CN117367429B - Remote sensing image-based working base map and unmanned aerial vehicle technology-based route image control point distribution algorithm - Google Patents
Remote sensing image-based working base map and unmanned aerial vehicle technology-based route image control point distribution algorithm Download PDFInfo
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Abstract
The invention relates to the field of river and lake demarcation, and particularly discloses a working base map based on remote sensing images and a route image control point distribution algorithm of an unmanned aerial vehicle technology, wherein the route image control point distribution working flow of the river and lake demarcation unmanned aerial vehicle technology is as follows: s1, determining an aerial survey range; s2, performing data processing according to the working base diagram; s3, establishing a 3D model; s4, setting two groups of unmanned aerial vehicles to perform image control point layout; s5, comparing and recording data through 3D simulation in the flight process of the unmanned aerial vehicle; s6, comparing the flight route of the unmanned aerial vehicle with an initial demarcation line, and analyzing the image control points with differences; and S7, correcting, namely distributing all correct image control points. Combines the traditional measurement technology with the orthographic image, carries on a plurality of sensors on same platform, full-automatic, multi-angle, high efficiency, accurate shooting just can acquire massive high accuracy data in a short time to can correct the image control point according to actual position and accomplish more accurately.
Description
Technical Field
The invention relates to the field of river and lake demarcation, in particular to a working base map based on remote sensing images and a route image control point distribution algorithm of unmanned aerial vehicle technology.
Background
Water is a source of living and growing spring by which humans and even everything depend. The importance of the river channel as an important carrier of water is self-evident. Along with the rapid development of economy and the rapid improvement of productivity, the development of the river is increasingly strengthened, and the flood control pressure of the river is increased due to serious invasion of partial river. Meanwhile, the problems of river pollution, unreasonable sand collection around the river, unrestrained river flood-passing areas and the like exist. In order to solve the problems, firstly, the river channel defining work is done, the preliminary preparation is done for the river channel repairing work, and the basic guarantee is provided for the comprehensive river channel treatment. Therefore, the method is particularly important to carry out scientific, reasonable and efficient river channel right-defining demarcation work.
Aerial photogrammetry is a photo taken from the air by an aircraft-mounted sensor such as an airplane and a satellite, and is used for acquiring POS information in combination with a navigation positioning system carried by the aircraft during shooting, and producing a Digital Elevation Model (DEM), a Digital Line Graph (DLG), a Digital Orthophoto Map (DOM) and a digital grid map (DRG) after being processed by internal industry in combination with a ground control point.
In recent years, with the continuous development of the technology of unmanned aerial vehicles in China, low-altitude unmanned aerial vehicle aerial photography is generally carried out by a single-phase inverter with the weight of about 500g on a light-weight and small-size unmanned aerial vehicle to fly at low altitude, a photo is shot according to technical requirements, the position and posture data of the unmanned aerial vehicle recorded in the shooting moment are combined with a real-time differential system or a rear differential system of the aircraft, after the photo is calibrated by the position, the posture parameter pos of the photo is formed, and the two data form complete aerial photogrammetry raw data. The low-altitude unmanned aerial vehicle aerial photogrammetry has the advantages that strict airspace restriction is not needed for a plurality of areas, the flying height is generally within 1km, the requirements on a take-off site are simple, the operation is simple, the low-altitude unmanned aerial vehicle aerial photogrammetry can be adjusted correspondingly in time for a plurality of emergency situations, and the low-altitude unmanned aerial vehicle aerial photogrammetry is very flexible in practical application, so that the low-altitude unmanned aerial vehicle aerial photogrammetry is rapidly popularized and popular, and the low-altitude unmanned aerial vehicle aerial photogrammetry is widely favored by various surveying and mapping units.
The traditional geographic relevant information acquisition mode is mainly carried out manually point by point, the method has complex procedures, needs a great deal of time and labor, has unsophisticated results, and can not be operated even in places, such as dangerous steep cliffs which can not be reached by the labor. The conventional field measurement method is adopted to conduct the embankment-free river channel right-determining demarcation work, so that the problems of long time consumption, huge cost, low drawing precision caused by drawing errors, low information sharing efficiency among multiple departments and the like exist.
Therefore, we propose a working base map based on remote sensing images and a route image control point distribution algorithm of unmanned aerial vehicle technology to solve the above problems.
