CN117687424B - Fully automatic low-altitude remote sensing and non-sensing inspection and monitoring system based on drones - Google Patents
Fully automatic low-altitude remote sensing and non-sensing inspection and monitoring system based on dronesInfo
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Abstract
本发明属于遥感领域，公开了基于无人机的全自动低空遥感无感巡检监测系统，包括航线规划装置、遥控装置和遥感无人机；航线规划装置用于对遥感区域进行切割，将遥感区域切割为多个局部区域，以及用于基于每个局部区域的地形特征为每个局部区域规划遥感航线；遥控装置用于基于遥感航线对遥感无人机进行控制，使得遥感无人机按照遥感航线进行飞行；遥感无人机用于在遥感航线上的航点进行遥感，获得遥感图像。本发明通过对遥感区域进行切割，使得每个切割区域中的地形尽可能平缓，使得规划的航线中，航线重叠率、旁向重叠率能够随着地形特征的变化而自适应的变化，从而实现在保证遥感的效率的同时，使得不同的局部区域的遥感结果均能满足覆盖率要求。
The present invention belongs to the field of remote sensing and discloses a fully automatic low-altitude remote sensing and non-sensing patrol monitoring system based on an unmanned aerial vehicle (UAV), comprising a route planning device, a remote control device, and a remote sensing UAV; the route planning device is used to cut a remote sensing area into multiple local areas, and is used to plan a remote sensing route for each local area based on the terrain characteristics of each local area; the remote control device is used to control the remote sensing UAV based on the remote sensing route, so that the remote sensing UAV flies along the remote sensing route; the remote sensing UAV is used to perform remote sensing at waypoints on the remote sensing route to obtain remote sensing images. The present invention cuts the remote sensing area so that the terrain in each cut area is as flat as possible, so that the route overlap rate and the side overlap rate in the planned route can adaptively change with changes in terrain characteristics, thereby ensuring remote sensing efficiency while ensuring that the remote sensing results of different local areas meet coverage requirements.
Description
Technical Field
The invention relates to the field of remote sensing, in particular to a full-automatic low-altitude remote sensing and non-sensing inspection monitoring system based on an unmanned aerial vehicle.
Background
In the prior art, when planning a route of the unmanned aerial vehicle for low-altitude remote sensing, the whole remote sensing area is generally determined first, and then parameters such as a route overlapping rate, a side overlapping rate and the like are set. The setting mode has certain defects, as the topography conditions are different in different local areas of the remote sensing area, if the same shooting parameters are set for all the local areas, the shot image can not meet the precision requirement. For example, for local area a and local area B, both local area a and local area B are part of the remote sensing area, if the terrain in local area a is relatively flat and the terrain in local area B is relatively complex and rugged. For the local area A, the remote sensing result with coverage rate meeting the requirement can be obtained by adopting larger route overlapping rate and side overlapping rate. Coverage here refers to the ratio between the total area of the blind field of view in the local area and the total area of the local area. The higher the coverage, the better. However, if the same parameters as those of the local area a are adopted to perform route planning, remote sensing shooting is performed on the local area B, and for the local area B, because the topography is rugged, there are many visual blind areas, so that a remote sensing result with coverage rate meeting the requirement cannot be obtained, that is, there are many visual blind areas in the remote sensing image. If the whole remote sensing area is smaller in route overlapping rate and side overlapping rate, the efficiency of remote sensing is lower certainly because of too many aerial photographing points.
Therefore, how to ensure the remote sensing efficiency and simultaneously enable the remote sensing results of different local areas to meet the coverage rate requirement becomes a technical problem to be solved.
Disclosure of Invention
The invention aims to disclose a full-automatic low-altitude remote sensing non-sensing inspection monitoring system based on an unmanned aerial vehicle, and solves the problem of how to ensure the efficiency of remote sensing and simultaneously enable remote sensing results of different local areas to meet coverage rate requirements in the process of utilizing the unmanned aerial vehicle to conduct low-altitude remote sensing.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the invention provides a full-automatic low-altitude remote sensing non-sensing inspection monitoring system based on an unmanned aerial vehicle, which comprises a route planning device, a remote control device and a remote sensing unmanned aerial vehicle;
the route planning device is used for cutting the remote sensing area, cutting the remote sensing area into a plurality of local areas and planning a remote sensing route for each local area based on the topographic features of each local area;
The remote control device is used for controlling the remote sensing unmanned aerial vehicle based on the remote sensing route, so that the remote sensing unmanned aerial vehicle flies according to the remote sensing route;
The remote sensing unmanned aerial vehicle is used for carrying out remote sensing on the waypoints on the remote sensing airlines to obtain remote sensing images.
