Integrated Surveying and Mapping Method and System for Remote Sensing Image Data Acquisition and Processing

Abstract

The present application relates to an integrated mapping method and system for remote sensing image data acquisition and processing, which solves the problem that when it comes to obtaining remote sensing images over a large area to distinguish soil categories, different operators need to operate different unmanned aerial vehicles (UAVs) to obtain remote sensing images of different ranges, perform image stitching, and then analyze the soil categories based on the remote sensing images. It includes: analyzing and determining the UAV type and flight route suitable for the sub-region according to the corresponding relationship between the topographic environment type of the sub-region, the suitable UAV type, and the flight route; starting the determined UAV type to perform mapping and obtain remote sensing images according to the flight route; and analyzing and obtaining the soil categories at different positions based on the spectral characteristics and reflectivity contained in the remote sensing images and the spectral characteristics and refractive indices corresponding to different soil categories. The present application has the following effects: improving the acquisition efficiency of remote sensing images and facilitating the analysis of soil categories.

Description

Technical Field

[0001] The present invention relates to the field of remote sensing data processing, and in particular to a method and system for integrated surveying and mapping of remote sensing image data acquisition and processing. Background Art

[0002] Compared with satellite remote sensing platforms, unmanned aerial vehicle (UAV) remote sensing systems have the characteristics of being flexible and having low operating costs, and have been widely used in fields such as emergency disaster relief and resource monitoring. Especially in cloudy and foggy areas, UAV remote sensing technology can make up for the defect that satellite remote sensing platforms cannot penetrate clouds, and can obtain high-definition images to lay a good data foundation for monitoring the regional environment.

[0003] Currently, UAVs are usually manually controlled by operators on site, or software is used to plan flights to complete single or multiple flights. Such an operation mode has a large workload and high operation difficulty during large-scale surveying and mapping. Software planning generally also requires unified scheduling by a ground command center.

[0004] In view of the above related technologies, the inventors found the following defects: UAVs need to be remotely operated by operators. Due to human subjectivity, there may be problems with incorrect operations. Moreover, it is necessary to stare at the UAV on site, which is rather troublesome. And once it comes to obtaining remote sensing images over a large area to distinguish soil types, different operators need to operate different UAVs to obtain remote sensing images of different areas, and then perform image stitching, and then analyze the soil types based on the remote sensing images. Summary of the Invention

[0005] In order to improve the acquisition efficiency of remote sensing images and facilitate the analysis of soil types, the present application provides a method and system for integrated surveying and mapping of remote sensing image data acquisition and processing.

[0006] In a first aspect, the present application provides a method for integrated surveying and mapping of remote sensing image data acquisition and processing, adopting the following technical solutions:

[0007] A method for integrated surveying and mapping of remote sensing image data acquisition and processing includes:

[0008] Obtaining the topographic environment types of the target survey area and the divided sub-areas;

[0009] Analyzing and determining the UAV type and flight route suitable for the sub-area according to the corresponding relationship between the topographic environment type of the sub-area and the adapted UAV type and flight route;

[0010] Starting the determined UAV type to perform surveying and mapping according to the flight route to obtain remote sensing images;

[0011] Based on the spectral characteristics and reflectivity contained in the remote sensing images, as well as the spectral characteristics and emissivity corresponding to different soil categories, analyze and obtain the soil categories at different locations.

[0012] Optionally, the analysis and determination of the UAV type and flight route adapted to the sub-region are as follows:

[0013] According to the topographic environment type of the sub-region, the adapted UAV type, the number of sub-regions, and the number of different UAV types, analyze whether the number of UAV types that meet the adaptation requirements of all sub-regions is sufficient;

[0014] If so, according to the corresponding relationship between the topographic environment type of the sub-region, the adapted UAV type, and the flight route, analyze and determine the UAV type and flight route adapted to the sub-region;

[0015] If not, analyze and obtain the UAV types with insufficient quantity. According to the total area of the sub-regions adapted to the current UAV type and the number of UAV types with insufficient quantity, evenly distribute the processing area of the same type of UAV to form the sub-regions and the required processing parts that all UAVs of the same type need to process;

[0016] According to the corresponding relationship between the topographic environment type of the sub-regions that the UAVs of the same type need to process and the flight route, analyze and determine the flight route.