Disclosure of Invention
The invention aims to provide a remote sensing image-based working base map and an unmanned aerial vehicle technology-based route image control point distribution algorithm, so as to solve the problems that in the background technology, the traditional geographic relevant information acquisition mode is mainly carried out manually point by point, the method is complex in procedure, requires a large amount of time and labor, and results are not fine, and even places cannot work, such as dangerous steep cliffs which cannot be reached by the labor. The conventional field measurement method is adopted to conduct the embankment-free river channel right-determining demarcation work, so that the problems of long time consumption, huge cost, low drawing precision caused by drawing errors, low information sharing efficiency among multiple departments and the like exist.
In order to achieve the above purpose, the invention provides a remote sensing image-based working base map and unmanned aerial vehicle technology route image control point distribution algorithm, and a river and lake demarcation unmanned aerial vehicle technology route image control point distribution work flow is as follows:
s1, determining an aerial survey range, and determining a working base map through a remote sensing image;
S2, carrying out data processing according to the working base map to obtain 3D point cloud data of the river reach and proportional orthophoto data;
S3, establishing a 3D model, setting a route path of the unmanned aerial vehicle, inserting unmanned aerial vehicle data into the 3D model, and performing demarcation scene simulation;
S4, arranging image control points by two groups of unmanned aerial vehicles, marking special points including embankments, farmlands, villages, roads and the like, analyzing the relative positions of the two unmanned aerial vehicles and the river, and calculating the safe positions to obtain initial demarcations;
S5, according to the delimited safety data, the unmanned aerial vehicle carries out flight acquisition according to the image control points after data processing, and data comparison and recording can be carried out through 3D simulation in the flight process;
S6, comparing the flight route of the unmanned aerial vehicle with the initial demarcation line, analyzing the image control points with differences in the comparison process, and then correcting the safety demarcation line according to the 3D model;
And S7, after correction is completed, distributing all correct image control points, realizing real-time simulation through 3D, storing data, and then forming actual demarcation data.
In a further embodiment, establishing the 3D model requires determining the range of the dike-free river reach through on-site investigation and data collection, based on stereopair, orthographic images and river channel large section measurement data.
In a further embodiment, the 3D model is built by using HEC-RAS software to build a one-dimensional mathematical model of the river channel to calculate and analyze a water surface line of the river channel, drawing a line of intersection of the designed water surface line and a bank slope to obtain a reference line of a riverbank-free river channel management range, using an ArcScene three-dimensional model to analyze a submerged range, checking rationality, and when obtaining accurate DEM data of a research area, using ArcScene to perform 3D visualization, obtaining elevation from the DEM surface, and floating an orthographic image on the DEN surface to obtain the 3D model.
In a further embodiment, the unmanned aerial vehicle route image control point correction algorithm comprises the following steps:
s1: in the process of laying the unmanned aerial vehicle image control points, determining the positioning condition of the image control points according to demarcation requirements;
s2: when the unmanned aerial vehicle reaches the position of the image control point, the image control point needs to be corrected if the actual data does not meet the demarcation requirement;
S3: the unmanned plane adjusts the position according to the actual situation, uploads correction information and photographic information and moves to an accurate image control point, and meanwhile, the accurate image control point position is uploaded and the scribing is simulated in real time;
s4: and when the image control point reached by the unmanned aerial vehicle meets the demarcation requirement, uploading signals directly and simulating scribing in real time.
In a further embodiment, the corrective imaging control point needs to be inserted with a range of safety data and special location data including bank, farmland, village, road and obstacle, etc.
In a further embodiment, the unmanned aerial vehicle image control point correction is to resample the image to be encrypted by using a distortion correction module in the space three encryption software according to the given distortion parameter in the camera, output the corrected image, then establish the navigation belt, add the corrected image, and rotate and adjust the navigation belt according to the rotation direction of the image when the distortion is corrected, import POS data, and output new image control point position information.
In a further embodiment, two groups of unmanned aerial vehicles fly synchronously, one group of unmanned aerial vehicles carries on the signal base station, the other group of unmanned aerial vehicles carries on the camera shooting equipment, signal transmission is carried between the two groups of unmanned aerial vehicles, and signal interference prevention equipment is carried between the two groups of unmanned aerial vehicles.
