Natural resource data analysis method based on spatial big data technology and related equipment

Abstract

The invention provides a natural resource data analysis method based on a spatial big data technology and related equipment, which are applied to the field of natural resource planning, and specifically comprise the following steps: acquiring remote sensing images of a target area at multiple angles, drawing a three-dimensional model, performing area division on the three-dimensional model to obtain multiple natural resource corresponding areas, and storing the multiple natural resource corresponding areas in a database; and determining the category of the natural resource corresponding to the corresponding natural resource corresponding area by analyzing the surface element feature corresponding to each natural resource. According to the method provided by the invention, the three-dimensional model of the target area is established, and the corresponding natural resource category is marked in the three-dimensional model for the specific area, so that the marking efficiency is higher.

Description

Technical Field

[0001] The present invention relates to the field of natural resource planning, and in particular to a natural resource data analysis method and related equipment based on spatial big data technology. Background Art

[0002] Natural resources are materials that can be directly obtained from nature and used for production and life. Non-renewable resources in natural resources, including various metal and non-metal minerals, fossil fuels, etc., need to go through a long geological period to form. In order to better protect and utilize natural resources, it is necessary to explore and mark the natural resources in various geological resource areas. At present, the marking process of natural resources often adopts the method of manual exploration and marking, which has low marking efficiency. Summary of the invention

[0003] In view of this, the present invention provides a natural resource data analysis method and related equipment based on spatial big data technology, which is used to mark the categories of natural resources in the corresponding area of ​​the target area by establishing a three-dimensional model corresponding to the target area, so as to improve the marking efficiency.

[0004] A natural resource data analysis method based on spatial big data technology, comprising: Calling the set camera equipment to shoot the target area to be analyzed from multiple angles to obtain the remote sensing image corresponding to the target area at each angle; Based on each of the remote sensing images, drawing a three-dimensional model of the target area; Dividing the three-dimensional model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model; Determine the geomorphic features of each of the longitude and latitude regions, and merge the longitude and latitude regions based on the geomorphic features of each of the longitude and latitude regions to determine a plurality of geomorphic regions; Determine the geographical spots of each natural resource corresponding to each of the geomorphic features, and divide each of the geomorphic regions based on the geographical spots of each of the natural resources to determine a plurality of natural resource corresponding areas in each of the geomorphic regions; Acquire the surface element characteristics of each natural resource corresponding area, input the surface element characteristics into the corresponding natural resource analysis model, output the probability value of the natural resource corresponding to each natural resource corresponding area after being processed by the natural resource analysis model, and determine the natural resource corresponding area with a probability value greater than a preset reference value as a to-be-marked area; A corresponding category mark is allocated to each of the areas to be marked, so as to mark the category of the natural resources corresponding to each of the areas to be marked.

[0005] The above-mentioned natural resource data analysis method based on spatial big data technology, optionally, calling the set camera equipment to shoot the target area to be analyzed from multiple angles to obtain the remote sensing image corresponding to the target area at each angle, includes: Determine the coverage of the target area and the terrain distribution data of the target area; Determine a shooting path for the target area according to the coverage range, and determine a plurality of shooting points and a shooting angle corresponding to each shooting point in the shooting path according to the terrain distribution data; The camera device is called to move along the shooting path, and when the camera device moves to each shooting point on the shooting path, the target area is photographed at a shooting angle corresponding to each shooting point to obtain a remote sensing image corresponding to the target area at each shooting angle.

[0006] The above-mentioned natural resource data analysis method based on spatial big data technology may optionally draw a three-dimensional model of the target area based on each of the remote sensing images, including: Extracting image features from the remote sensing image corresponding to each of the shooting angles; Combining the terrain distribution data of the target area and the coverage of the target area, performing feature arrangement on each of the image features; Removing repeated feature data from each of the image features after feature arrangement to obtain modeling features corresponding to each of the image features; The modeling features are input into a pre-established three-dimensional modeling system, and after being processed by the three-dimensional modeling system, a three-dimensional model of the target area is drawn.

[0007] The above-mentioned natural resource data analysis method based on spatial big data technology may optionally divide the three-dimensional model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model, including: Establishing a longitude and latitude correspondence between the three-dimensional model and the target area; According to the longitude and latitude correspondence, the longitude and latitude information of the target area is mapped to the three-dimensional model to obtain the longitude and latitude information corresponding to the three-dimensional model; The three-dimensional model is divided into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model.

