CN116380023B - Land mapping system based on remote sensing technology - Google Patents
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Abstract
The invention provides a land mapping system based on a remote sensing technology, which comprises an aerial unmanned aerial vehicle, a route planning subsystem and an image correction subsystem; the method comprises the steps of combining an aerial photographing technology with a remote sensing mapping technology, analyzing an image obtained by remote sensing mapping, comparing according to image type characteristics, identifying a boundary, using the boundary as a simulated flight route of aerial photographing, comparing the image obtained by aerial photographing with the image of remote sensing mapping, accurately mapping the position of the image according to the comparison of the mapping image and the aerial photographing image, measuring the flight distance of aerial photographing video according to the ratio of the overlapping part of the mapping image and the aerial photographing image, and acquiring the distance of the mapping image, so that the accuracy of remote sensing mapping is higher, and the problem of unclear identification of the remote sensing to the image boundary is solved.
Description
Technical Field
The invention relates to the technical field of remote sensing, in particular to a land mapping system based on a remote sensing technology.
Background
The remote sensing technology is a detection technology which is raised in the 60 s of the 20 th century, is a comprehensive technology for detecting and identifying various scenes on the ground by collecting, processing and finally imaging electromagnetic wave information radiated and reflected by a remote target by using various sensing instruments according to the theory of electromagnetic waves, and can inquire domestic high-resolution remote sensing images such as high-resolution first, high-resolution second and third resources through the remote sensing technology.
The land mapping is based on computer technology, photoelectric technology, network communication technology, space science and information science, and uses Global Positioning System (GPS), remote Sensing (RS) and Geographic Information System (GIS) as technical cores, and the existing characteristic points and boundaries of the ground are used for obtaining the graph and position information reflecting the current situation of the ground through measurement means for planning, design and administrative management of engineering construction.
In the prior art, in the process of carrying out land mapping, land feature information is acquired, image generation is carried out according to the land feature information, land is mapped according to the generated image, in the process of carrying out image generation, analysis is carried out according to the shot image, boundary identification is easy to be unclear, and thus the land mapping is inaccurate, so that the invention provides a land mapping system based on a remote sensing technology.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a land mapping system based on a remote sensing technology, which comprises an aerial unmanned aerial vehicle, a route planning subsystem and an image correction subsystem;
the routing subsystem is configured with a routing strategy comprising
A1, acquiring a remote sensing mapping image of a target area;
a2, carrying out partition processing on the remote sensing mapping image according to the characteristic distribution and determining edge lines between partitions;
a3, generating a reference aerial photographing route according to the determined connecting line of the edge line;
a4, marking aerial photographing features near a reference aerial photographing route according to the remote sensing mapping image;
step A5, calculating a feature identification value of each aerial feature;
step A6, re-performing aerial photography route planning according to the characteristic identification value to generate a static aerial photography route, wherein the static aerial photography route is a connecting line between corresponding coordinates of aerial photography characteristics;
step A7, transmitting the static aerial photographing route and the corresponding aerial photographing characteristics to the corresponding aerial photographing unmanned aerial vehicle;
the aerial photographing unmanned aerial vehicle performs aerial photographing according to the static aerial photographing route, and corrects the aerial photographing route in the aerial photographing process by identifying corresponding aerial photographing characteristics in the photographed image;
the image modification subsystem includes an image modification strategy including
Step B1, acquiring an aerial image shot by an aerial unmanned aerial vehicle;
step B2, transferring the aerial image to a coordinate system corresponding to the remote sensing mapping image according to the position of the aerial image shot by the aerial unmanned aerial vehicle;
step B3, comparing the aerial image with the remote sensing mapping image to obtain correction deviation;
and step B4, correcting the remote sensing mapping image by correcting the deviation.
