CN114993270A - Unmanned aerial vehicle thermal melting lake and pond hydrological monitoring system - Google Patents
Unmanned aerial vehicle thermal melting lake and pond hydrological monitoring system Download PDFInfo
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- CN114993270A CN114993270A CN202210581744.1A CN202210581744A CN114993270A CN 114993270 A CN114993270 A CN 114993270A CN 202210581744 A CN202210581744 A CN 202210581744A CN 114993270 A CN114993270 A CN 114993270A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 129
- 238000002844 melting Methods 0.000 title claims abstract description 17
- 230000008018 melting Effects 0.000 title claims abstract description 17
- 239000012943 hotmelt Substances 0.000 claims abstract description 57
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 28
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 claims abstract description 25
- 238000013135 deep learning Methods 0.000 claims abstract description 17
- 238000013480 data collection Methods 0.000 claims description 39
- 238000004891 communication Methods 0.000 claims description 30
- 238000012545 processing Methods 0.000 claims description 22
- 238000003702 image correction Methods 0.000 claims description 18
- 230000003628 erosive effect Effects 0.000 claims description 13
- 230000001932 seasonal effect Effects 0.000 claims 2
- 238000000034 method Methods 0.000 abstract description 5
- 230000004927 fusion Effects 0.000 description 11
- 238000010586 diagram Methods 0.000 description 4
- 239000002689 soil Substances 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000010792 warming Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000010309 melting process Methods 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C13/00—Surveying specially adapted to open water, e.g. sea, lake, river or canal
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/183—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
Abstract
The invention discloses a hydrological monitoring system of an unmanned aerial vehicle thermal melting lake pond, which relates to the field of hydrological monitoring, and adopts the technical scheme that the hydrological monitoring system comprises a monitoring unmanned aerial vehicle, a hydrological monitoring host is arranged in the monitoring unmanned aerial vehicle, the hydrological monitoring host comprises an environment monitoring system, a flight control system, an image system, a data collecting module and an alarm module, the environment monitoring system comprises a water flow monitoring module, a temperature monitoring module and a vegetation covering module, and the water flow, the temperature and the vegetation covering around the thermal melting lake pond are monitored by the environment monitoring system; the flight control system comprises a deep learning module, a route planning system, a hovering monitoring module, a CMOS camera and a laser radar system, images outside the hot melt lake are shot through the CMOS camera in the process that the monitoring unmanned aerial vehicle flies, and specific geographic information outside the hot melt lake is collected through the laser radar system, so that the collection of data around the hot melt lake is greatly improved.
Description
Technical Field
The invention relates to the technical field of hydrological monitoring, in particular to a hydrological monitoring system of an unmanned aerial vehicle hot-melt lake pond.
Background
In recent decades, Qinghai-Tibet plateau has experienced constant warming. The gradual warming of the climate changes the thermal state of the surface of the Qinghai-Tibet plateau, so that the active layer is continuously deepened, and the underground ice near the upper limit is continuously melted, thereby the thermal melting process is intensified, a large number of thermal melting lakes are formed after the surface is sunk with water, and the area and the number of the thermal melting lakes are changed. The formation and expansion of the hot melt lake pond affect the hydrologic cycle, the production confluence process, the water balance and the distribution of plateau water resources in plateau permafrost regions.
The thermal melting pond obviously changes the thermal state of soil at the lower part and the surrounding area of the thermal melting pond, so that the thermal state of the soil around the thermal melting pond is in a dynamic balance state, the thermal influence of the thermal melting pond is also influenced by the heat of the surrounding permafrost, the water in the thermal melting pond has stronger permeability and shows stronger lateral thermal erosion action, and the lateral thermal erosion action range is gradually enlarged along with the depth, thereby causing serious influence on the surrounding frozen soil.
However, the conventional thermal fusion lake pond monitoring device is generally explored periodically by manpower, and on the basis of consuming a large amount of manpower, the statistical result is easy to deviate, and timely alarm is difficult to be performed on the erosion speed of the thermal fusion lake pond according to the environment around the thermal fusion lake pond, so that an unmanned aerial vehicle thermal fusion lake pond hydrology monitoring system is needed.