In a further embodiment, the image in-process flow is:
S1: matching images;
s2: utilizing the encryption result and the original image data to orient and restore the stereoscopic model;
s3: three-dimensional editing of DEM;
s4: DOM data production;
s5: orthorectification is carried out based on the space three encryption result and the measured DEM result;
s6: and (5) making the DSM by using the visual three-dimensional model and performing subsequent work.
In a further embodiment, the image matching is performed by establishing a data processing project of a clustered data processing system, and performing multi-core multi-thread image matching by using an air-to-air encryption result and original image data to generate an initial DEM of a region;
In a further embodiment, the DEM stereoscopic editing is to load an initial DEM of a corresponding area in a stereoscopic environment, modify areas such as buildings, trees, bridges and the like by using a system editing tool, edit flying spots and error areas which fail to reflect the actual surface elevation, and output the edited areas as a result DEM after data edge connection and quality inspection.
Compared with the prior art, the invention has the beneficial effects that:
According to the invention, the precision of the topographic map of the river reach is basically in accordance with the requirement through the low-altitude unmanned aerial vehicle photogrammetry, a relatively accurate base map is provided for planning the subsequent management range line and the protection range line, the traditional mapping data acquisition method is improved, the working difficulty and strength of field workers are greatly reduced, an effective method is provided for delimiting the river and the lake, convenience is provided for topographic map measurement, and the topographic map measurement of various scales can be realized through using unmanned aerial vehicles and cameras of different types.
According to the invention, the site can be restored to a great extent through three-dimensional modeling, when the accurate DEM data of a research area are obtained, the ArcScene is used for 3D visualization, and in the definition of the river management range of a mountain area, the elevation is obtained from the DEM surface, so that the orthographic image floats on the DEN surface to obtain the three-dimensional model. The effect similar to a sand table not only increases the third dimension, but also provides information support for planning and design of land development and arrangement, can have visual understanding to the slope direction of the surrounding mountain slope, water source distribution condition, original road facilities and drainage and irrigation facilities layout, and also provides convenience for follow-up related works, such as: river management, river planning, river bank construction and the like, and realizes one-time aerial survey of results and multiple utilization.
According to the invention, the software functional module is utilized to adjust the constructed free network, the connection points with larger rough differences are removed step by step, the number and distribution of the connection points are ensured, and meanwhile, the precision of the free network is improved, so that the precision of the adjustment of the subsequent regional network is ensured. And importing coordinate data of control points of the aerial photo, firstly observing image point coordinates of the photo control points at four corners of a region to be encrypted, then carrying out preliminary control network adjustment, on the basis, turning points of other photo control points and detection points by means of a prediction function of software and by comparing the control points, calling an adjustment module to carry out regional network adjustment after all photo control points and detection points are observed, checking whether the precision of the air-third is required to meet the specification requirement by using the detection points, and outputting the air-third encryption result if the precision is required to meet the air-third specification requirement. The traditional measurement technology is combined with the orthographic image, a plurality of sensors are carried on the same platform, and the full-automatic multi-angle high-efficiency accurate shooting can be realized, so that massive high-precision data can be obtained in a short time, and the requirements of reducing the cost and shortening the project time of the river and lake demarcation work can be met.
Drawings
Fig. 1 is a schematic diagram of the overall structure of a remote sensing image-based working base map and a route image control point distribution algorithm of unmanned aerial vehicle technology;
FIG. 2 is a schematic diagram of an unmanned aerial vehicle route in a remote sensing image-based work base map and unmanned aerial vehicle technology-based route image control point distribution algorithm;
fig. 3 is a working base map based on remote sensing images and an image demarcation workflow in a course image control point distribution algorithm of unmanned aerial vehicle technology.