Further, in the step A5, an identification feature algorithm is configured to calculate an identification feature value, where the identification feature algorithm isWherein->For identifying characteristic values, < >>For the trusted similarity value of the aerial feature, < +.>For the aerial feature and adjacent +.>Similarity of individual aerial features, +.>For the number of aerial features adjacent to the aerial feature, < >>For the feature abundance value of the aerial feature, < >>Identifying a value for the type of the aerial feature, < >>For the environmental time sequence recognition function, +.>For the minimum distance value of the aerial characteristic position and the reference aerial route, +.>For the aerial feature and the last aerial featureDistance value>Weights are configured for preset trustworthiness, < +.>For a preset adjacent recognition weight, +.>Identifying weights for preset types, +.>For the preset environment recognition weight, +.>Weights are set for the preset distances, with +.>。
Further, in step A5, a type image library is configured, the type image library stores feature images corresponding to different feature types, and the trusted similarity value is obtained by obtaining the feature type of the aerial photographing feature, indexing the corresponding feature image according to the feature type, and comparing the feature image with the aerial photographing feature to obtain the corresponding trusted similarity value.
Further, in step A5, a type database is configured, where the type database stores feature abundance values and type identification values corresponding to different feature types, the feature abundance values reflect color lump abundance of the aerial feature, and the type identification values reflect contrast of adjacent color lump of the aerial feature.
Further, in step A5, an environmental function library is configured, where the environmental function library stores a plurality of different environmental time sequence recognition functions, the environmental time sequence recognition functions use time order data as indexes and are configured with color value recognition parameters, and step A5 includes determining a corresponding environmental time sequence recognition function according to the time order data, generating a corresponding color value recognition parameter according to an average color value of the aerial feature, and bringing the corresponding color value recognition parameter into the environmental time sequence recognition function.
Further, the aerial photo unmanned aerial vehicle is configured with an aerial photo adjustment strategy, when the aerial photo unmanned aerial vehicle does not recognize the corresponding aerial photo feature on the static aerial photo route, the aerial photo adjustment strategy is executed, and after the aerial photo adjustment strategy returns to the position corresponding to the last aerial photo feature, the aerial photo unmanned aerial vehicle is directly controlled to move to the position corresponding to the next aerial photo feature.
Further, in the step A2, the boundary is obtained according to the obtained mapping image and the colors, and different partitions are obtained according to the difference between the mapping land color and other mapping colors.
Further, a mapping subsystem is also included, the mapping subsystem is configured with a land mapping strategy, the land mapping strategy includes
Step C1, partitioning in a remote sensing mapping image and determining corresponding mapping points according to the partitioning;
step C2, determining real flight coordinates of a mapping point according to the actual flight trajectory of the aerial unmanned aerial vehicle;
and C3, determining the distance between mapping points according to the real flight coordinates so as to calculate the area of each subarea.
Further, step C2 includes that the aerial photo unmanned aerial vehicle is configured with a color value feature corresponding to the mapping point, if the aerial photo unmanned aerial vehicle has the color value feature in the flight process of the mapping point, the corresponding real flight coordinates are recorded, and if the obtained aerial photo image does not have the corresponding color value feature, the actual flight trajectory is corrected until the aerial photo image has the color value feature.
The invention has the beneficial effects that:
the invention is based on the combination of the aerial photographing technology and the remote sensing mapping technology, the images obtained by remote sensing mapping are firstly analyzed, the boundary is identified by comparing the image type characteristics, the boundary is taken as the aerial flight path, the images obtained by aerial photographing and the images obtained by remote sensing mapping are compared, the positions of the images are precisely mapped according to the comparison of the mapping images and the aerial photographing images, the flying distance of the aerial photographing video is measured according to the ratio of the overlapping part of the mapping images and the aerial photographing images, the distance of the mapping images is obtained, the remote sensing mapping accuracy is higher, and the problem that the remote sensing is unclear in identifying the image boundary is solved.
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Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a schematic diagram of a system architecture of a land mapping system based on remote sensing technology of the present invention;
fig. 2 is a schematic diagram of a mapping subsystem of a land mapping system based on remote sensing technology according to the present invention.