Optionally, the route planning device comprises an input module, an acquisition module, a partition module and a route planning module;
the input module is used for inputting the longitude and latitude set of the edge of the remote sensing area by the remote sensing staff;
The acquisition module is used for intercepting the satellite map according to the longitude and latitude set of the edge of the remote sensing area, acquiring the satellite map corresponding to the remote sensing area, and intercepting the contour map according to the longitude and latitude set of the edge of the remote sensing area, and acquiring the contour map corresponding to the remote sensing area;
The partition module is used for cutting the remote sensing area based on the satellite map and the contour map of the remote sensing area and cutting the remote sensing area into a plurality of local areas;
The route planning module is used for planning a remote sensing route for each local area based on the terrain features of each local area.
Optionally, the remote sensing area is cut based on a satellite map and a contour map of the remote sensing area, and the remote sensing area is cut into a plurality of local areas, including:
S1, randomly selecting a point A from the edge of a remote sensing area as a coordinate origin, establishing a rectangular coordinate system, and placing the areas except the point A in the remote sensing area in a first quadrant of the rectangular coordinate system;
s2, respectively using xa and xi to represent the maximum value and the minimum value of the X-axis coordinate of the remote sensing area, and respectively using ya and yi to represent the maximum value and the minimum value of the Y-axis coordinate of the remote sensing area;
S3, determining that the value range of the X-axis coordinate of the cutting areas cutarea and cutarea is [ xi, xa ]; and determining that the value range of the Y-axis coordinate in cutarea is [ yi, ya ];
and S4, cutting cutarea on the basis of a satellite map and a contour map of the remote sensing area, and cutting the remote sensing area into a plurality of local areas.
Optionally, the satellite map and the contour map pair cutarea based on the remote sensing area cut the remote sensing area into a plurality of local areas, including:
Firstly, cutting cutarea into N local areas with consistent areas, and storing the obtained local areas into a next cutting set;
cutting each local area in the next cutting set into N local areas with consistent areas, and storing the obtained local areas in a judging set;
Thirdly, respectively calculating the cutting probability coefficient of each local area in the judging set;
fourthly, storing the local area with the cutting probability coefficient smaller than or equal to the cutting probability coefficient threshold value into an output set;
fifthly, deleting all local areas in the next cutting set to obtain an updated next cutting set;
A sixth step of judging whether the number of the local areas with the cutting probability coefficient larger than the cutting probability coefficient threshold is larger than or equal to 1, if so, entering a seventh step, and if not, entering an eighth step;
A seventh step of storing the local area with the cutting probability coefficient larger than the cutting probability coefficient threshold value to the next cutting set, and entering a second step;
and eighth, further calculating the local area in the output set to obtain a final local area.
Optionally, the calculation formula of the cutting probability coefficient is:
cutpro a denotes a cutting probability coefficient of the local area a, numctr a denotes the number of contour lines of different heights in a contour map corresponding to the local area a, numctr std denotes a preset number, numedge a denotes the number of edge pixel points in a grayscale image imggray a corresponding to a satellite map corresponding to the local area a, numpixe a denotes the total number of pixel points in imggray a, grayvar a denotes an information amount parameter of pixel points in imggray a, maxgray denotes the maximum value of the grayscale value of pixel points in imggray a, areasub a denotes the area of the local area a in a rectangular coordinate system, rmtare denotes the area of a remote sensing area in a rectangular coordinate system, weight 1、weight2、weight3、weight4 denotes a contour number weight, an edge pixel point number weight, an information amount parameter weight, and an area weight, respectively;
grayvar a has a calculation formula:
pixeu a is a set of pixel points in imggray a, and pixgray i is a gray value of pixel point i.
Optionally, the process of acquiring the number of the contour lines with different heights in the contour map corresponding to the local area a includes:
judging whether an overlapped area exists between the local area a and the remote sensing area, if so, performing the following calculation:
acquiring a set latltd a of longitudes and latitudes of points at edges of the overlapped areas;
In the contour map, acquiring a corresponding region ctr a according to latltd a;
acquiring the number of contour lines with different heights in ctr a;
if not, the number of the contour lines of different heights in the contour map corresponding to the local area a is set to 0.