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, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1 to 3, in the embodiment of the present invention, a working base map based on remote sensing images and a line image control point distribution algorithm of unmanned aerial vehicle technology, a line image control point distribution workflow of river and lake demarcation unmanned aerial vehicle technology is as follows:
s1, determining an aerial survey range, and determining a working base map through a remote sensing image;
S2, carrying out data processing according to the working base map to obtain 3D point cloud data of the river reach and proportional orthophoto data;
S3, establishing a 3D model, setting a route path of the unmanned aerial vehicle, inserting unmanned aerial vehicle data into the 3D model, and performing demarcation scene simulation;
S4, arranging image control points by two groups of unmanned aerial vehicles, marking special points including embankments, farmlands, villages, roads and the like, analyzing the relative positions of the two unmanned aerial vehicles and the river, and calculating the safe positions to obtain initial demarcations;
S5, according to the delimited safety data, the unmanned aerial vehicle carries out flight acquisition according to the image control points after data processing, and data comparison and recording can be carried out through 3D simulation in the flight process;
S6, comparing the flight route of the unmanned aerial vehicle with the initial demarcation line, analyzing the image control points with differences in the comparison process, and then correcting the safety demarcation line according to the 3D model;
And S7, after correction is completed, distributing all correct image control points, realizing real-time simulation through 3D, storing data, and then forming actual demarcation data.
The traditional measurement technology is combined with the orthographic image, a plurality of sensors are carried on the same platform, and the full-automatic multi-angle high-efficiency accurate shooting can be realized, so that massive high-precision data can be obtained in a short time, and the requirements of reducing the cost and shortening the project time of the river and lake demarcation work can be met.
The accuracy of the topographic map of the river reach obtained through the low-altitude unmanned aerial vehicle photogrammetry basically meets the requirements, a relatively accurate base map is provided for planning of subsequent management range lines and protection range lines, a traditional mapping data acquisition method is reformed, working difficulty and strength of field workers are greatly reduced, an effective method is provided for delimiting rivers and lakes, convenience is provided for topographic map measurement, and topographic map measurement of various scales can be achieved through unmanned aerial vehicles and cameras of different models.
The 3D model is established by determining the range of the riverbank by on-site investigation and data collection, and is based on stereopair, orthophoto and river channel large section measurement data.
And (3) establishing a river channel one-dimensional mathematical model by utilizing HEC-RAS software, calculating and analyzing a river channel design water surface line, drawing a water surface line and a bank slope intersection line to obtain a dyke-free river channel management range datum line, analyzing a submerged range by utilizing an ArcScene three-dimensional model, checking rationality, and when the accurate DEM data of a research area are obtained, carrying out 3D visualization by utilizing the ArcScene, acquiring an elevation from the surface of the DEM, and floating an orthographic image on the surface of the DEN to obtain a 3D model.
Through three-dimensional modeling, the scene can be restored to a great extent, when the accurate DEM data of a research area are obtained, the ArcScene is used for carrying out 3D visualization, in the definition of the management range of a mountain river channel, the elevation is obtained from the surface of the DEM, and the orthographic image is floated on the surface of the DEN to obtain a three-dimensional model. The effect similar to a sand table not only increases the third dimension, but also provides information support for planning and design of land development and arrangement, can have visual understanding to the slope direction of the surrounding mountain slope, water source distribution condition, original road facilities and drainage and irrigation facilities layout, and also provides convenience for follow-up related works, such as: river management, river planning, river bank construction and the like, and realizes one-time aerial survey of results and multiple utilization.
And the software functional module is used for carrying out adjustment on the constructed free network, and the connection points with larger rough differences are removed step by step, so that the precision of the free network is improved while the number and distribution of the connection points are ensured, and the precision of the subsequent regional network adjustment is ensured. And importing coordinate data of control points of the aerial photo, firstly observing image point coordinates of the photo control points at four corners of a region to be encrypted, then carrying out preliminary control network adjustment, on the basis, turning points of other photo control points and detection points by means of a prediction function of software and by comparing the control points, calling an adjustment module to carry out regional network adjustment after all photo control points and detection points are observed, checking whether the precision of the air-third is required to meet the specification requirement by using the detection points, and outputting the air-third encryption result if the precision is required to meet the air-third specification requirement. The traditional measurement technology is combined with the orthographic image, a plurality of sensors are carried on the same platform, and the full-automatic multi-angle high-efficiency accurate shooting can be realized, so that massive high-precision data can be obtained in a short time, and the requirements of reducing the cost and shortening the project time of the river and lake demarcation work can be met.