Detailed Description
The invention is further described in connection with the following detailed description, in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
In the present invention, referring to fig. 1 and 2, a land mapping system based on remote sensing technology includes an aerial unmanned aerial vehicle, a route planning subsystem and an image correction subsystem; the method has the key content that the aerial unmanned aerial vehicle is built through the image features in the remote sensing mapping image, so that the route of the aerial unmanned aerial vehicle is not easy to determine during aerial photography, firstly, the features of the boundary position are difficult to identify, but after the aerial unmanned aerial vehicle flies for a long time, the actual flight distance of the aerial unmanned aerial vehicle is possibly deviated from the flight distance and the direction calculated by theory, so that the aerial unmanned aerial vehicle is difficult to convert, the position of the aerial unmanned aerial vehicle is required to be continuously recalibrated by people, the aerial unmanned aerial vehicle is complicated and obviously difficult to be on complex terrains, the deviation caused by long-time flight of the aerial unmanned aerial vehicle is difficult to build the same coordinate system with the remote sensing mapping image, and the meaning of aerial correction does not exist, so that the method solves the problems:
the routing subsystem is configured with a routing strategy comprising
A1, acquiring a remote sensing mapping image of a target area; the remote sensing mapping image is an image about overlooking angle obtained through satellite mapping technology, and is mainly aimed at mapping land areas, but the remote sensing mapping has the problem that if the image is a city, the mapping is more accurate when the mapping is combined with a city planning image, but mapping is particularly difficult in remote places such as mountain areas and the like where the trail is difficult to reach.
A2, carrying out partition processing on the remote sensing mapping image according to the characteristic distribution and determining edge lines between partitions; in the step A2, the boundary is acquired according to the acquired mapping image and the colors, and different subareas are obtained according to the difference between the mapping soil colors and other mapping colors. Since the color features in the remote sensing mapping image can generally determine the subareas, different subareas can be distinguished through the color features, and therefore, the edge line can be obtained.
A3, generating a reference aerial photographing route according to the determined connecting line of the edge line; the method comprises the following steps of giving a re-inspection reference value to each edge line according to color difference values among the subareas, enabling the generated reference aerial photographing route to pass through each edge line, enabling the comprehensive loss value to be minimum, enabling the comprehensive loss value to be a path loss value minus a re-inspection effective value, enabling the path loss value to be positively related to the reference aerial photographing route, and summing the obtained re-inspection reference values to generate the re-inspection effective value when the reference aerial photographing route repeatedly passes through a certain edge line.
Step A4, marking aerial photographing features near a reference aerial photographing route according to remote sensing mapping images, wherein a distance range between the aerial photographing features and the reference aerial photographing route can be determined according to actual requirements; specifically, an image feature library is established, the shape and color value changes of a region near a reference aerial photographing route are identified and compared with the image feature library, so that corresponding aerial photographing features are determined, and as the type of each aerial photographing feature in the image feature library is recorded in advance, the corresponding type of the aerial photographing features is determined in the step, for example, trees near the aerial photographing route are taken as aerial photographing features, and the types of the trees are the corresponding types.