[0008] The above-mentioned natural resource data analysis method based on spatial big data technology, optionally, determining the geomorphic features of each of the latitude and longitude regions, and merging the latitude and longitude regions based on the geomorphic features of each of the latitude and longitude regions to determine multiple geomorphic regions, includes: Randomly select a longitude and latitude area from each of the longitude and latitude areas to determine as an initial longitude and latitude area; Determining a first geomorphic region corresponding to the initial longitude and latitude region in the three-dimensional stereo model, the first geomorphic region is composed of at least one longitude and latitude region, each longitude and latitude region constituting the first geomorphic region includes at least the initial longitude and latitude region, and the similarity of geomorphic features of any two adjacent longitude and latitude regions in each longitude and latitude region constituting the first geomorphic region is less than a preset similarity threshold; A new initial longitude and latitude area is randomly selected from the remaining longitude and latitude areas, and the first landform area corresponding to the new initial longitude and latitude area is determined in the three-dimensional model until all longitude and latitude areas have determined their corresponding first landform areas, so as to complete the process of merging the longitude and latitude areas and determining multiple landform areas.

[0009] The above-mentioned natural resource data analysis method based on spatial big data technology, optionally, the determining of the geographical spots of each natural resource corresponding to each of the landform features, dividing each of the landform regions based on the geographical spots of each of the natural resources, so as to determine a plurality of natural resource corresponding areas in each of the landform regions, includes: In a pre-established natural resource map library, determining the geographical map of each natural resource corresponding to the geomorphic features of each latitude and longitude region; In each of the geomorphic regions, the patch boundaries of each geographic patch contained in the geomorphic region are determined, and the geomorphic region is divided based on each of the patch boundaries, so as to determine a plurality of natural resource corresponding areas in each of the geomorphic regions.

[0010] The above-mentioned natural resource data analysis method based on spatial big data technology may optionally further include: The display ratio of the three-dimensional model and the target area is determined in a designated display area, and the three-dimensional model is displayed in the display area according to the display ratio. During the display of the three-dimensional model, the category of natural resources corresponding to each area to be marked in the three-dimensional model is displayed in the three-dimensional model.

[0011] A natural resource data analysis system based on spatial big data technology, comprising: A calling unit, used for calling a set camera device to shoot a target area to be analyzed at multiple angles, and obtaining a remote sensing image corresponding to the target area at each angle; A drawing unit, used for drawing a three-dimensional model of the target area based on each of the remote sensing images; A division unit, configured to divide the three-dimensional model into a plurality of longitude and latitude regions according to longitude and latitude information corresponding to the three-dimensional model; a merging unit, configured to determine the geomorphic features of each of the latitude and longitude regions, and merge the latitude and longitude regions based on the geomorphic features of each of the latitude and longitude regions to determine a plurality of geomorphic regions; A determination unit, configured to determine the geographical spots of each natural resource corresponding to each of the geomorphic features, and to divide each of the geomorphic regions based on the geographical spots of each of the natural resources, so as to determine a plurality of natural resource corresponding areas in each of the geomorphic regions; an acquisition unit, used for acquiring the surface element characteristics of each natural resource corresponding area, inputting the surface element characteristics into the corresponding natural resource analysis model, outputting the probability value of the natural resource corresponding to each natural resource corresponding area after being processed by the natural resource analysis model, and determining the natural resource corresponding area with a probability value greater than a preset reference value as a to-be-marked area; The marking unit is used to assign a corresponding category mark to each of the areas to be marked, so as to mark the category of the natural resources corresponding to each of the areas to be marked.

[0012] A storage medium includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the natural resource data analysis method based on spatial big data technology as described above.

[0013] An electronic device includes a memory and one or more instructions, wherein the one or more instructions are stored in the memory and are configured to be executed by one or more processors to perform the above-mentioned natural resource data analysis method based on spatial big data technology.

[0014] Compared with the prior art, the present invention has the following advantages: The present invention provides a natural resource data analysis method based on spatial big data technology, comprising: calling a set camera device to shoot a target area to be analyzed from multiple angles to obtain a remote sensing image corresponding to the target area at each angle; drawing a three-dimensional stereo model of the target area based on each of the remote sensing images; dividing the three-dimensional stereo model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional stereo model; determining the geomorphic features of each of the longitude and latitude regions, and merging each of the longitude and latitude regions based on the geomorphic features of each of the longitude and latitude regions to determine a plurality of geomorphic regions; determining each natural resource corresponding to each of the geomorphic features The geographical spots of the source are divided into each of the landform areas based on the geographical spots of each of the natural resources, so as to determine a plurality of natural resource corresponding areas in each of the landform areas; the surface element characteristics of each of the natural resource corresponding areas are obtained, and the surface element characteristics are input into the corresponding natural resource analysis model, and after being processed by the natural resource analysis model, the probability value of the natural resource corresponding to each of the natural resource corresponding areas is output, and the natural resource corresponding area with a probability value greater than a preset reference value is determined as a to-be-marked area; a corresponding category mark is assigned to each of the to-be-marked areas, so as to mark the category of the natural resource corresponding to each of the to-be-marked areas. The method provided by the present invention has a higher marking efficiency by establishing a three-dimensional stereo model of the target area and marking the corresponding natural resource category for a specific area in the three-dimensional stereo model. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0016] Figure 1 A method flow chart of a natural resource data analysis method based on spatial big data technology provided by an embodiment of the present invention; Figure 2 Another method flow chart of a natural resource data analysis method based on spatial big data technology provided by an embodiment of the present invention; Figure 3 An example diagram of a natural resource data analysis method based on spatial big data technology provided by an embodiment of the present invention; Figure 4 A schematic diagram of the structure of a natural resource data analysis system based on spatial big data technology provided by an embodiment of the present invention; Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0019] The present invention can be used in many general or special computing device environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multi-processor devices, distributed computing environments including any of the above devices or devices, etc.