The unmanned aerial vehicle image control point layout steps are as follows:
s1: determining the positioning condition of the image control point according to the demarcation requirement,
S2: when the unmanned aerial vehicle reaches the position of the image control point, the image control point needs to be corrected when the actual data does not meet the demarcation requirement, the image control point needs to be corrected, the safety data range and the special position data need to be inserted into the image control point, the special position data comprise a embankment, a farmland, a village, a road, an obstacle and the like,
S3: then the unmanned plane performs position adjustment according to the actual situation, uploads correction information and photographic information and moves to an accurate image control point, and meanwhile, the accurate image control point position is uploaded and scribing is simulated in real time;
s4: and when the image control point reached by the unmanned aerial vehicle meets the demarcation requirement, uploading signals directly and simulating scribing in real time.
The unmanned aerial vehicle image control point correction is to resample an image to be encrypted by using a distortion correction module in space three encryption software according to given distortion parameters in a camera, output the corrected image, then establish a navigation belt, add the corrected image, rotate and adjust the navigation belt according to the rotation direction of the image during distortion correction, import POS data and output new image control point position information.
Two sets of unmanned aerial vehicles fly in step, and a set of unmanned aerial vehicle carries on signal base station, and another set of unmanned aerial vehicle carries on camera photographic arrangement, signal transmission between two sets of unmanned aerial vehicles carries on between two sets of unmanned aerial vehicles and prevents signal interference equipment. The difficulty in the arrangement of the image control points is that the RTK stepping on the points is difficult because the signals of the mountain and the large trench are weak or the signals are directly absent. Through setting up two unmanned aerial vehicle equipment, one carries out RTK and steps on the point, and one is equivalent to the dynamic information base station and provides the signal, can realize that the developments steps on the point and provides the signal dynamically.
The image internal processing flow is as follows:
S1: image matching: establishing PHOTOMOD a data processing project of a clustered data processing system, and performing multi-core multi-thread image matching by using the blank three encryption result and the original image data to generate an initial DEM of a region;
s2: three-dimensional modeling: and utilizing the encryption result and the original image data to orient and restore the stereoscopic model.
S3: DEM stereoscopic editing: loading an initial DEM of a corresponding area in a three-dimensional environment, modifying the areas such as buildings, trees, bridges and the like by adopting a system editing tool, editing flying spots and error areas which fail to reflect the actual surface elevation, and outputting the obtained product DEM after data edge connection and quality inspection;
S4: DOM data production: DOM data production takes aerial photography result images as data sources.
S5: orthorectification is carried out based on PHOTOMOD blank three encryption achievements and a measured DEM achievements;
s6: finally, combining ContextCapture software, and making DSM and subsequent work by using the visual three-dimensional model.
In the prior art, characteristic points are collected point by using RTK, an field sketch is drawn, data is led out to a computer, and then related software is used for connection according to the sketch and post-related processing to obtain required results.
The unmanned aerial vehicle performing oblique photogrammetry comprises the following steps: obtaining field data, matching various image data, correcting and processing adjustment, processing an orthographic image, carrying out overall analysis according to aerial shooting data of the research project area and other collected data of the area, and defining a river 1 by adopting a river and lake management range developed by an aerial photogrammetry technology: 2000 cadastral mapping work tasks include links such as aerial flight data inspection, photo control measurement, space three encryption, DOM production, DEM production, result arrangement and submission, and the like, quality key nodes are strictly controlled, and the next link is handed over after quality inspection of each link is qualified.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
Claims (10)
1. The remote sensing image-based working base map and unmanned aerial vehicle technology route image control point distribution algorithm is characterized in that the river and lake demarcation unmanned aerial vehicle technology route image control point distribution workflow is as follows:
s1, determining an aerial survey range, and determining a working base map through a remote sensing image;
S2, carrying out data processing according to the working base map to obtain 3D point cloud data of the river reach and proportional orthophoto data;
S3, establishing a 3D model, setting a route path of the unmanned aerial vehicle, inserting unmanned aerial vehicle data into the 3D model, and performing demarcation scene simulation;
S4, arranging image control points by two groups of unmanned aerial vehicles, marking special points including embankments, farmlands, villages and roads, analyzing the relative positions of the two unmanned aerial vehicles and the river, and calculating the safe positions to obtain initial demarcations;
S5, carrying out flight acquisition by the unmanned aerial vehicle according to the delimited safety data and the image control points after data processing, and carrying out data comparison and recording through 3D simulation in the flight process;
S6, comparing the flight route of the unmanned aerial vehicle with the initial demarcation line, analyzing the image control points with differences in the comparison process, and then correcting the safety demarcation line according to the 3D model;
And S7, after correction is completed, distributing all correct image control points, realizing real-time simulation through 3D, storing data, and then forming actual demarcation data.