[0017] Optionally, the total area of the sub-regions adapted to the current UAV type and the number of UAV types with insufficient quantity, evenly distributing the processing area of the same type of UAV to form the sub-regions and the required processing parts that all UAVs of the same type need to process include:

[0018] Obtain the power status of each UAV of the same type with insufficient quantity;

[0019] If the power status of each UAV of the same type with insufficient quantity is the same, then according to the total area of the sub-regions adapted to the current UAV type and the number of UAV types with insufficient quantity, evenly distribute the processing area of the same type of UAV to form the sub-regions and the required processing parts that all UAVs of the same type need to process;

[0020] If the power status of each UAV of the same type with insufficient quantity is different, then according to the ratio status of the power status of each UAV of the same type with insufficient quantity, the total area of the sub-regions adapted to the current UAV type, and the number of UAV types with insufficient quantity, distribute the processing area of the same type of UAV to form the sub-regions and the required processing parts that all UAVs of the same type need to process.

[0021] Optionally, according to the ratio status of the power levels of each drone of the same type with insufficient quantity, the total area of the sub-regions adapted to the current drone type, and the number of drone types with insufficient quantity, allocate the processing area for drones of the same type to form the sub-regions to be processed by all drones of the same category and the parts to be processed, including:

[0022] Obtain the weather condition of the sub-region;

[0023] According to the corresponding relationship between the weather condition of the sub-region and the influence degree value of the power levels of different types of drones, analyze and obtain the influence degree value of the drone power level;

[0024] According to the area of the sub-region adapted to the current drone type and the influence degree value of the drone power level, analyze and obtain the equivalent area of the sub-region adapted to the current drone type;

[0025] According to the equivalent area of the sub-region adapted to the current drone type, analyze and obtain the total equivalent area of the sub-region adapted to the current drone type;

[0026] According to the ratio status of the power levels of each drone of the same type with insufficient quantity, the total equivalent area of the sub-regions adapted to the current drone type, and the number of drone types with insufficient quantity, allocate the processing area for drones of the same type to form the sub-regions to be processed by all drones of the same category and the parts to be processed.

[0027] Optionally, it further includes the step of synchronizing with the start of mapping and obtaining remote sensing images by the analyzed and determined drone types according to the flight route, specifically as follows:

[0028] Analyze whether there are drones with insufficient power to complete the task according to the flight route;

[0029] If so, send the positions of these drones to the mobile power supply device, and the mobile power supply device moves to the corresponding positions according to the positions of these drones and realizes power supply for these drones to complete the remaining part of the flight route.

[0030] Optionally, the mobile power supply device moving to the corresponding positions according to the positions of these drones and realizing power supply includes:

[0031] According to the corresponding relationship between the drone power level and the distance and the remaining power level of the drone, analyze and obtain the flight route distance that the remaining power level of the drone can support;

[0032] Obtain the ratio of the flight route distance that the remaining power level of the drone can support to the distance of the remaining flight route, and sort the positions in ascending order of the ratio;

[0033] Form a route for the mobile power supply device according to the sorted positions, and the mobile power supply device supplies power to the UAVs to be powered one by one according to the formed route.

[0034] Optionally, it further includes the following specific steps after starting to analyze and determine the UAV type to perform mapping according to the flight route to obtain remote sensing images, and before starting the operation of analyzing and obtaining the soil types at different positions based on the spectral characteristics and reflectivity included in the remote sensing images and the spectral characteristics and emissivity corresponding to different soil categories:

[0035] Analyze whether there is missing image information in the obtained remote sensing images;

[0036] If there is, analyze the positions of the missing image information and send the positions of the corresponding missing image information parts to the terminal held by the person in charge.

[0037] In a second aspect, the present application provides an integrated mapping system for remote sensing image data acquisition and processing, adopting the following technical solutions:

[0038] An integrated mapping system for remote sensing image data acquisition and processing includes a memory, a processor, and a program stored on the memory and executable on the processor. When the program is loaded and executed by the processor, it can implement the integrated mapping method for remote sensing image data acquisition and processing as described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flowchart showing the process of an integrated mapping method for remote sensing image data acquisition and processing according to an embodiment of the present application.

[0040] Figure 2 It is a flowchart showing the process of analyzing and determining the UAV type and flight route adapted to a sub-region according to another embodiment of the present application.