Step A5, calculating a feature identification value of each aerial feature; in the step A5, an identification feature algorithm is configured to calculate an identification feature value, where the identification feature algorithm is thatWherein, the method comprises the steps of, wherein,for identifying characteristic values, < >>And configuring a type image library for the credible similarity value of the aerial photographing feature, wherein the type image library stores feature images corresponding to different feature types, and the credible similarity value is obtained by acquiring the feature type of the aerial photographing feature and comparing the feature image with the aerial photographing feature according to the feature image corresponding to the feature type index. The credible similarity value is used for reflecting whether the image corresponding to the aerial feature is similar to the corresponding type, and the similarity degree is that the aerial feature is pine, for example, from the type, the similarity degree of the feature and the pine can be judged through image comparison, and the more similar is that the aerial feature is used for carrying out aerial recognition in aerial, the higher the reliability degree is, the better the safety degree is, and the safety degree is>For the aerial feature and adjacent +.>If one aerial feature is similar to an adjacent aerial feature, the similar value of the aerial features cannot be easily identified in the aerial path, so that the difficulty of identifying the aerial features can be judged by calculating the image corresponding to the aerial feature and the image corresponding to the adjacent aerial feature>The number of the aerial features adjacent to the aerial feature is determined according to the distance, if the distance is smaller than the threshold value of the adjacent relationship, the adjacent relationship is determined as the adjacent relationship, and the adjacent relationship is determined as the adjacent relationship>For the feature abundance value of the aerial feature, < >>The type database is configured with the type identification value of the aerial feature, the type database stores feature abundance values and type identification values corresponding to different feature types, the feature abundance values reflect the color lump abundance of the aerial feature, the type identification values reflect the contrast of adjacent color lump of the aerial feature, the color richness of the color lump and the contrast of the adjacent color lump are all data which can improve the accuracy of the identification judgment result in image identification. />The environment time sequence recognition function is configured with an environment function library, the environment function library stores a plurality of different environment time sequence recognition functions, the environment time sequence recognition functions take time order data as indexes, color value recognition parameters are configured, corresponding environment time sequence recognition functions are determined according to the time order data, corresponding color value recognition parameters are generated according to average color values of aerial photographing features, the corresponding color value recognition parameters are brought into the environment time sequence recognition functions, different color values have different adjustment parameters under different time conditions because different color recognition difficulties are different in daytime and nighttime, the recognition difficulty corresponding to different time is different, so that a function relation of illumination and time is set up, and then the actual recognition difficulty values of different aerial photographing features at different time can be judged through bringing the color values. />For the minimum distance value of the aerial characteristic position and the reference aerial route, +.>For the distance value of this aerial feature from the last aerial feature, it is theoretically necessary for each aerial feature to be as close as possible to the reference aerial route, while also being as close as possible to the coordinates of the last aerial feature,>weights are configured for preset trustworthiness, < +.>For a preset adjacent recognition weight, +.>Identifying weights for preset types, +.>For the preset environment recognition weight, +.>Weights are set for the preset distances, with +.>。
Step A6, re-performing aerial photography route planning according to the characteristic identification value to generate a static aerial photography route, wherein the static aerial photography route is a connecting line between corresponding coordinates of aerial photography characteristics;
step A7, transmitting the static aerial photographing route and the corresponding aerial photographing characteristics to the corresponding aerial photographing unmanned aerial vehicle; the identification point can be calculated and obtained through the value setting algorithm, the identification point can be a stone or a tree, the purpose is to calibrate the aerial flight track in the aerial flight process, so that the aerial flight has continuity,
the aerial photographing unmanned aerial vehicle performs aerial photographing according to the static aerial photographing route, and corrects the aerial photographing route in the aerial photographing process by identifying corresponding aerial photographing characteristics in the photographed image; the unmanned aerial vehicle is configured with an aerial photographing adjustment strategy, when the unmanned aerial vehicle does not recognize the corresponding aerial photographing feature on the static aerial photographing route, the aerial photographing adjustment strategy is executed, and after the aerial photographing adjustment strategy returns to the position corresponding to the last aerial photographing feature, the unmanned aerial vehicle is directly controlled to move to the position corresponding to the next aerial photographing feature. If the aerial photographing cannot reach the preset identification points, the flying route can be walked again by taking the front and rear identification points as the basis, so that two image information are obtained, and the average value of the two image information is used as the comparison basis.
The image modification subsystem includes an image modification strategy including
Step B1, acquiring an aerial image shot by an aerial unmanned aerial vehicle;
step B2, transferring the aerial image to a coordinate system corresponding to the remote sensing mapping image according to the position of the aerial image shot by the aerial unmanned aerial vehicle; because the route of the aerial unmanned aerial vehicle is known, the data of the aerial image can be transferred to a coordinate system corresponding to the remote sensing mapping image through the coordinates of the aerial characteristic in the remote sensing mapping image.