[0020] The embodiment of the present invention provides a natural resource data analysis method based on spatial big data technology. The method can be applied in a data platform for natural resource data analysis. The execution subject can be a processor in the data platform. The method specifically includes: S101: calling a set camera device to shoot a target area to be analyzed at multiple angles to obtain a remote sensing image corresponding to the target area at each angle; In the method provided by an embodiment of the present invention, a camera device for terrain photography is pre-set, and the target area to be analyzed may be a natural area that requires natural resource marking. The processor calls the camera device to perform multi-angle photography of the target area, wherein during the multi-angle photography process, each angle is set according to the regional characteristics of the target area, and the regional characteristics may be the regional area, altitude, and topography and landforms contained in the target area and other regional features.

[0021] In the method provided by the embodiment of the present invention, a target area is photographed at multiple angles by a camera device to obtain a remote sensing image corresponding to the target area at each shooting angle.

[0022] S102: Drawing a three-dimensional model of the target area based on each of the remote sensing images; In the method provided by the embodiment of the present invention, after obtaining the remote sensing images obtained by the camera equipment shooting the target area at various angles, each remote sensing image is analyzed to draw a three-dimensional stereo model of the target area. The three-dimensional stereo model is a virtual model of the target area, which truly restores the regional shape of the target area and the corresponding landform and other element features.

[0023] In the method provided in the embodiment of the present invention, a pre-set construction model is used to draw a three-dimensional model of the target area for each remote sensing image.

[0024] S103: Dividing the three-dimensional model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model; In the method provided by an embodiment of the present invention, the three-dimensional model is divided into multiple longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model. In the longitude and latitude information corresponding to the three-dimensional model, each longitude and latitude corresponding to the three-dimensional model is crossed to form multiple grid regions. Each grid region is projected onto the three-dimensional model to obtain multiple longitude and latitude regions in the three-dimensional model.

[0025] S104: determining the geomorphic features of each of the longitude and latitude regions, and merging the longitude and latitude regions based on the geomorphic features of each of the longitude and latitude regions to determine a plurality of geomorphic regions; In the method provided by the embodiment of the present invention, each longitude and latitude region contains corresponding geomorphic features, and the geomorphic features can characterize the geomorphic information contained in the longitude and latitude region. The geomorphic information can include the terrain information in the longitude and latitude region, such as mountains, basin bottoms and other terrains, and can also include terrain trend information, vegetation, rocks and other information contained in the terrain, and the color information of vegetation and rocks, and the distribution information of vegetation and rocks in each longitude and latitude region. After determining the geomorphic features of each longitude and latitude region, the various longitude and latitude regions are merged based on the geomorphic features of each longitude and latitude region, and adjacent longitude and latitude regions with similar geomorphic features are merged, and finally multiple geomorphic regions are determined.

[0026] S105: determining the geographical spots of each natural resource corresponding to each of the landform features, and dividing each of the landform regions based on the geographical spots of each of the natural resources, so as to determine a plurality of natural resource corresponding areas in each of the landform regions; In the method provided by an embodiment of the present invention, the longitude and latitude regions are merged based on the geomorphic features of each longitude and latitude region to determine multiple geomorphic regions, each geomorphic feature can correspond to at least one geographical patch of a natural resource, and in each geomorphic region, each geomorphic region is divided based on the geographical patches, and multiple natural resource corresponding areas can be divided in each geomorphic region, and each geographical patch corresponds to a natural resource corresponding area.

[0027] S106: Acquire the surface element characteristics of each natural resource corresponding area, input the surface element characteristics into the corresponding natural resource analysis model, and after being processed by the natural resource analysis model, output the probability value of the natural resource corresponding to each natural resource corresponding area, and determine the natural resource corresponding area with a probability value greater than a preset reference value as a to-be-marked area; In the method provided by an embodiment of the present invention, each natural resource corresponding area contains at least one surface element feature, which is a natural reaction of the natural resource on the surface of the ground in the area where it is located, and can be understood as the soil color, rock color, etc. corresponding to the natural resource on the surface, as well as the corresponding vegetation distribution and surface particulate matter distribution, etc.

