the key content of interest. The specific preset display level is not specifically limited in this embodiment of the application, and can be limited by relevant technical personnel according to actual needs.

[0090] During the visit of relevant staff, the collapsible hierarchy can be selectively displayed by real-time detection of the display interface information. When selectively displaying the collapsible hierarchy, the highest relationship level in the current display interface can be identified. Since the area visited by relevant staff may change, the highest relationship level in the current display interface may also change. Because different relationship levels correspond to different level identifiers, the highest relationship level can be identified from the current display interface through feature recognition. The specific recognition method is not specifically limited in this embodiment and can be set by relevant technical personnel. After determining the highest relationship level in the current display interface, the displayable levels are determined based on the highest relationship level and the preset display level interval. The preset display level interval can be 3 levels or 4 levels, and the specific preset display level interval is not specifically limited in this embodiment. For example, with a maximum display level of 4 and a preset display level interval of 3, levels 1-7 can be identified as displayable levels. Collapsible levels within these levels are also designated as displayable levels. Natural resources corresponding to these displayable levels are then considered displayable natural resources. The displayable natural resources corresponding to levels 5-7 are displayed on the current interface. By collapsing higher relationship levels, the interface can easily handle information loading, helping staff clearly view and understand the relationships between different resources of interest. Furthermore, the preset display level interval automatically adjusts the displayed content to meet the access needs of relevant staff.

[0091] Furthermore, to enable relevant personnel to gain a more intuitive and comprehensive understanding of the actual situation of natural resources within the area to be managed, after determining the resource spatial data, the method provided in this application embodiment further includes:

[0092] Based on the natural resources of interest contained in the resource spatial data, resource tiling is performed on the regional remote sensing image to obtain resource remote sensing slices corresponding to each natural resource of interest; each resource remote sensing slice is overlaid on the resource spatial data to obtain overlaid resource spatial data, and the overlaid resource spatial data is fed back.

[0093] Specifically, for any natural resource of interest, deep learning technology is used to identify all displayed content related to that natural resource from a regional remote sensing image. Then, based on the identification results, the regional remote sensing image is sliced ​​to obtain a resource remote sensing slice corresponding to the natural resource of interest. The resource remote sensing slice can reflect the actual distribution of the corresponding natural resource of interest in the area to be managed. For example, if the area to be managed is a biosphere, and one of the natural resources of interest in the biosphere is soil, after slicing the regional remote sensing image based on the soil resources, the resulting resource remote sensing slice only contains the actual distribution of the soil resources in the area to be managed.

[0094] To improve the accuracy and effectiveness of resource remote sensing tiling, data preprocessing of the regional remote sensing images can be performed first. Preprocessing operations include, but are not limited to, denoising, enhancement, radiometric correction, and geometric correction, to improve the image quality of the regional remote sensing images. After the resource remote sensing tiles are determined, tile optimization and post-processing can be performed. Tile optimization and post-processing include, but are not limited to, removing small spots and smoothing edges to improve the visual effect and quality of the resource remote sensing tiles.

[0095] Based on the above method, resource remote sensing slices corresponding to each natural resource of interest can be obtained. Each natural resource of interest is identified from the resource spatial data, and then the corresponding resource remote sensing slices are superimposed at the corresponding locations to obtain superimposed resource spatial data. By performing resource slicing on the regional remote sensing image, it is possible to accurately locate and extract each natural resource of interest, thereby improving the visualization accuracy of the resource spatial data. Furthermore, by superimposing each resource remote sensing slice on the resource spatial data, it is easier to provide relevant personnel with more intuitive and richer survey results, and also to enable relevant personnel to have a more intuitive and comprehensive understanding of the actual situation of natural resources in the area to be managed.