Step B3, comparing the aerial image with the remote sensing mapping image to obtain correction deviation; taking the aerial image as a reference, the difference value of the two images on each image point can be obtained, and the difference value image is obtained as correction deviation.
And step B4, correcting the remote sensing mapping image by correcting the deviation. And correcting the remote sensing mapping image according to a certain proportion through the difference image, so that the color value of the pixels of the remote sensing mapping image is close to that of the aerial image.
Also included is a mapping subsystem configured with a land mapping strategy comprising
Step C1, partitioning in a remote sensing mapping image and determining corresponding mapping points according to the partitioning;
step C2, determining real flight coordinates of a mapping point according to the actual flight trajectory of the aerial unmanned aerial vehicle; in step C2, the aerial unmanned aerial vehicle is configured with the color value characteristics corresponding to the mapping points, if the aerial unmanned aerial vehicle has the color value characteristics in the flight process of the mapping points, the corresponding real flight coordinates are recorded, and if the obtained aerial image does not have the corresponding color value characteristics, the actual flight trajectory is corrected until the aerial image has the color value characteristics.
And C3, determining the distance between mapping points according to the real flight coordinates so as to calculate the area of each subarea.
The mapping subsystem in a specific mapping strategy comprises a remote sensing mapping module, a land information acquisition module, a boundary analysis module, an image confirmation module, an image superposition acquisition module, a land calculation module and a server; the remote sensing mapping module, the land information acquisition module, the boundary analysis module, the image confirmation module, the image superposition acquisition module and the land calculation module are respectively connected with the server through data;
the remote sensing mapping module acquires the land map image to obtain a mapping image, and the land mapping image is conveyed to the boundary analysis module for boundary analysis and boundary mapping position determination;
when acquiring the boundary mapping position, the following is specific:
obtaining a boundary according to the obtained mapping image and colors, and obtaining a region to be measured according to the difference between the mapping land colors and other mapping colors;
the method comprises the steps of obtaining the shape of a region to be measured, drawing a mapping image, defining a mapping point at the joint of two intersecting lines according to the drawn mapping image, and forming a mapping position by all the mapping points together;
transmitting the mapping position to an image confirmation module;
the land information acquisition module carries out aerial photography on the land to be mapped through the unmanned aerial vehicle to obtain aerial photography and mapping;
when the land information acquisition module acquires the aerial photo map, the land information acquisition module comprises the following specific steps:
cruising the land to be mapped through the unmanned plane, acquiring the cruising direction in the cruising process, acquiring the cruising direction change times, and recording the land color characteristics in the cruising process and the land color characteristics at the boundary to obtain video information;
obtaining the distance in the process of changing the cruising direction each time, so as to obtain a plurality of distance values;
generating an aerial photo map according to video information, direction change times and distance values of each direction change in the cruising process;
the aerial mapping and the boundary mapping positions are conveyed to an image confirmation module, and the image confirmation module receives mapping images and combines the boundary mapping positions to confirm image superposition;
the image registration confirmation is specifically as follows:
acquiring the position information of each mapping point according to the boundary mapping position, and sequencing the direction and the direction change of the mapping points;
acquiring the aerial change direction of the aerial survey drawing, and acquiring the direction of the surveying and mapping point which is the same as the aerial direction;
acquiring video information, acquiring the color of the aerial photographing position according to the video information, comparing the acquired color with the color of the mapping position, judging whether the color difference is the same, if the color difference is the same, judging that the aerial photographing mapping is overlapped with the mapping position of the position, if the color difference is different, acquiring the direction point of which the aerial photographing change direction is the same as the mapping position again, and comparing the colors until the color difference is the same;
determining the superposition position of the aerial survey and drawing;
the image coincidence acquisition module receives the aerial photographing measuring drawing and the mapping position to carry out image comparison, and acquires the coincidence area occupation ratio;
measuring the distance of the mapping position and the distance of the aerial mapping, acquiring the occupation ratio of the overlapping region according to the measured distance of the mapping position and the distance of the aerial mapping, and transmitting the acquired occupation ratio of the overlapping region and the acquired occupation ratio of the mapping to a land calculation module;
the overlapping area ratio is transmitted to a land calculation module, time information and speed information in the aerial photographing process are acquired, the acquired time information and speed information are transmitted to the land calculation module, and the land calculation module calculates mapping distances based on the overlapping area ratio and the time information and the speed information.