[0041] Figure 3 It is a flowchart showing the process of forming the sub-regions to be processed by all UAVs of the same type and the parts to be processed, by evenly distributing the processing area of UAVs of the same type according to the total area of the sub-region adapted to the current UAV type and the number of UAV types with insufficient quantity, according to another embodiment of the present application.

[0042] Figure 4 It is a flowchart showing the process of forming the sub-regions to be processed by all UAVs of the same type and the parts to be processed, by distributing the processing area of UAVs of the same type according to the ratio of the power status of each UAV of the same type with insufficient quantity, the total area of the sub-region adapted to the current UAV type, and the number of UAV types with insufficient quantity, according to another embodiment of the present application.

[0043] Figure 5It is a schematic flowchart of the steps for another embodiment of the present application to synchronize with the process of obtaining remote sensing images by mapping according to the flight route for the determined type of unmanned aerial vehicle (UAV) to be analyzed and started.

[0044] Figure 6 It is a schematic flowchart of the steps for another embodiment of the present application in which the mobile power supply device moves to the corresponding position according to the position of this part of the UAV and realizes power supply.

[0045] Figure 7 It is a schematic flowchart of the steps for another embodiment of the present application after the determined type of UAV to be analyzed and started maps according to the flight route to obtain remote sensing images, and before the steps of analyzing and obtaining the soil types at different positions in parallel based on the spectral characteristics and reflectivity included in the remote sensing images and the spectral characteristics and emissivity corresponding to different soil types. Detailed implementation manners

[0046] The present application will be further described in detail below with reference to the accompanying drawings.

[0047] Refer to Figure 1 , a method for integrated mapping of remote sensing image data acquisition and processing disclosed in the present application, includes:

[0048] Step S100, obtaining the terrain environment types of the target mapping area and the divided sub-areas.

[0049] Among them, the target mapping area is the area that needs to be mapped this time, the divided sub-areas can be divided according to the position, and the terrain environment types can be divided into flat terrain and complex mountain terrain environments.

[0050] Step S200, analyzing and determining the type of UAV and the flight route adapted to the sub-area according to the corresponding relationship between the terrain environment type of the sub-area, the adapted UAV type, and the flight route.

[0051] Among them, the analysis and determination of the UAV type adapted to the sub-area are as follows: taking the terrain environment type of the sub-area as the query object, querying and obtaining the adapted UAV type and flight route from the preset database storing the corresponding relationship between the terrain environment type of the sub-area, the adapted UAV type, and the flight route.

[0052] UAVs can be classified according to the flight platform configuration into fixed-wing UAVs, multi-rotor UAVs, and flapping-wing UAVs. Fixed-wing UAVs can fly for a long time and cover a wider area; multi-rotor UAVs can stay in the air and collect high-quality terrain data at a lower altitude. Such UAVs can also accurately control their position and attitude at a certain altitude to obtain more accurate data. Fixed-wing UAVs are more suitable for collecting terrain data of flat terrain; multi-rotor UAVs are more suitable for collecting complex mountain terrain environments.

[0053] Regarding flight routes, for libraries in flat terrain environments, grid-crossing routes and panoramic routes are used; for debris flow gullies in mountainous terrain environments, horizontal routes, grid-crossing routes, and video routes are used.

[0054] Step S300: Start the determined type of unmanned aerial vehicle (UAV) to conduct mapping according to the flight route to obtain remote sensing images.

[0055] Among them, remote sensing refers to a non-contact, long-distance detection technology. Generally, it refers to the detection of the electromagnetic wave radiation and reflection characteristics of objects using sensors and remote sensors. Remote sensing is to detect the target ground objects through remote sensors, which are instruments sensitive to electromagnetic waves, under the conditions of being far from the target and not in contact with the target object.

[0056] Image acquisition is a means of obtaining real-time image information using modern technologies. The acquisition of remote sensing images requires the cooperation of a UAV. However, during the use process, the image acquisition camera is often fixedly installed on the UAV device, and the shooting angle is adjusted by adjusting the attitude of the UAV to obtain remote sensing images.

[0057] Step S400: Analyze and obtain the soil types at different locations based on the spectral characteristics and reflectivity contained in the remote sensing images, as well as the spectral characteristics and emissivity corresponding to different soil types.