[0096] Furthermore, to facilitate the timely detection of abnormal changes in relevant natural resources, the method provided in this application embodiment also includes:

[0097] The system collects and analyzes the resource spatial data generated within a preset time period, and identifies the resource remote sensing slice corresponding to each natural resource in each resource spatial data. It then integrates all resource remote sensing slices based on the natural resources to obtain a remote sensing slice group corresponding to each natural resource of interest. Following the chronological order, it imports each resource remote sensing slice in the remote sensing slice group into the same layer to obtain a resource change trend map corresponding to each remote sensing slice group. When a trend viewing command is detected, it provides feedback on all obtained resource change trend maps.

[0098] Specifically, the preset time period can be 3 months or 5 months, and the specific duration is not specifically limited in this embodiment. The resource spatial data generation frequency may be once every 10 days or once every 20 days. The resource spatial data generated within the preset time period contains resource spatial data corresponding to multiple generation times. Therefore, by integrating the resource spatial data generated within the preset time period, the changing trends of various natural resources of interest can be analyzed. When integrating multiple resource spatial data, the resource remote sensing slices of each natural resource of interest identified in each resource spatial data can be grouped to obtain a resource remote sensing slice group corresponding to each natural resource of interest. Each resource remote sensing slice group contains multiple resource remote sensing slices, and the generation times of different resource remote sensing slices are different. According to the time sequence, each resource remote sensing slice contained in each remote sensing slice group is imported into the same layer, that is, according to the generation time, each resource remote sensing slice contained in each remote sensing slice group is imported into the same layer. The changing trend map of each natural resource of interest within the preset time period can be obtained. Through the resource changing trend map corresponding to each remote sensing slice group, the changing trend of each resource of interest within the preset time period can be analyzed and viewed.

[0099] Trend viewing commands can be issued by relevant visitors via their terminal devices and received by electronic devices. When a trend viewing command is detected, the resource change trend corresponding to each remote sensing tile group will be displayed. Figure 1 And feedback is provided. By analyzing resource change trend maps, it is also easier to promptly identify abnormal changes in natural resources of concern, and the timely response mechanism for anomalies facilitates the timeliness and accuracy of relevant personnel in taking countermeasures.

[0100] Furthermore, to facilitate rapid response and resolution of any abnormal situations by relevant personnel based on the early warning method, the method provided in this application also includes steps S1-S5, such as... Figure 2 As shown, where:

[0101] Step S1: When an abnormal natural resource is found, identify the abnormal level of the abnormal natural resource in the resource spatial data. The abnormal natural resource is the natural resource of interest whose actual survey value is higher than the corresponding boundary value in the actual survey data.

[0102] Specifically, each natural resource of interest in the actual survey data is compared with its corresponding boundary value to determine whether any abnormal natural resources exist during the actual survey. When the actual survey value of a natural resource of interest is higher than its corresponding boundary value, the natural resource of interest is considered an abnormal natural resource. The method for determining the boundary value corresponding to each natural resource of interest can be found in the above-described embodiments and will not be repeated here. Abnormal natural resources may or may not exist in the actual survey data. When abnormal natural resources are present, the number of abnormal natural resources is not specifically limited.

[0103] The anomalous level of an abnormal natural resource can be determined from the resource spatial data based on the resource identifier. Since the higher the anomalous level, the lower the importance, the lower the first anomalous score. The first anomalous score corresponding to any anomalous level can be determined based on the first mapping relationship, which is the correspondence between the anomalous level and the first anomalous score.

[0104] Step S2: Based on the impact relationship corresponding to the anomaly level, determine the associated resources from the resource space data.

[0105] Step S3: Determine the association type of each associated resource based on the hierarchical difference between each associated resource and the abnormal natural resource, and determine the association ratio based on the number of associated resources of different association types. The association types include active association and passive association.

[0106] Specifically, since the anomaly level may be located in an upper-level relationship network or a lower-level relationship network, the influence relationship corresponding to the anomaly level may be an upper-level influence relationship or a lower-level influence relationship. Based on the influence relationship, associated resources are determined from the resource space data. Natural resources of interest located at the same anomaly level as the anomalous natural resource, and those located at the next higher or lower level of the associated level, are identified as associated resources. The number of associated resources is not specifically limited in this embodiment. Specifically, the level difference between different associated resources and the anomalous natural resource can be used to determine whether the associated resource is located at the level above or below the anomalous natural resource.