When the land calculation module calculates the mapping distance, the time value and the speed value of the aerial photography in each direction in the aerial photography process are obtained according to the obtained time information and the speed information, the actual distance running in each direction is obtained by multiplying the time value by the speed value, and the actual distances in a plurality of directions are summed to obtain the mapping distance;
the area enclosed by the mapping distance is calculated according to the mapping distance, and when the land area enclosed by the mapping distance is calculated, the specific steps are as follows:
firstly, setting a datum point on the land area of a mapping distance surrounding city;
capturing the virtual speed and measuring the distance and angle of the datum point to each corner of the land by using a measuring instrument such as a total station, a laser range finder or GPS equipment;
calculating the area of the land by the data acquired by the measuring instrument;
the remote sensing technology is a technology for collecting electromagnetic radiation information of ground object targets from artificial satellites, airplanes or other aircrafts and judging and recognizing the earth environment and resources. The method is a comprehensive sensing technology which is gradually formed along with the development of aerospace technology and electronic computer technology on the basis of aerophotography and interpretation in the 60 th year. Any object has different electromagnetic wave reflection or radiation characteristics. Aerospace remote sensing is to use remote sensors installed on an aircraft to sense electromagnetic radiation characteristics of ground object targets and record the characteristics for recognition and judgment. The remote sensor is placed on an aircraft such as a high-altitude balloon, an airplane and the like for remote sensing, and is called aerial remote sensing. The remote sensor is arranged on a spacecraft for remote sensing, which is called space remote sensing. The whole set of equipment for completing the remote sensing task is called a remote sensing system. Aviation and aerospace remote sensing can sense from different heights, large ranges, fast and multi-spectral ranges, and acquire a large amount of information. Space remote sensing can also periodically obtain real-time ground object information. Therefore, the aviation and aerospace remote sensing technology is widely applied to various aspects of national economy and military. For example, in meteorological observations, resource surveys, mapping, military reconnaissance, and the like.
In another embodiment, a land mapping system based on remote sensing technology specifically includes the following steps when performing land mapping:
step C1: the remote sensing mapping module acquires a land image to obtain a mapping image, acquires a boundary according to the acquired mapping image and colors, acquires a region to be measured according to the difference between the colors of the mapping land and other mapping colors, acquires the shape of the region to be measured, draws the mapping image, defines a mapping point at the joint of two intersecting lines according to the drawn mapping image, and all the mapping points jointly form a mapping position; the mapping position is conveyed to an image confirmation module, the land mapping image is conveyed to a boundary analysis module for boundary analysis, the boundary mapping position is determined, and the position of the corresponding mapping point is determined;
step C2: cruising the land to be mapped through the unmanned plane, acquiring the cruising direction in the cruising process, acquiring the cruising direction change times, recording the land color characteristics in the cruising process and the land color characteristics at the boundary to obtain video information, and acquiring the distance in each cruising direction change process, so that a plurality of distance values are obtained; generating an aerial photo map according to video information, direction change times and distance values of each direction change in the cruising process; the aerial mapping and the boundary mapping positions are conveyed to an image confirmation module, and the image confirmation module receives mapping images and combines the boundary mapping positions to confirm image superposition; step C21: acquiring the position information of each mapping point according to the boundary mapping position, and sequencing the direction and the direction change of the mapping points; step C22: acquiring the aerial change direction of the aerial survey drawing, and acquiring the direction of the surveying and mapping point which is the same as the aerial direction; step C23: acquiring video information, acquiring the color of the aerial photographing position according to the video information, comparing the acquired color with the color of the mapping position, and judging whether the color difference is the same or not; step C24: if the color difference is the same, the aerial photographing measuring drawing is judged to be coincident with the mapping position of the position, if the color difference is different, the direction point of the aerial photographing changing direction, which is the same as the mapping point position, is acquired again, and color comparison is carried out until the color difference is the same.