[0058] Specifically, the analysis and acquisition of soil types at different locations are as follows: Based on the spectral characteristics and reflectivity contained in the remote sensing images, query the database storing the spectral characteristics and emissivity corresponding to different soil types, and analyze and obtain the soil types.

[0059] Soils can be divided into three types: sandy soil, clay soil, and loam soil.

[0060] Moreover, according to needs, the corresponding model of high-quality soil can also be set. Specifically, through remote sensing images, making full use of remote sensing features such as the RGB-IR band and the NDVI vegetation index, using the FCN-8S algorithm, constructing a deep network, and establishing the corresponding model of high-quality soil after filtering.

[0061] Moreover, it can also be considered that soil texture has an important impact on the growth and development of crops. Remote sensing technology can evaluate the characteristics of soil texture through reflectivity and spectral data. By analyzing the soil spectral curves and indicators in remote sensing images, the types of soil texture, such as sandy loam, loam, and clay, can be quantitatively evaluated.

[0062] In Figure 1 step S200, further considering the situation that the required types of UAVs may be insufficient, further analysis is required at this time. For specific details, refer to Figure 2 the embodiments shown for a detailed description.

[0063] Reference Figure 2 , the analysis and determination of the UAV type and flight route adapted to the sub-region are as follows:

[0064] Step S210: According to the terrain environment type of the sub-region, the adapted UAV type, the number of sub-regions, and the number of different UAV types, analyze whether the number of UAV types that meet the adaptation of all sub-regions is sufficient. If yes, execute step S220; if no, execute step S230.

[0065] Step S220: According to the corresponding relationship between the terrain environment type of the sub-region, the adapted UAV type, and the flight route, analyze and determine the UAV type and flight route adapted to the sub-region.

[0066] Among them, the analysis and determination of the UAV type and flight route adapted to the sub-region are as follows: Using the terrain environment type of the sub-region as the query object, query and obtain the UAV type and flight route adapted to the sub-region from the preset database that stores the corresponding relationship between the terrain environment type of the sub-region, the adapted UAV type, and the flight route.

[0067] Step S230: Analyze and obtain the UAV types with insufficient quantity. According to the total area of the sub-regions adapted to the current UAV type and the number of UAV types with insufficient quantity, evenly distribute the processing area of the same type of UAV to form the sub-regions and the required processing parts that all UAVs of the same type need to process.

[0068] Among them, the process of evenly distributing the processing area of the same type of UAV is as follows: First, analyze and obtain the total area of the sub-regions adapted to the current UAV type according to the area of each sub-region adapted to the current UAV type. Then, use the total area of the sub-regions adapted to the current UAV type as the dividend and the number of UAV types with insufficient quantity as the divisor. The obtained quotient is the evenly distributed processing area of the same type of UAV.

[0069] Among them, the allocation of the required processing parts is based on the principle of proximity.

[0070] Step S240: According to the corresponding relationship between the terrain environment type of the sub-region that the UAVs of the same type need to process and the flight route, analyze and determine the flight route.

[0071] In Figure 2 In step S230, when specifically allocating UAV tasks, it should not be limited only to the number of UAV types. The battery status of the UAVs should also be considered. Therefore, it is necessary to further analyze the formation of the sub-regions and the required processing parts that all UAVs of the same type need to process. For details, refer to Figure 3 the embodiments shown for a detailed description.

[0072] Reference Figure 3 For the total area of the sub-regions adapted to the current type of UAV and the number of UAV types with insufficient quantity, evenly distribute the processing area of UAVs of the same type to form the sub-regions that all UAVs of the same type need to process, and the parts to be processed include:

[0073] Step S231: Obtain the power status of each UAV of the same type with insufficient quantity.

[0074] Among them, the power status of each UAV of the same type with insufficient quantity can be detected and obtained through a power detection device preset in the UAV.

[0075] Step S232: If the power status of each UAV of the same type with insufficient quantity is the same, then according to the total area of the sub-regions adapted to the current type of UAV and the number of UAV types with insufficient quantity, evenly distribute the processing area of UAVs of the same type to form the sub-regions that all UAVs of the same type need to process and the parts to be processed.