2. The remote sensing image-based working base map and unmanned aerial vehicle technology-based route image control point distribution algorithm according to claim 1, wherein the 3D model is established by determining the range of a dike-free river reach through on-site investigation and data collection, and is based on stereopair, orthographic images and river channel large section measurement data.
3. The remote sensing image-based working base map and unmanned aerial vehicle technology-based route image control point distribution algorithm according to claim 2, wherein the 3D model is built by using software to build a one-dimensional mathematical model of a river channel to calculate and analyze a river channel design water surface line, drawing a water surface line and a bank slope intersection line to obtain a dyke-free river channel management range datum line, using a three-dimensional model to analyze a submerged range, checking rationality, when accurate DEM data of a research area are obtained, performing 3D visualization, acquiring an elevation from the surface of the DEM, and enabling an orthophoto to float on the surface of the DEM to obtain the 3D model.
4. The remote sensing image-based working base map and unmanned aerial vehicle technology-based course image control point distribution algorithm according to claim 1, wherein the unmanned aerial vehicle course image control point correction algorithm comprises the following steps:
s1a: in the process of laying the unmanned aerial vehicle image control points, determining the positioning condition of the image control points according to demarcation requirements;
S2a: when the unmanned aerial vehicle reaches the position of the image control point, the image control point needs to be corrected if the actual data does not meet the demarcation requirement;
s3a: the unmanned plane adjusts the position according to the actual situation, uploads correction information and photographic information and moves to an accurate image control point, and meanwhile, the accurate image control point position is uploaded and the scribing is simulated in real time;
S4a: and when the image control point reached by the unmanned aerial vehicle meets the demarcation requirement, uploading signals directly and simulating scribing in real time.
5. The remote sensing image-based work base map and unmanned aerial vehicle technology-based route image control point distribution algorithm according to claim 1, wherein the corrected image control points need to be inserted with a safe data range and special position data including embankments, farms, villages, roads and obstacles.
6. The remote sensing image-based work base map and unmanned aerial vehicle technology-based route image control point distribution algorithm according to claim 1, wherein unmanned aerial vehicle image control point correction is to resample an image to be encrypted by using a distortion correction module in space three encryption software according to given distortion parameters in a camera, output the corrected image, then establish a navigation belt, add the corrected image, and rotate and adjust the navigation belt according to the rotation direction of the image when distortion correction, import POS data, and output new image control point position information.
7. The remote sensing image-based work base map and unmanned aerial vehicle technology-based route image control point distribution algorithm according to claim 1, wherein two groups of unmanned aerial vehicles fly synchronously, one group of unmanned aerial vehicles carries a signal base station, the other group of unmanned aerial vehicles carries a camera shooting device, signal transmission is carried between the two groups of unmanned aerial vehicles, and a signal interference prevention device is carried between the two groups of unmanned aerial vehicles.
8. The remote sensing image-based work base map and unmanned aerial vehicle technology-based route image control point distribution algorithm of claim 6, wherein the image internal processing flow is as follows:
S1b: matching images;
s2b: utilizing the encryption result and the original image data to orient and restore the stereoscopic model;
s3b: three-dimensional editing of DEM;
S4b: DOM data production;
s5b: orthorectification is carried out based on the space three encryption result and the measured DEM result;
s6b: and (5) making the DSM by using the visual three-dimensional model and performing subsequent work.
9. The remote sensing image-based work base map and unmanned aerial vehicle technology-based route image control point distribution algorithm according to claim 8, wherein the image matching is to generate an initial DEM of a region by establishing a data processing project of a clustered data processing system, and performing multi-core multi-thread image matching by using an air-to-three encryption result and original image data.
10. The remote sensing image-based working base map and unmanned aerial vehicle technology-based route image control point distribution algorithm according to claim 8, wherein the three-dimensional edition of the DEM is to load a corresponding area initial DEM in a three-dimensional environment, modify areas of buildings, trees and bridges by using a system editing tool, edit flying spots and error areas which fail to reflect the actual ground surface elevation, and then output as a result DEM after data edge connection and quality inspection.
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