Optionally, the acquiring process of the gray image imggray a corresponding to the satellite map corresponding to the local area a includes:
judging whether an overlapped area exists between the local area a and the remote sensing area, if so, performing the following calculation:
acquiring a set latltd a of longitudes and latitudes of points at edges of the overlapped areas;
In the satellite map, acquiring a corresponding region satmap a according to latltd a;
And carrying out graying treatment on satmap a to obtain a gray image imggray a.
Optionally, further computing the local area in the output set to obtain a final local area, including:
respectively acquiring an overlapping area of each local area and a remote sensing area;
All overlapping areas are taken as final local areas.
Optionally, the topographical features of the local area include the number of contours of different heights in the contour map corresponding to the local area and the area variance of the areas of different height ranges.
Optionally, the remote sensing image comprises at least one of a visible light remote sensing image, a panchromatic remote sensing image, a multispectral remote sensing image, an infrared remote sensing image, a Lidar remote sensing image and a synthetic aperture radar remote sensing image.
Compared with the prior art, the method and the device have the advantages that in the process of carrying out route planning on the remote sensing areas, the remote sensing areas are cut, so that the topography in each cutting area is as gentle as possible, corresponding route planning can be carried out according to the topography characteristics of each cutting area, and in the planned route, the route overlapping rate and the side overlapping rate can be adaptively changed along with the change of the topography characteristics, so that the remote sensing results of different local areas can meet the coverage rate requirements while the remote sensing efficiency is ensured.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a full-automatic low-altitude remote sensing non-sensing inspection monitoring system based on an unmanned aerial vehicle.
Fig. 2 is another schematic diagram of the full-automatic low-altitude remote sensing non-sensing inspection monitoring system based on the unmanned aerial vehicle.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, based on the embodiments of the invention, which a person of ordinary skill in the art would obtain without inventive faculty, are within the parameters of the scope of the invention.
The invention provides a full-automatic low-altitude remote sensing non-sensing inspection monitoring system based on an unmanned aerial vehicle, which is shown in an embodiment in fig. 1 and comprises a route planning device, a remote control device and a remote sensing unmanned aerial vehicle.
In one embodiment, the route planning device is configured to cut the remote sensing area, to cut the remote sensing area into a plurality of local areas, and to plan a remote sensing route for each local area based on the topographical features of each local area.
Specifically, by dividing the remote sensing area into a plurality of local areas with smaller terrain variation, the route overlapping rate and the side overlapping rate can be calculated in a self-adaptive manner in the following remote sensing route planning process, and generally, in a flatter area, the set route overlapping rate and the side overlapping rate are higher, the number of waypoints in the remote sensing route is smaller, so that the remote sensing efficiency is effectively improved.
The waypoint is the point on the remote sensing route where shooting is stopped.
Further, the route planning device comprises an input module, an acquisition module, a partition module and a route planning module;
the input module is used for inputting the longitude and latitude set of the edge of the remote sensing area by the remote sensing staff;
The acquisition module is used for intercepting the satellite map according to the longitude and latitude set of the edge of the remote sensing area, acquiring the satellite map corresponding to the remote sensing area, and intercepting the contour map according to the longitude and latitude set of the edge of the remote sensing area, and acquiring the contour map corresponding to the remote sensing area;
The partition module is used for cutting the remote sensing area based on the satellite map and the contour map of the remote sensing area and cutting the remote sensing area into a plurality of local areas;
The route planning module is used for planning a remote sensing route for each local area based on the terrain features of each local area.
Specifically, the remote sensing area needs to be designated manually in advance, a plurality of points can be selected at the edge of the remote sensing area, a set is formed by the longitudes and latitudes of the points, and then when the remote sensing area needs to be analyzed, the corresponding remote sensing area can be obtained only by connecting the points corresponding to the longitudes and latitudes in the set.
Further, the method for cutting the remote sensing area into a plurality of local areas based on the satellite map and the contour map of the remote sensing area includes:
S1, randomly selecting a point A from the edge of a remote sensing area as a coordinate origin, establishing a rectangular coordinate system, and placing the areas except the point A in the remote sensing area in a first quadrant of the rectangular coordinate system;
s2, respectively using xa and xi to represent the maximum value and the minimum value of the X-axis coordinate of the remote sensing area, and respectively using ya and yi to represent the maximum value and the minimum value of the Y-axis coordinate of the remote sensing area;
S3, determining that the value range of the X-axis coordinate of the cutting areas cutarea and cutarea is [ xi, xa ]; and determining that the value range of the Y-axis coordinate in cutarea is [ yi, ya ];
and S4, cutting cutarea on the basis of a satellite map and a contour map of the remote sensing area, and cutting the remote sensing area into a plurality of local areas.