[0107] When the hierarchical difference between associated resources and anomalous natural resources is negative, the association type corresponding to the associated resources is active association; conversely, when the hierarchical difference between associated resources and anomalous natural resources is positive, the association type corresponding to the associated resources is passive association. The association ratio between actively associated resources and passively associated resources is determined based on the quantity of associated resources. The higher the association ratio, the higher the corresponding second anomaly score. The second anomaly score corresponding to any association ratio can be determined according to the second mapping relationship, which is the correspondence between the association ratio and the second anomaly score.

[0108] Step S4: Determine the abnormal value difference based on the actual survey data and corresponding boundary values ​​of the abnormal natural resources.

[0109] Specifically, the larger the difference in abnormal values, the higher the corresponding third abnormal score. The third abnormal score corresponding to any abnormal value can be determined according to the third mapping relationship, which is the correspondence between abnormal values ​​and third abnormal scores.

[0110] Step S5: Based on the anomaly level, correlation ratio, and anomaly value difference, determine the anomaly value corresponding to the anomaly natural resource, and determine the corresponding early warning level based on the anomaly value.

[0111] Specifically, the first, second, and third abnormal scores corresponding to the abnormal natural resources are summed to obtain the abnormal value corresponding to the abnormal natural resources. Different abnormal values ​​correspond to different warning levels. The higher the abnormal value, the higher the warning level. The correspondence between abnormal values ​​and warning levels can be determined by relevant personnel based on historical processing experience and then uploaded to electronic devices. The specific content is not specifically limited in this application embodiment.

[0112] By combining the abnormal value difference, abnormal level, and correlation ratio of the abnormal natural resources, the abnormal values ​​of the abnormal natural resources are determined. The abnormal situation of the abnormal natural resources is comprehensively evaluated based on multidimensional data, which helps to improve the accuracy of the abnormality assessment results. Finally, the corresponding early warning level is determined based on the abnormal situation, which helps relevant staff to respond quickly and resolve the existing abnormal situation according to the early warning method.

[0113] This application provides an electronic device, such as... Figure 3 As shown, Figure 3 The illustrated electronic device 300 includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one type, and the structure of this electronic device 300 does not constitute a limitation on the embodiments of this application.

[0114] Processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0115] Bus 302 may include a pathway for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 302 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by only one line, but this does not mean that there is only one bus or one type of bus.

[0116] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0117] The memory 303 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0118] Electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers can also be included. Figure 3 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0119] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0120] This application provides a computer program product including a computer program that, when executed by a processor, implements the methods described in any of the above embodiments.

[0121] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0122] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for managing spatial data of natural resources, characterized in that, include: Acquire a remote sensing image of the area to be managed, identify regional features from the remote sensing image, and determine the area type of the area to be managed based on the regional features. The area type includes mineral area, water area, biological area, and land area. Based on the region type, a corresponding resource spatial relationship network is determined. The resource spatial relationship network includes the natural resources of interest contained in the region to be managed under the corresponding region type, as well as the relationship between each natural resource of interest. Historical survey data of the area to be managed is obtained, the boundary values ​​of each natural resource of interest in the resource spatial relationship network are determined from the historical survey data, and each boundary value is superimposed on the corresponding position in the resource spatial relationship network to obtain the displayed resource spatial relationship network; Obtain actual survey data, and based on the natural resources of interest contained in the displayed resource spatial relationship network, divide the actual survey data to obtain sub-actual survey data corresponding to each natural resource of interest; Each sub-actual survey data is added to the displayed resource space relationship network to obtain resource space data, and the resource space data is then fed back. The step of determining the corresponding resource spatial relationship network based on the region type includes: Based on the region type and the preset resource mapping relationship, the natural resources of interest corresponding to the region type are determined. The preset resource mapping relationship is the correspondence between the region type and the natural resources of interest. Based on the region type, bottom-level and top-level natural resources of concern are determined from the natural resources of concern, and each of the bottom-level and top-level natural resources of concern contains at least one natural resource of concern. Identify the underlying influence relationships among all natural resources of interest in the underlying natural resources of interest, determine the underlying relationship identifier based on the underlying influence relationships, and determine the underlying relationship network based on the underlying natural resources of interest, the underlying relationship identifier, and the preset underlying spatial network; Identify the upper-level influence relationships among all the natural resources of interest in the upper-level focus, determine the upper-level relationship identifier based on the upper-level influence relationships, and determine the upper-level relationship network based on the upper-level natural resources of interest, the upper-level relationship identifier, and the preset upper-level spatial network; The resource space relationship network is determined based on the underlying relationship network and the upper-level relationship network.