[0028] In the method provided by the embodiment of the present invention, after obtaining the surface element characteristics of each natural resource corresponding area, the corresponding natural resource analysis model is applied to analyze and process each surface element characteristic to obtain the probability value of each natural resource corresponding area belonging to a specific natural resource.

[0029] In the method provided by the embodiment of the present invention, in actual application, in the process of analyzing the surface element characteristics, the natural resource analysis model independently corresponding to each surface element characteristic can be called to process the surface element characteristic, or a unified natural resource analysis model can be used to process the surface element characteristics as a whole.

[0030] In the method provided by the embodiment of the present invention, a corresponding preset reference value is set, and the natural resource corresponding area with a probability value greater than the preset reference value is determined as the area to be marked, indicating that the probability of the natural resources corresponding to the natural resource corresponding area is high.

[0031] S107: assigning a corresponding category mark to each of the areas to be marked, so as to mark the category of the natural resources corresponding to each of the areas to be marked.

[0032] In the method provided by an embodiment of the present invention, corresponding natural resource category tags are set. After determining the natural resources corresponding to each area to be marked, the corresponding natural resource category tag is assigned to the area to be marked to mark the category of the natural resources corresponding to each area to be marked.

[0033] The natural resource data analysis method based on spatial big data technology provided by the embodiment of the present invention, when it is necessary to mark the location range of natural resources in the target area, calls the corresponding camera equipment to shoot the target area from multiple angles to obtain the remote sensing image corresponding to the target area at each angle; based on each of the remote sensing images, draws a three-dimensional stereo model of the target area; according to the longitude and latitude information corresponding to the three-dimensional stereo model, divides the three-dimensional stereo model into multiple longitude and latitude areas; determines the geomorphic features of each of the longitude and latitude areas, and merges each of the longitude and latitude areas based on the geomorphic features of each of the longitude and latitude areas to determine multiple geomorphic areas; determines each of the geomorphic features The method comprises the following steps: obtaining the geographical spots of each natural resource corresponding to the landform characteristics, dividing each landform area based on the geographical spots of each natural resource, so as to determine a plurality of natural resource corresponding areas in each landform area; obtaining the surface element characteristics of each natural resource corresponding area, inputting the surface element characteristics into the corresponding natural resource analysis model, outputting the probability value of the natural resource corresponding to each natural resource corresponding area after being processed by the natural resource analysis model, and determining the natural resource corresponding area with a probability value greater than a preset reference value as a to-be-marked area; and assigning a corresponding category mark to each to-be-marked area to mark the category of the natural resource corresponding to each to-be-marked area.

[0034] In the method provided by the embodiment of the present invention, when marking the natural resources that need to be marked in the target area, a three-dimensional model of the target area is constructed, and the corresponding areas in the three-dimensional model are divided and the natural resources are marked through image analysis, thereby reducing the manual marking process in the actual area and improving the marking efficiency through model marking.

[0035] refer to Figure 2 , shows the process of calling the set camera device to shoot the target area to be analyzed at multiple angles in the method provided by the embodiment of the present invention, and obtaining the remote sensing image corresponding to the target area at each angle, which specifically includes: S201: Determine the coverage of the target area and the terrain distribution data of the target area; S202: determining a shooting path for the target area according to the coverage range, and determining a plurality of shooting points and a shooting angle corresponding to each shooting point in the shooting path according to the terrain distribution data; S203: Calling the camera device to move along the shooting path, and when the camera device moves to each shooting point on the shooting path, shooting the target area at a shooting angle corresponding to each shooting point, to obtain a remote sensing image corresponding to the target area at each shooting angle.

[0036] In the method provided by the embodiment of the present invention, in the process of using a camera device to perform multi-angle shooting of a target area, regional indicators such as the area and altitude of the target area are comprehensively considered, and the coverage range of the target area and the terrain distribution data of the target area are first determined. By analyzing the coverage range of the target area, the shooting path of the target area can be determined. The process of determining the shooting path can consider factors such as the cruising range of the camera device, and the optimal shooting path is determined according to the actual coverage range of the target area, and the entire range of the target area can be effectively photographed on this shooting path.

[0037] In the method provided by the embodiment of the present invention, according to the terrain distribution data of the target area, multiple shooting points and the shooting angle corresponding to each shooting point are determined on the shooting path. The target area may include terrain such as mountains or basin bottoms. According to different terrain distribution conditions, corresponding shooting points are determined on the shooting path and the shooting angle of each shooting point is determined to shoot the target area in all directions.