[0076] Step S233: If the power status of each UAV of the same type with insufficient quantity is different, then according to the ratio status of the power status of each UAV of the same type with insufficient quantity, the total area of the sub-regions adapted to the current type of UAV, and the number of UAV types with insufficient quantity, distribute the processing area of UAVs of the same type to form the sub-regions that all UAVs of the same type need to process and the parts to be processed.

[0077] Among them, the distribution of the processing area of UAVs of the same type is as follows: After obtaining the power status of each UAV of the same type with insufficient quantity, calculate the ratio status of the power status of each UAV of the same type with insufficient quantity, then further calculate the proportion of the power of each UAV in the total power of all UAVs of the same type according to the ratio status of the power status of each UAV of the same type with insufficient quantity, and then multiply the proportion of each UAV by the total area of the sub-regions adapted to the current type of UAV. The obtained product is the area that all UAVs of the same type need to process.

[0078] In Figure 3 In step S233, further considering that when distributing the UAV task volume, it should also be considered that the weather conditions in different sub-regions will have an impact on the power consumption of UAVs during task execution. Therefore, further analysis is required. For specific details, refer to Figure 4 the embodiments shown for a detailed description.

[0079] Reference Figure 4, allocate the processing area of the same type of drones according to the ratio status of the power conditions of each drone of the same type with insufficient quantity, the total area of the sub-regions adapted to the current drone type, and the number of types of drones with insufficient quantity, and form the sub-regions to be processed by all drones of the same type and the parts to be processed, including:

[0080] Step S233.1, obtain the weather conditions of the sub-region.

[0081] Among them, the weather conditions of the sub-region can be obtained from the Internet through web crawling technology.

[0082] Step S233.2, analyze and obtain the influence degree value of the drone power according to the corresponding relationship between the weather conditions of the sub-region and the influence degree values of the powers of different types of drones.

[0083] Among them, the analysis and acquisition of the influence degree value of the drone power are as follows: taking the weather conditions of the sub-region as the query object, query and obtain the influence degree value of the drone power from the preset database storing the corresponding relationship between the weather conditions of the sub-region and the influence degree values of the powers of different types of drones.

[0084] Step S233.3, analyze and obtain the equivalent area of the sub-region adapted to the current drone type according to the area of the sub-region adapted to the current drone type and the influence degree value of the drone power.

[0085] Among them, the analysis and acquisition of the equivalent area of the sub-region adapted to the current drone type are as follows: add the product of the area of the sub-region adapted to the current drone type and the influence degree value of the drone power to the area of the sub-region adapted to the current drone type, and the obtained sum is the equivalent area of the sub-region adapted to the current drone type.

[0086] Step S233.4, analyze and obtain the total equivalent area of the sub-regions adapted to the current drone type according to the equivalent area of the sub-region adapted to the current drone type.

[0087] Among them, the analysis and acquisition of the total equivalent area of the sub-regions adapted to the current drone type are as follows:

[0088] Add the equivalent areas of the sub-regions adapted to the current drone type, and the obtained sum is the total equivalent area of the sub-regions adapted to the current drone type.

[0089] Step S233.5, allocate the processing area of the same type of drones according to the ratio status of the power conditions of each drone of the same type with insufficient quantity, the total equivalent area of the sub-regions adapted to the current drone type, and the number of types of drones with insufficient quantity, and form the sub-regions to be processed by all drones of the same type and the parts to be processed.

[0090] The sub - regions to be processed by all drones of the same type and the formation of the parts to be processed are as follows: First, according to the ratio of the power status of each drone of the same type with insufficient quantity, the power proportion of each drone can be analyzed. Then, multiply the power proportion by the equivalent total area of the sub - regions adapted to the current drone type. The obtained product is the area to be processed by the corresponding drone. Then, allocate the sub - regions to be processed by drones of the same type and the parts to be processed according to the principle of proximity.

[0091] In Figure 1 step S300, further considering that when the drone is actually executing tasks, due to various external factors, it may not be able to complete the task execution according to the plan. At this time, a power supply device needs to be arranged to supply power to the drone to ensure the normal operation of the drone. For specific details, refer to Figure 5 the embodiments shown.

[0092] Refer to Figure 5 , an integrated mapping method for remote sensing image data acquisition and processing further includes a step synchronized with starting the drones of the analyzed and determined type to perform mapping along the flight route to obtain remote sensing images, specifically as follows:

[0093] Step SA00, analyze whether there are drones with insufficient power to complete the task along the flight route.