2. The method for managing spatial data of natural resources according to claim 1, characterized in that, Also includes: Identify the relationship hierarchy in the upper-level influence relationship, determine the relationship hierarchy in the upper-level influence relationship that is higher than the preset display hierarchy as a collapsible hierarchy, and determine the natural resources of interest corresponding to the collapsible hierarchy as collapsible natural resources; When display interface information is detected, the highest relationship level in the current display interface is identified. Based on the highest relationship level and the preset display level interval, the displayable level is determined from the foldable levels, and the foldable natural resource corresponding to the displayable level is determined as the displayable natural resource. The displayable hierarchy and the displayable natural resources are displayed.

3. The method for managing spatial data of natural resources according to claim 1, characterized in that, After determining the resource space data, the following also includes: Based on the natural resources of interest contained in the resource spatial data, resource slicing is performed on the remote sensing image of the region to obtain a resource remote sensing slice corresponding to each natural resource of interest. Each resource remote sensing slice is overlaid onto the resource spatial data to obtain overlaid resource spatial data, and the overlaid resource spatial data is then fed back.

4. The method for managing spatial data of natural resources according to claim 1, characterized in that, Also includes: The system collects and analyzes the resource spatial data generated within a preset time period, and identifies the resource remote sensing slice corresponding to each natural resource in each resource spatial data. Based on natural resources, all remote sensing slices of resources are integrated to obtain a remote sensing slice group corresponding to each natural resource of interest. Import each resource remote sensing slice in the remote sensing slice group into the same layer according to the time sequence to obtain the resource change trend map corresponding to each remote sensing slice group; When a trend viewing command is detected, all resource change trend charts will be provided as feedback.

5. A method for managing spatial data of natural resources according to claim 2, characterized in that, Also includes: When an abnormal natural resource is found, the abnormal level of the abnormal natural resource in the resource space data is identified. The abnormal natural resource is a natural resource of interest whose actual survey value is higher than the corresponding boundary value in the actual survey data. Based on the influence relationship corresponding to the anomaly level, the associated resources are determined from the resource space data; Based on the hierarchical difference between each associated resource and the abnormal natural resource, the association type of each associated resource is determined, and the association ratio is determined based on the number of associated resources of different association types. The association types include active association and passive association. Based on the actual survey data and corresponding boundary values ​​of the aforementioned abnormal natural resources, the abnormal value difference is determined; Based on the anomaly level, the correlation ratio, and the anomaly value difference, the anomaly value corresponding to the anomaly natural resource is determined, and the corresponding early warning level is determined based on the anomaly value.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform a method for managing spatial data of natural resources according to any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, include: A computer program is stored that can be loaded by a processor and executed as described in any one of claims 1-5 for the management of spatial data of natural resources.

8. A computer program product, characterized in that, It includes a computer program, which, when executed by a processor, implements the steps of a method for managing spatial data of natural resources as described in any one of claims 1-5.

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