Step C31: measuring the distance of the mapping position and the distance of the aerial mapping, acquiring the occupation ratio of the overlapping region according to the measured distance of the mapping position and the distance of the aerial mapping, and transmitting the acquired occupation ratio of the overlapping region and the acquired occupation ratio of the mapping to a land calculation module; step C32: the overlapping area ratio is transmitted to a land calculation module, time information and speed information in the aerial photographing process are acquired, the acquired time information and speed information are transmitted to the land calculation module, and the land calculation module calculates mapping distances based on the overlapping area ratio and the time information and the speed information.
When land calculation is performed, the specific steps are as follows: when the land calculation module calculates the mapping distance, the time value and the speed value of the aerial photography in each direction in the aerial photography process are obtained according to the obtained time information and the speed information; calculating the actual distance of each direction running by multiplying the time value by the speed value, and summing the actual distances of a plurality of directions to obtain a mapping distance; firstly, setting a datum point on the land area of a mapping distance surrounding city; capturing the virtual speed and measuring the distance and angle of the datum point to each corner of the land by using a measuring instrument such as a total station, a laser range finder or GPS equipment; the area of the land is calculated from the data obtained by the measuring instrument. The data is calculated in an auxiliary mode through the measuring instrument, and therefore the mapping area is obtained. It should be noted that, the relationship between the mapping subsystem and the correction logic is that the corrected remote sensing mapping image is more accurate as a mapping basis, and the aerial unmanned aerial vehicle is loaded with the remote sensing mapping image, so that the mapping is performed by controlling the actual flight path of the aerial unmanned aerial vehicle, and the method is more convenient.
The above formulas are all formulas for removing dimensions and taking numerical calculation, the formulas are formulas for obtaining the latest real situation by collecting a large amount of data and performing software simulation, preset parameters in the formulas are set by a person skilled in the art according to the actual situation, if weight coefficients and proportion coefficients exist, the set sizes are specific numerical values obtained by quantizing the parameters, the subsequent comparison is convenient, and the proportional relation between the weight coefficients and the proportion coefficients is not influenced as long as the proportional relation between the parameters and the quantized numerical values is not influenced.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media having computer-usable program code embodied therein.