[0038] In the method provided by the embodiment of the present invention, the camera device is called to move along the shooting path, and the target area is photographed at the corresponding shooting point according to the set shooting angle to obtain the remote sensing image corresponding to each shooting angle.

[0039] In the method provided by the embodiment of the present invention, the process of drawing the three-dimensional model of the target area based on each of the remote sensing images includes: Extracting image features from the remote sensing image corresponding to each of the shooting angles; Combining the terrain distribution data of the target area and the coverage of the target area, performing feature arrangement on each of the image features; Removing repeated feature data from each of the image features after feature arrangement to obtain modeling features corresponding to each of the image features; The modeling features are input into a pre-established three-dimensional modeling system, and after being processed by the three-dimensional modeling system, a three-dimensional model of the target area is drawn.

[0040] In the method provided by an embodiment of the present invention, the remote sensing image contains multiple image features, and the image features correspond to information such as terrain distribution in the target area. By analyzing and organizing the image features, the image features at each geographical location in the entire target area are determined, so that modeling is performed through each image feature.

[0041] In the method provided by the embodiment of the present invention, the specific process of extracting the image features in the remote sensing image corresponding to each shooting angle may include: Each remote sensing image is normalized and its image format is converted into a predetermined image format, which may be a binary image format or various image formats recognizable by a computer. An edge detection algorithm is used to perform shape analysis on the normalized remote sensing image to extract image features from each remote sensing image.

[0042] In the method provided in the embodiment of the present invention, an edge detection algorithm can be used to perform image segmentation and shape analysis on the normalized remote sensing images, thereby obtaining image features in each remote sensing image.

[0043] In the method provided by the embodiment of the present invention, in the process of drawing the three-dimensional stereo model of the target area, the image features of the remote sensing image corresponding to each shooting angle are extracted, each remote sensing image includes multiple image features, and each image feature corresponds to the regional information of the target area.

[0044] In the method provided by the embodiment of the present invention, the specific implementation process of arranging the features of each image feature in combination with the terrain distribution data of the target area and the coverage range of the target area may include: determining the altitudes of various terrains in the target area and the connecting slopes between the various terrains within the coverage range of the target area according to the terrain distribution data of the target area; determining the image features corresponding to the altitudes of each terrain and each connecting slope one by one, and arranging each image feature according to the altitudes of various terrains in the target area and each connecting slope.

[0045] The arranged image features are deduplicated to obtain modeling features for modeling, and the modeling features are input into a three-dimensional modeling system to draw a three-dimensional model.

[0046] In the method provided by the embodiment of the present invention, the process of dividing the three-dimensional model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model includes: Establishing a longitude and latitude correspondence between the three-dimensional model and the target area; According to the longitude and latitude correspondence, the longitude and latitude information of the target area is mapped to the three-dimensional stereo model to obtain the longitude and latitude information corresponding to the three-dimensional stereo model; The three-dimensional model is divided into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model.

[0047] refer to Figure 3 , shows an example longitude and latitude diagram for a target area provided by an embodiment of the present invention. It can be understood that there are multiple longitudes and latitudes corresponding to a target area, and the longitudes and latitudes intersect to form multiple longitude and latitude intersection areas.

[0048] In the process of dividing the three-dimensional model into longitude and latitude areas, the three-dimensional model is first mapped to the three-dimensional model according to the longitude and latitude information corresponding to the target area in the actual environment. In the method provided by the embodiment of the present invention, a longitude and latitude correspondence between the three-dimensional model and the target area is established, and the longitude and latitude information of the target area is mapped to the three-dimensional model to obtain the longitude and latitude information corresponding to the three-dimensional model.

[0049] According to the longitude and latitude information corresponding to the three-dimensional model, each area obtained by the intersection of the longitude and latitude is projected, and a plurality of longitude and latitude areas are divided in the three-dimensional model.

[0050] In the method provided by the embodiment of the present invention, the process of determining the geomorphic features of each of the latitude and longitude regions, and merging the latitude and longitude regions based on the geomorphic features of each of the latitude and longitude regions to determine multiple geomorphic regions includes: Randomly select a longitude and latitude area from each of the longitude and latitude areas to determine as an initial longitude and latitude area; Determining a first geomorphic region corresponding to the initial longitude and latitude region in the three-dimensional stereo model, the first geomorphic region is composed of at least one longitude and latitude region, each longitude and latitude region constituting the first geomorphic region includes at least the initial longitude and latitude region, and the similarity of geomorphic features of any two adjacent longitude and latitude regions in each longitude and latitude region constituting the first geomorphic region is less than a preset similarity threshold; A new initial longitude and latitude area is randomly selected from the remaining longitude and latitude areas, and the first landform area corresponding to the new initial longitude and latitude area is determined in the three-dimensional model until all longitude and latitude areas have determined their corresponding first landform areas, so as to complete the process of merging the longitude and latitude areas and determining multiple landform areas.