Specifically, in this step, the remote sensing area is mainly coordinated, and by placing the remote sensing area in a rectangular coordinate system, various graphic calculations, such as cutting, can be conveniently performed on the remote sensing area.
Further, the satellite map and the contour map pair cutarea based on the remote sensing area cut the remote sensing area into a plurality of local areas, including:
Firstly, cutting cutarea into N local areas with consistent areas, and storing the obtained local areas into a next cutting set;
cutting each local area in the next cutting set into N local areas with consistent areas, and storing the obtained local areas in a judging set;
Thirdly, respectively calculating the cutting probability coefficient of each local area in the judging set;
fourthly, storing the local area with the cutting probability coefficient smaller than or equal to the cutting probability coefficient threshold value into an output set;
fifthly, deleting all local areas in the next cutting set to obtain an updated next cutting set;
A sixth step of judging whether the number of the local areas with the cutting probability coefficient larger than the cutting probability coefficient threshold is larger than or equal to 1, if so, entering a seventh step, and if not, entering an eighth step;
A seventh step of storing the local area with the cutting probability coefficient larger than the cutting probability coefficient threshold value to the next cutting set, and entering a second step;
and eighth, further calculating the local area in the output set to obtain a final local area.
Specifically, in the cutting process, the cutting probability coefficient is calculated continuously for the obtained local area, so that the terrain change in the obtained local area is flatter, and after route planning is performed on the local area by adopting a single route overlapping rate and a single side overlapping rate, the obtained remote sensing image can also meet the coverage rate requirement, and the accuracy of remote sensing is ensured.
Further, the value of N is 4.
Further, the cut probability coefficient threshold may be one quarter of the limit of the cut probability coefficient.
Further, the calculation formula of the cutting probability coefficient is as follows:
cutpro a denotes a cutting probability coefficient of the local area a, numctr a denotes the number of contour lines of different heights in a contour map corresponding to the local area a, numctr std denotes a preset number, numedge a denotes the number of edge pixel points in a grayscale image imggray a corresponding to a satellite map corresponding to the local area a, numpixe a denotes the total number of pixel points in imggray a, grayvar a denotes an information amount parameter of pixel points in imggray a, maxgray denotes the maximum value of the grayscale value of pixel points in imggray a, areasub a denotes the area of the local area a in a rectangular coordinate system, rmtare denotes the area of a remote sensing area in a rectangular coordinate system, weight 1、weight2、weight3、weight4 denotes a contour number weight, an edge pixel point number weight, an information amount parameter weight, and an area weight, respectively;
grayvar a has a calculation formula:
pixeu a is a set of pixel points in imggray a, and pixgray i is a gray value of pixel point i.
Specifically, the cutting probability coefficient comprehensively represents the local area from a plurality of different aspects, specifically including four aspects of the number of contour lines, the number of edge pixel points, information quantity parameters and the area, so that the cutting probability coefficient can more accurately represent the topographic features of the local area.
When the number of contour lines is larger, the number of edge pixel points is larger, the information quantity parameter is larger, and the area is larger, the topography of the local area is less gentle, and the topography is more diversified, at the moment, the cutting probability coefficient is larger than the cutting probability coefficient threshold value set in advance, so that the local area enters the next cutting process, and the purpose of acquiring the local area with gentle topography change is realized;
the smaller the number of contour lines, the smaller the number of edge pixel points, the smaller the information quantity parameters and the smaller the area, the flatter the topography of the local area is represented without entering the next cutting process.
Therefore, the cutting probability coefficient can enable the terrain change in the local area obtained by the method to be smooth enough, and due to the fact that the area parameter is set, the situation that the local area is too small can be avoided, so that too many different remote sensing routes need to be planned, and the remote sensing efficiency is affected.
In the local area, since the information amount is calculated based on the gray-scale image of the satellite image, the larger the difference in gray-scale values of the pixel points in the local area, that is, the larger the information amount, the less gentle the topography of the area is indicated.
Further, the values of the contour number weight, the edge pixel point number weight, the information quantity parameter weight, and the area weight may be 0.2, 0.3, and 0.2, respectively.