The above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (4)
1. The land mapping system based on the remote sensing technology is characterized by comprising an aerial unmanned aerial vehicle, a route planning subsystem, an image correction subsystem and a mapping subsystem;
the routing subsystem is configured with a routing strategy comprising
A1, acquiring a remote sensing mapping image of a target area;
a2, carrying out partition processing on the remote sensing mapping image according to the characteristic distribution and determining edge lines between partitions;
a3, generating a reference aerial photographing route according to the determined connecting line of the edge line;
a4, marking aerial photographing features near a reference aerial photographing route according to the remote sensing mapping image;
step A5, calculating the feature identification value of each aerial feature,
is provided with an identification feature algorithm for calculating identification feature values, wherein the identification feature algorithm is used for identifyingThe characteristic algorithm is thatWherein->For identifying characteristic values, < >>For the trusted similarity value of the aerial feature, < +.>For the aerial feature and adjacent +.>Similarity of individual aerial features, +.>For the number of aerial features adjacent to the aerial feature, < >>For the feature abundance value of the aerial feature, < >>Identifying a value for the type of the aerial feature, < >>For the environmental time sequence recognition function, +.>For the minimum distance value of the aerial characteristic position and the reference aerial route, +.>For the distance value of the aerial feature from the last aerial feature, < >>Is a pre-preparationTrusted configuration weights set, +.>For a preset adjacent recognition weight, +.>Identifying weights for preset types, +.>For the preset environment recognition weight, +.>Weights are set for the preset distances, with +.>；
The method comprises the steps that a type image library is configured, characteristic images are stored in the type image library corresponding to different characteristic types, and the credible similarity value is obtained by acquiring the characteristic types of aerial photographing characteristics and comparing the characteristic images with the aerial photographing characteristics according to the characteristic images corresponding to characteristic type indexes;
the method comprises the steps of configuring a type database, wherein the type database stores feature abundance values and type identification values corresponding to different feature types, the feature abundance values reflect color lump abundance of the aerial photography feature, and the type identification values reflect contrast of adjacent color lump of the aerial photography feature;
the method comprises the steps that an environment function library is configured, the environment function library stores a plurality of different environment time sequence recognition functions, the environment time sequence recognition functions take time order data as indexes, and color value recognition parameters are configured, the step A5 comprises the steps of determining corresponding environment time sequence recognition functions according to the time order data, generating corresponding color value recognition parameters according to average color values of aerial photographing characteristics, and bringing the corresponding color value recognition parameters into the environment time sequence recognition functions;
step A6, re-planning an aerial photographing route according to the characteristic identification value to generate a static aerial photographing route, wherein the static aerial photographing route is a connecting line between corresponding coordinates of aerial photographing characteristics;
step A7, transmitting the static aerial photographing route and the corresponding aerial photographing characteristics to the corresponding aerial photographing unmanned aerial vehicle;
the aerial photographing unmanned aerial vehicle performs aerial photographing according to the static aerial photographing route, and corrects the aerial photographing route in the aerial photographing process by identifying corresponding aerial photographing characteristics in the photographed image;
the image modification subsystem includes an image modification strategy including
Step B1, acquiring an aerial image shot by an aerial unmanned aerial vehicle;
step B2, transferring the aerial image to a coordinate system corresponding to the remote sensing mapping image according to the position of the aerial image shot by the aerial unmanned aerial vehicle;
step B3, comparing the aerial image with the remote sensing mapping image to obtain correction deviation;
step B4, correcting the remote sensing mapping image through correcting deviation;
the mapping subsystem is configured with a land mapping strategy comprising
Step C1, partitioning in a remote sensing mapping image and determining corresponding mapping points according to the partitioning;
step C2, determining actual flight coordinates of mapping points according to the actual flight trajectory of the aerial unmanned aerial vehicle;
and C3, determining the distance between mapping points according to the real flight coordinates so as to calculate the area of each subarea.
2. The land mapping system of claim 1, wherein the aerial unmanned aerial vehicle is configured with an aerial adjustment strategy, and when the aerial unmanned aerial vehicle does not recognize the corresponding aerial feature on the static aerial route, the aerial adjustment strategy is executed, and after the aerial adjustment strategy returns to the position corresponding to the previous aerial feature, the unmanned aerial vehicle is directly controlled to move to the position corresponding to the next aerial feature.
3. The land mapping system according to claim 1, wherein the step A2 includes obtaining the boundary according to the obtained mapping image and obtaining different areas according to the difference between the mapping land color and other mapping colors.
4. The land mapping system based on remote sensing technology as set forth in claim 1, wherein step C2 includes, configuring the aerial unmanned aerial vehicle with color value characteristics corresponding to the mapping points, if the aerial unmanned aerial vehicle has color value characteristics in the flight process of the mapping points, recording corresponding actual flight coordinates, and if the aerial unmanned aerial vehicle does not have corresponding color value characteristics, correcting the actual flight trajectory until the aerial image has color value characteristics.
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