[0094] Step SB00, if so, send the positions of these drones to the mobile power supply device. The mobile power supply device moves to the corresponding positions according to the positions of these drones and realizes power supply to enable these drones to complete the remaining part of the flight route.

[0095] Among them, the mobile power supply device can be a ground mobile device with a moving function or a power - supplying drone.

[0096] In Figure 5 step SB00, further considering how the mobile power supply device can successfully supply power to these drones to be powered. For specific details, refer to Figure 6 the embodiments shown.

[0097] Refer to Figure 6 , the mobile power supply device moves to the corresponding positions according to the positions of these drones and realizes power supply, including:

[0098] Step SB10, analyze and obtain the flight route distance that the remaining power of the drone can support according to the correspondence between the drone's power and distance and the remaining power of the drone.

[0099] Among them, the analysis and acquisition of the flight route distance that the remaining power of the drone can support are as follows: Taking the remaining power of the drone as the query object, query and obtain the flight route distance that the remaining power of the drone can support from a preset database storing the corresponding relationship between the drone power and the distance.

[0100] Step SB20: Obtain the ratio of the flight route distance that the remaining power of the drone can support to the remaining flight route distance, and sort the positions in ascending order of the ratio.

[0101] Step SB30: Form the route of the mobile power supply device according to the sorted positions, and the mobile power supply device supplies power to the drones to be powered one by one according to the formed route.

[0102] After Figure 1 step S300, it should also be considered that the remote sensing images may be incomplete. At this time, it is necessary to notify the location of this part of the missing information to the person in charge in time for the person in charge to process it in time. For details, refer to Figure 7 the embodiments shown for detailed description.

[0103] Referring to Figure 7 , an integrated mapping method for remote sensing image data acquisition and processing further includes the following steps after starting to map according to the determined drone type along the flight route to obtain remote sensing images and before starting to analyze and obtain the soil types at different positions based on the spectral characteristics and reflectivity included in the remote sensing images and the spectral characteristics and emissivity corresponding to different soil categories:

[0104] Step Sa00: Analyze whether there is missing image information in the obtained remote sensing images.

[0105] Among them, the analysis of whether there is missing image information in the obtained remote sensing images is as follows: Judge whether there is missing point cloud data of the target object according to the obtained point cloud data and whether there is deviation in some of the obtained point cloud data.

[0106] Step Sb00: If there is, analyze the position of the missing image information and send the position of the corresponding part of the missing image information to the terminal held by the person in charge.

[0107] Based on the same inventive concept, an embodiment of the present invention provides an integrated mapping system for remote sensing image data acquisition and processing, including a memory and a processor. A program that can be run on the processor to implement any Figures 1 to 6 of the methods is stored on the memory.

[0108] The embodiments of this specific implementation manner are all preferred embodiments of this application, and do not limit the protection scope of this application. Therefore, all equivalent changes made according to the structure, shape, and principle of this application shall be covered within the protection scope of this application.

Claims

1. An integrated mapping method for remote sensing image data acquisition and processing, characterized in that, Including: Obtain the terrain environment types of the target survey area and the divided sub-areas; According to the corresponding relationship between the terrain environment type of the sub-area, the adapted UAV type, and the flight route, analyze and determine the UAV type and flight route adapted to the sub-area; Start the determined UAV type to conduct surveys according to the flight route to obtain remote sensing images; Based on the spectral characteristics and reflectivity included in the remote sensing images and the spectral characteristics and reflectivity corresponding to different soil categories, analyze and obtain the soil categories at different positions; The analysis and determination of the UAV type and flight route adapted to the sub-area are as follows: According to the terrain environment type of the sub-area, the adapted UAV type, the number of sub-areas, and the number of different UAV types, analyze whether the number of UAV types that meet the adaptation requirements of all sub-areas is sufficient; If so, according to the corresponding relationship between the terrain environment type of the sub-area, the adapted UAV type, and the flight route, analyze and determine the UAV type and flight route adapted to the sub-area; If not, analyze and obtain the UAV types with insufficient quantity. According to the total area of the sub-areas adapted to the current UAV type and the number of UAV types with insufficient quantity, evenly distribute the processing area of the same type of UAV to form the sub-areas and the required processing parts that all UAVs of the same type need to process; According to the corresponding relationship between the terrain environment type of the sub-areas that the same type of UAV needs to process and the flight route, analyze and determine the flight route; The total area of the sub-areas adapted to the current UAV type and the number of UAV types with insufficient quantity, evenly distribute the processing area of the same type of UAV to form the sub-areas and the required processing parts that all UAVs of the same type need to process, including: Obtain the power status of each UAV of the same type with insufficient quantity; If the power status of each UAV of the same type with insufficient quantity is the same, according to the total area of the sub-areas adapted to the current UAV type and the number of UAV types with insufficient quantity, evenly distribute the processing area of the same type of UAV to form the sub-areas and the required processing parts that all UAVs of the same type need to process; If the power status of each UAV of the same type with insufficient quantity is different, according to the ratio status of the power status of each UAV of the same type with insufficient quantity, the total area of the sub-areas adapted to the current UAV type, and the number of UAV types with insufficient quantity, distribute the processing area of the same type of UAV to form the sub-areas and the required processing parts that all UAVs of the same type need to process.