[0051] In the method provided by the embodiment of the present invention, in the process of determining multiple landform areas, a longitude and latitude area is randomly selected from each longitude and latitude area as the initial longitude and latitude area, and the initial longitude and latitude area is used as the starting point to diffuse to the periphery of the initial longitude and latitude area. First, each longitude and latitude area that is adjacent to the initial longitude and latitude area is detected, and then the detection is diffused outward in turn. If the similarity of the landform features of two adjacent longitude and latitude areas is less than a preset similarity threshold, the two adjacent longitude and latitude areas are merged into one area until the similarity of no landform features meets the corresponding conditions during the diffusion detection process with the initial longitude and latitude area as the starting point. A new initial longitude and latitude area is determined in each other longitude and latitude area, and the above process is repeated until all longitude and latitude areas in the three-dimensional model complete the merging process to determine multiple landform areas.

[0052] The specific process of the above-mentioned sequential outward diffusion detection can be understood as first detecting each latitude and longitude region that is adjacent to the initial latitude and longitude region, and determining the latitude and longitude region that has passed the detection among the latitude and longitude regions that are adjacent to the initial latitude and longitude region as a marked region. Further detecting each latitude and longitude region that is adjacent to the marked region, and determining a new marked region, until it is determined that there is no new marked region, the diffusion detection process is completed.

[0053] In the method provided by the embodiment of the present invention, the process of determining the similarity of the geomorphic features of two adjacent longitude and latitude regions may include: Extract the terrain features, ground undulation features and altitude features from the geomorphic features of two adjacent longitude and latitude regions; Calculate the first similarity of the terrain features of two adjacent areas, the second similarity of the ground relief features, and the third similarity of the altitude features; The first similarity, the second similarity and the third similarity are weighted to obtain the similarity of the geomorphic features of two adjacent longitude and latitude regions.

[0054] In the specific application process, the weighting coefficient can be obtained by summarizing the data detected in each area according to the historical data.

[0055] In the method provided by the embodiment of the present invention, the first similarity, the second similarity and the third similarity may be calculated by using a Euclidean distance similarity calculation method or a Manhattan distance similarity calculation method.

[0056] In the method provided by the embodiment of the present invention, the process of determining the geographical spots of each natural resource corresponding to each of the geomorphic features, dividing each of the geomorphic regions based on the geographical spots of each of the natural resources, and determining a plurality of natural resource corresponding areas in each of the geomorphic regions, includes: In a pre-established natural resource map library, determining the geographical map of each natural resource corresponding to the geomorphic features of each latitude and longitude region; In each of the geomorphic regions, the patch boundaries of each geographic patch contained in the geomorphic region are determined, and the geomorphic region is divided based on each of the patch boundaries, so as to determine a plurality of natural resource corresponding areas in each of the geomorphic regions.

[0057] The method provided in the embodiment of the present invention further includes: The display ratio of the three-dimensional model and the target area is determined in a designated display area, and the three-dimensional model is displayed in the display area according to the display ratio. During the display of the three-dimensional model, the category of natural resources corresponding to each area to be marked in the three-dimensional model is displayed in the three-dimensional model.

[0058] In the method provided by the embodiment of the present invention, the target area may include various terrains such as mountains, plains or basin bottoms, and the mountains may be specifically divided into various different terrains such as mountain tops, side peaks, valleys and slopes. According to the various terrains included in the target area, there may be multiple shooting paths to collect remote sensing images of the target area. In the method provided by the embodiment of the present invention, according to the operating factors such as the flight altitude and endurance of the camera equipment, the optimal shooting path is selected from the multiple shooting paths to shoot various terrains in the target area.

[0059] and Figure 1 Corresponding to the natural resource data analysis method based on spatial big data technology shown in the embodiment of the present invention, a natural resource data analysis system based on spatial big data technology is provided for analyzing Figure 1 The natural resource data analysis method based on spatial big data technology is specifically implemented as shown in the figure. The structural diagram of the system is shown in Figure 4 As shown, the system comprises: The calling unit 301 is used to call the set camera equipment to shoot the target area to be analyzed at multiple angles to obtain the remote sensing image corresponding to the target area at each angle; A drawing unit 302, used for drawing a three-dimensional model of the target area based on each of the remote sensing images; A division unit 303 is used to divide the three-dimensional model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model; A merging unit 304 is used to determine the geomorphic features of each of the latitude and longitude regions, and merge the latitude and longitude regions based on the geomorphic features of each of the latitude and longitude regions to determine a plurality of geomorphic regions; A determination unit 305 is used to determine the geographical spots of each natural resource corresponding to each of the landform features, and divide each of the landform regions based on the geographical spots of each of the natural resources to determine a plurality of natural resource corresponding areas in each of the landform regions; The acquisition unit 306 is used to acquire the surface element characteristics of each natural resource corresponding area, input the surface element characteristics into the corresponding natural resource analysis model, and after being processed by the natural resource analysis model, output the probability value of the natural resource corresponding to each natural resource corresponding area, and determine the natural resource corresponding area with a probability value greater than a preset reference value as a to-be-marked area; The marking unit 307 is used to assign a corresponding category mark to each of the areas to be marked, so as to mark the category of the natural resources corresponding to each of the areas to be marked.