Further, the preset number is 50. The preset number can be set according to the area of the remote sensing range and the interval of the contour lines, and the larger the area of the remote sensing range and the smaller the interval of the contour lines, the larger the preset number.
Further, the process of acquiring the number of the contour lines with different heights in the contour map corresponding to the local area a includes:
judging whether an overlapped area exists between the local area a and the remote sensing area, if so, performing the following calculation:
acquiring a set latltd a of longitudes and latitudes of points at edges of the overlapped areas;
In the contour map, acquiring a corresponding region ctr a according to latltd a;
acquiring the number of contour lines with different heights in ctr a;
if not, the number of the contour lines of different heights in the contour map corresponding to the local area a is set to 0.
Specifically, in the contour map, points corresponding to the longitude and latitude in the set latltd a are marked, and then the points are connected, so that the enclosed area is ctr a.
Specifically, the intervals between the contour lines may be 100 meters, 200 meters, etc., and the specific intervals may be set according to the area of the remote sensing area, and the larger the area, the larger the intervals.
Further, the acquiring process of the gray image imggray a corresponding to the satellite map corresponding to the local area a includes:
judging whether an overlapped area exists between the local area a and the remote sensing area, if so, performing the following calculation:
acquiring a set latltd a of longitudes and latitudes of points at edges of the overlapped areas;
In the satellite map, acquiring a corresponding region satmap a according to latltd a;
And carrying out graying treatment on satmap a to obtain a gray image imggray a.
Specifically, in the satellite map, points corresponding to the longitude and latitude in the set latltd a are marked, and then the points are connected, so that the enclosed area is satmap a.
Further, in the present invention, the satellite image is a visible light image.
Optionally, further computing the local area in the output set to obtain a final local area, including:
respectively acquiring an overlapping area of each local area and a remote sensing area;
All overlapping areas are taken as final local areas.
Specifically, since cutarea includes a portion that does not belong to the remote sensing area, the present invention needs to further calculate the local area, and only the portion that belongs to the remote sensing area in the local area is reserved.
Further, the topographical features of the local area include the number of contour lines of different heights in the contour map corresponding to the local area and the area variance of the areas of different height ranges.
Further, planning a remote sensing route for each local area based on the topographical features of each local area, comprising:
For the local area b, numctr b is used for representing the number of the contour lines with different heights in the contour map corresponding to the local area b, areavar b is used for representing the area variance of the areas with different height ranges in the contour map corresponding to the local area b;
areavar b has a calculation formula:
numhei denotes the number of areas of different height ranges in the contour map corresponding to the local area b, areahei denotes the set of all height ranges in the contour map corresponding to the local area b, area j denotes the area of the height range j in the contour map corresponding to the local area b, avearea denotes the average of the areas of all height ranges in areahei;
and calculating the route overlapping rate when the local area b is remotely sensed by adopting the following formula:
rutovl b denotes a route overlapping rate when remote sensing is performed on the local area b, rutovl std denotes a preset route overlapping rate, areavar max denotes the maximum value of the area variance of areas in different height ranges among all the local areas, α denotes a first weight, and δ denotes a second weight;
The side lap ratio when remote sensing is carried out on the local area b is calculated by adopting the following formula:
latovl b denotes a side lap ratio when remote sensing the local area b, latovl std denotes a preset side lap ratio;
And inputting the route overlapping rate and the side overlapping rate into route planning software to obtain the remote sensing route of the local area b.
Specifically, when the route planning is carried out, the route overlapping rate and the side overlapping rate can be adaptively changed along with the number of the equal-altitude lines at different heights and the area variance of the areas in different height ranges, so that the larger route overlapping rate and the side overlapping rate can be used in the area with gentle terrain to improve the remote sensing efficiency while the coverage rate is ensured, and the smaller route overlapping rate and the side overlapping rate are used in the area with complex terrain to ensure the coverage rate.
In a local area, if the number of the contour lines with different heights is larger, the height change in the local area is more complex and less gradual, and in addition, the invention also characterizes whether the area is smooth or not from the variance of the area with different height ranges, specifically, if the variance of the area with different height ranges is larger, the area difference between the areas with different height ranges in the area is larger, and the probability of complex topography is larger.
Therefore, when the remote sensing shooting is carried out on all the local areas, the remote sensing efficiency can be considered, and the requirement of meeting the coverage rate can be ensured.