2. The integrated mapping method for remote sensing image data acquisition and processing according to claim 1, characterized in that, According to the ratio status of the power status of each UAV of the same type with insufficient quantity, the total area of the sub-areas adapted to the current UAV type, and the number of UAV types with insufficient quantity, distribute the processing area of the same type of UAV to form the sub-areas and the required processing parts that all UAVs of the same type need to process, including: Obtain the weather conditions of the sub-areas; According to the corresponding relationship between the weather conditions of the sub-areas and the influence degree values of different types of UAV power, analyze and obtain the influence degree values of UAV power; According to the area of the sub-areas adapted to the current UAV type and the influence degree value of UAV power, analyze and obtain the equivalent area of the sub-areas adapted to the current UAV type; Analyze and obtain the equivalent total area of the sub-region adapted to the current type of UAV according to the equivalent area of the sub-region adapted to the current type of UAV. According to the ratio status of the power conditions of each UAV of the same type with insufficient quantity, the equivalent total area of the sub-region adapted to the current type of UAV, and the number of types of UAVs with insufficient quantity, allocate the processing area of UAVs of the same type to form the sub-regions and the parts to be processed required for all UAVs of the same kind.

3. The integrated mapping method for remote sensing image data acquisition and processing according to claim 2, characterized in that, It also includes the step of synchronizing with the start of mapping the determined type of UAV according to the flight route to obtain remote sensing images, specifically as follows: Analyze whether there are UAVs with insufficient power to complete the task according to the flight route. If so, send the positions of these UAVs to the mobile power supply device, and the mobile power supply device moves to the corresponding positions according to the positions of these UAVs and realizes power supply for these UAVs to complete the remaining part of the flight route.

4. The integrated mapping method for remote sensing image data acquisition and processing according to claim 3, characterized in that, The mobile power supply device moves to the corresponding positions according to the positions of these UAVs and realizes power supply, including: Analyze and obtain the flight route distance that the remaining power of the UAV can support according to the corresponding relationship between the UAV power and the distance and the remaining power of the UAV. Obtain the ratio of the flight route distance that the remaining power of the UAV can support to the distance of the remaining flight route, and sort the positions from less to more according to the ratio. Form the route of the mobile power supply device according to the sorted positions, and the mobile power supply device supplies power to the UAVs to be powered one by one according to the formed route.

5. The integrated mapping method for remote sensing image data acquisition and processing according to any one of claims 1 to 4, characterized in that , It also includes the steps to be executed after starting to map the determined type of UAV according to the flight route to obtain remote sensing images and before starting to analyze and obtain the soil types at different positions based on the spectral characteristics and reflectivity included in the remote sensing images and the spectral characteristics and reflectivity corresponding to different soil categories, as follows: Analyze whether there is missing image information in the obtained remote sensing image. If there is, analyze the positions of the missing image information and send the positions of the corresponding parts of the missing image information to the terminal held by the person in charge.

6. An integrated mapping system for remote sensing image data acquisition and processing, characterized in that,Include: It includes a memory, a processor, and a program stored on the memory and executable on the processor. When the program is loaded and executed by the processor, it can implement a method for integrated mapping of remote sensing image data acquisition and processing as described in any one of claims 1 to 5.

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