[0060] The system provided by the embodiment of the present invention constructs a three-dimensional model of the target area when marking the natural resources that need to be marked in the target area, divides the corresponding areas in the three-dimensional model and marks the natural resources through image analysis, thereby reducing the manual marking process in the actual area and improving the marking efficiency through model marking.

[0061] An embodiment of the present invention also provides a storage medium, which includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the above-mentioned natural resource data analysis method based on spatial big data technology.

[0062] The embodiment of the present invention further provides an electronic device, the structural diagram of which is shown in FIG. Figure 5 As shown, it specifically includes a memory 401 and one or more instructions 402, wherein the one or more instructions 402 are stored in the memory 401 and are configured to be executed by one or more processors 403 to perform the following operations: Calling the set camera equipment to shoot the target area to be analyzed from multiple angles to obtain the remote sensing image corresponding to the target area at each angle; Based on each of the remote sensing images, drawing a three-dimensional model of the target area; Dividing the three-dimensional model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model; Determine the geomorphic features of each of the longitude and latitude regions, and merge the longitude and latitude regions based on the geomorphic features of each of the longitude and latitude regions to determine a plurality of geomorphic regions; Determine the geographical spots of each natural resource corresponding to each of the geomorphic features, and divide each of the geomorphic regions based on the geographical spots of each of the natural resources to determine a plurality of natural resource corresponding areas in each of the geomorphic regions; Acquire the surface element characteristics of each natural resource corresponding area, input the surface element characteristics into the corresponding natural resource analysis model, output the probability value of the natural resource corresponding to each natural resource corresponding area after being processed by the natural resource analysis model, and determine the natural resource corresponding area with a probability value greater than a preset reference value as a to-be-marked area; A corresponding category mark is allocated to each of the areas to be marked, so as to mark the category of the natural resources corresponding to each of the areas to be marked.

[0063] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0064] Those skilled in the art may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, computer software, or a combination of both.

[0065] In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0066] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A natural resource data analysis method based on spatial big data technology, characterized in that: include: Calling the set camera equipment to shoot the target area to be analyzed from multiple angles to obtain the remote sensing image corresponding to the target area at each angle; Based on each of the remote sensing images, drawing a three-dimensional model of the target area; Dividing the three-dimensional model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model; Determine the geomorphic features of each of the longitude and latitude regions, and merge the longitude and latitude regions based on the geomorphic features of each of the longitude and latitude regions to determine a plurality of geomorphic regions; Determine the geographical spots of each natural resource corresponding to each of the geomorphic features, and divide each of the geomorphic regions based on the geographical spots of each of the natural resources to determine a plurality of natural resource corresponding areas in each of the geomorphic regions; Acquire the surface element characteristics of each natural resource corresponding area, input the surface element characteristics into the corresponding natural resource analysis model, output the probability value of the natural resource corresponding to each natural resource corresponding area after being processed by the natural resource analysis model, and determine the natural resource corresponding area with a probability value greater than a preset reference value as a to-be-marked area; A corresponding category mark is allocated to each of the areas to be marked, so as to mark the category of the natural resources corresponding to each of the areas to be marked.

2. The natural resource data analysis method based on spatial big data technology according to claim 1 is characterized in that: The calling of the set camera equipment to shoot the target area to be analyzed at multiple angles to obtain the remote sensing image corresponding to the target area at each angle includes: Determine the coverage of the target area and the terrain distribution data of the target area; Determine a shooting path for the target area according to the coverage range, and determine a plurality of shooting points and a shooting angle corresponding to each shooting point in the shooting path according to the terrain distribution data; The camera device is called to move along the shooting path, and when the camera device moves to each shooting point on the shooting path, the target area is photographed at a shooting angle corresponding to each shooting point to obtain a remote sensing image corresponding to the target area at each shooting angle.