The following describes regions of different height ranges with a specific example:
Assuming that the local region b includes four kinds of contours of 150,200,250,300, the number of regions in different height ranges is 5, and the height ranges are 150 or less, 150 or more and 200 or less, 200 or more and 250 or less, 250 or more and 300 or less, or 300 or more, respectively. In the contour map corresponding to the local area, the areas of the areas in different height ranges can be obtained by obtaining the areas of the areas surrounded by the contour lines and the edges of the map.
Further, the predetermined course overlap ratio is 30%, and the predetermined side overlap ratio is 30%.
Specifically, the value intervals of the route overlapping rate and the side overlapping rate are 10 percent and 90 percent. And if the calculated route overlapping rate exceeds the value interval, taking the end point of the value interval as the final route overlapping rate, and if the calculated side overlapping rate exceeds the value interval, taking the end point of the value interval as the final side overlapping rate.
Specifically, if the calculated route overlap ratio is 95%, the final route overlap ratio is 90%, and if the calculated route overlap ratio is 5%, the final route overlap ratio is 10%.
Specifically, if the calculated side lap ratio is 95%, the final side lap ratio is 90%, and if the calculated side lap ratio is 5%, the final side lap ratio is 10%.
Specifically, when route planning is performed by using software for route planning, parameters such as a pitching angle and a shooting height of the cradle head need to be set in addition to a route overlapping rate and a side overlapping rate. This belongs to the prior art, and the invention will not be described in detail. For example, a Sinkiang mental map may be used for route planning.
Further, the values of the first weight and the second weight are 0.6 and 0.4, respectively.
Further, the remote sensing image comprises at least one of a visible light remote sensing image, a full-color remote sensing image, a multispectral remote sensing image, an infrared remote sensing image, a Lidar remote sensing image and a synthetic aperture radar remote sensing image.
In one embodiment, the remote control device is configured to control the remote sensing unmanned aerial vehicle based on the remote sensing route, so that the remote sensing unmanned aerial vehicle flies according to the remote sensing route.
The remote control device can control the remote sensing unmanned aerial vehicle to stay at each waypoint in sequence for preset time, for example, 5 seconds, and the remote sensing unmanned aerial vehicle can conduct remote sensing to the lower side in a stay time period.
In one embodiment, the remote sensing unmanned aerial vehicle is used for remote sensing of waypoints on a remote sensing aerial line to obtain a remote sensing image.
The remote sensing unmanned aerial vehicle carries the camera lens that is used for the remote sensing, realizes being connected between camera lens and the unmanned aerial vehicle body simultaneously through the cloud platform to improve anti-shake's performance.
In one embodiment, as shown in fig. 2, the remote sensing image analysis module is further included;
The remote sensing image analysis module is used for identifying the remote sensing image and obtaining the identification result of the remote sensing image, thereby realizing the inspection of the remote sensing area.
Specifically, the identification of the remote sensing image comprises area calculation of the region of interest, type identification of the region of interest and the like.
For example, in the field of forestry remote sensing, the region of interest is the region where the tree is located. When the city is remotely sensed, the region of interest can be a building, and the type identification of the region of interest is the identification of the type of the building.
In the process of carrying out route planning on the remote sensing areas, the remote sensing areas are cut, so that the topography in each cutting area is as gentle as possible, corresponding route planning can be carried out according to the topography features of each cutting area, and in the planned route, the route overlapping rate and the side overlapping rate can be adaptively changed along with the change of the topography features, thereby realizing the change of the remote sensing efficiency, and simultaneously enabling the remote sensing results of different local areas to meet the coverage rate requirement.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The foregoing embodiments are only for illustrating the technical solution of the present invention, but not for limiting the same, and although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that modifications may be made to the technical solution described in the foregoing embodiments or equivalents may be substituted for parts of the technical features thereof, and that such modifications or substitutions do not depart from the spirit and scope parameters of the technical solution of the embodiments of the present invention in essence of the corresponding technical solution.
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| CN111428627A (en) * | 2020-03-23 | 2020-07-17 | 西北大学 | Mountain landform remote sensing extraction method and system |
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| CN111428627A (en) * | 2020-03-23 | 2020-07-17 | 西北大学 | Mountain landform remote sensing extraction method and system |
| CN116149350A (en) * | 2022-10-12 | 2023-05-23 | 浙江点创信息科技有限公司 | A UAV route planning and data acquisition method for mountainous terrain |
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