3. The natural resource data analysis method based on spatial big data technology according to claim 2 is characterized in that: Drawing a three-dimensional model of the target area based on each of the remote sensing images includes: Extracting image features from the remote sensing image corresponding to each of the shooting angles; Combining the terrain distribution data of the target area and the coverage of the target area, performing feature arrangement on each of the image features; Removing repeated feature data from each of the image features after feature arrangement to obtain modeling features corresponding to each of the image features; The modeling features are input into a pre-established three-dimensional modeling system, and after being processed by the three-dimensional modeling system, a three-dimensional model of the target area is drawn.

4. The natural resource data analysis method based on spatial big data technology according to claim 1 is characterized in that: The step of dividing the three-dimensional model into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model comprises: Establishing a longitude and latitude correspondence between the three-dimensional model and the target area; According to the longitude and latitude correspondence, the longitude and latitude information of the target area is mapped to the three-dimensional model to obtain the longitude and latitude information corresponding to the three-dimensional model; The three-dimensional model is divided into a plurality of longitude and latitude regions according to the longitude and latitude information corresponding to the three-dimensional model.

5. The natural resource data analysis method based on spatial big data technology according to claim 4 is characterized in that: The determining of the geomorphic features of each of the latitude and longitude regions, and merging the latitude and longitude regions based on the geomorphic features of each of the latitude and longitude regions to determine a plurality of geomorphic regions, includes: Randomly select a longitude and latitude area from each of the longitude and latitude areas to determine as an initial longitude and latitude area; Determining a first geomorphic region corresponding to the initial longitude and latitude region in the three-dimensional stereo model, the first geomorphic region is composed of at least one longitude and latitude region, each longitude and latitude region constituting the first geomorphic region includes at least the initial longitude and latitude region, and the similarity of geomorphic features of any two adjacent longitude and latitude regions in each longitude and latitude region constituting the first geomorphic region is less than a preset similarity threshold; A new initial longitude and latitude area is randomly selected from the remaining longitude and latitude areas, and the first landform area corresponding to the new initial longitude and latitude area is determined in the three-dimensional model until all longitude and latitude areas have determined their corresponding first landform areas, so as to complete the process of merging the longitude and latitude areas and determining multiple landform areas.

6. The natural resource data analysis method based on spatial big data technology according to claim 1 is characterized in that: The determining of the geographical spots of the natural resources corresponding to each of the geomorphic features, and dividing each of the geomorphic regions based on the geographical spots of each of the natural resources to determine a plurality of natural resource corresponding areas in each of the geomorphic regions, includes: In a pre-established natural resource map library, determining the geographical map of each natural resource corresponding to the geomorphic features of each latitude and longitude region; In each of the geomorphic regions, the patch boundaries of each geographic patch contained in the geomorphic region are determined, and the geomorphic region is divided based on each of the patch boundaries, so as to determine a plurality of natural resource corresponding areas in each of the geomorphic regions.

7. The natural resource data analysis method based on spatial big data technology according to claim 1 is characterized in that: Also includes: The display ratio of the three-dimensional model and the target area is determined in a designated display area, and the three-dimensional model is displayed in the display area according to the display ratio. During the display of the three-dimensional model, the category of natural resources corresponding to each area to be marked in the three-dimensional model is displayed in the three-dimensional model.

8. A natural resource data analysis system based on spatial big data technology, characterized in that: include: A calling unit, used for calling a set camera device to shoot a target area to be analyzed at multiple angles, and obtaining a remote sensing image corresponding to the target area at each angle; A drawing unit, used for drawing a three-dimensional model of the target area based on each of the remote sensing images; A division unit, configured to divide the three-dimensional model into a plurality of longitude and latitude regions according to longitude and latitude information corresponding to the three-dimensional model; a merging unit, configured to determine the geomorphic features of each of the latitude and longitude regions, and merge the latitude and longitude regions based on the geomorphic features of each of the latitude and longitude regions to determine a plurality of geomorphic regions; A determination unit, configured to determine the geographical spots of each natural resource corresponding to each of the geomorphic features, and to divide each of the geomorphic regions based on the geographical spots of each of the natural resources, so as to determine a plurality of natural resource corresponding areas in each of the geomorphic regions; an acquisition unit, used for acquiring the surface element characteristics of each natural resource corresponding area, inputting the surface element characteristics into the corresponding natural resource analysis model, outputting the probability value of the natural resource corresponding to each natural resource corresponding area after being processed by the natural resource analysis model, and determining the natural resource corresponding area with a probability value greater than a preset reference value as a to-be-marked area; The marking unit is used to assign a corresponding category mark to each of the areas to be marked, so as to mark the category of the natural resources corresponding to each of the areas to be marked.

9. A storage medium, characterized in that: The storage medium includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the natural resource data analysis method based on spatial big data technology as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: It includes a memory and one or more instructions, wherein the one or more instructions are stored in the memory and are configured to be executed by one or more processors to perform the natural resource data analysis method based on spatial big data technology as described in any one of claims 1 to 7.

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