Disclosure of Invention
The invention aims to provide an unmanned aerial vehicle thermal fusion lake pond hydrology monitoring system, which aims to solve the defects that in the prior art, a large amount of manpower is consumed by manual periodic exploration, meanwhile, the statistical result is easy to deviate, and timely alarming is difficult to be carried out on the erosion speed of a thermal fusion lake pond according to the environment around the thermal fusion lake pond.
In order to achieve the purpose, the invention adopts the following technical scheme:
the hydrological monitoring system of the unmanned aerial vehicle thermal melting pond comprises a monitoring unmanned aerial vehicle, wherein a hydrological monitoring host is arranged inside the monitoring unmanned aerial vehicle, the hydrological monitoring host comprises an environment monitoring system, a flight control system, an image system, a data collection module and an alarm module, the environment monitoring system comprises a water flow monitoring module, a temperature monitoring module and a vegetation covering module, and the environment monitoring system is used for monitoring the water flow, the temperature and vegetation covering around the thermal melting pond;
the flight control system comprises a deep learning module, a route planning system, a hovering monitoring module, a CMOS camera and a laser radar system, the flight control system regulates and controls the flight path and the monitoring position of the monitoring unmanned aerial vehicle, the image system comprises an image acquisition module, an image processing module, an image recognition module, an image correction module and an image splicing module, the image system acquires external images, simultaneously performs primary processing and recognition on the acquired images, and then corrects and splices the recognized images;
the data collection module collects external numerical control, the environment monitoring system is in communication connection with the data collection module, the alarm module is in communication connection with the image splicing module, and the alarm module is in communication connection with the data collection module.
The above technical solution further comprises:
the data collection module acquires data in an external meteorological station through a network, the data collection module arranges the data according to timeliness, only the latest timeliness data is reserved, the data collection module acquires geographic conditions around the hot melt lake, the data collection module is in communication connection with the environment monitoring system, and the data collection module is in communication connection with the flight control system.
The data collection module transmits the acquired data to the flight control system, the route planning system judges whether unmanned aerial vehicle monitoring is carried out according to external weather conditions, and the deep learning module carries out deep learning according to geographical conditions around the hot melt lake pond acquired in the data collection module, so that a flight monitoring path for monitoring the unmanned aerial vehicle is formulated.
The hovering monitoring module enables the monitoring unmanned aerial vehicle to be in a hovering state when the monitoring unmanned aerial vehicle shoots water flow, images outside the thermal fusion lake pond are shot through the CMOS camera, and specific geographic information outside the thermal fusion lake pond is collected through the laser radar system.
The flight control system is in communication connection with the image system, the flight control system transmits monitored data to the image system, the image acquisition module acquires the transmitted data, the image acquisition module transmits the acquired data to the image processing module, and the image processing module performs primary processing on the image, so that noise in the image is reduced, and meanwhile, the brightness of the image is enhanced.
The image processing module is in communication connection with the image recognition module, the image recognition module recognizes the processed image, so that textures in the image are extracted, and then the textures are combined and recognized, wherein the contents recognized by the image recognition module comprise the positions of vegetation around the hot melt lake and lake water.
The image correction module is in communication connection with the image correction module, the image correction module is used for further correcting the data recognized in the image recognition module and correcting the distortion position in the image data so as to realize the correction of the recognized image data, the image correction module is in communication connection with the image splicing module, and the image splicing module is used for splicing images according to the image correction module and the data collected by the laser radar so as to realize the drawing of the images around the hot melt lake.
The image system is in communication connection with the environment monitoring system, the environment monitoring system obtains vegetation coverage rate around the hot-melt lake through the vegetation coverage module according to image data in the image system, meanwhile, the water flow monitoring module obtains hydrological conditions around the hot-melt lake through data monitored by the hovering monitoring module, and the alarm module realizes real-time monitoring on erosion conditions of the hot-melt lake according to external data and data in the environment monitoring system.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, when the unmanned aerial vehicle monitoring system is used, whether unmanned aerial vehicle monitoring is carried out is judged according to external weather conditions through the route planning system, and deep learning is carried out through the deep learning module according to the geographical conditions around the hot-melt lake, which are obtained from the data collection module, so that a flight monitoring path of the monitoring unmanned aerial vehicle is formulated, images outside the hot-melt lake are shot through the CMOS camera in the process of flying of the monitoring unmanned aerial vehicle, and specific geographical information outside the hot-melt lake is collected through the laser radar system, so that the collection of data around the hot-melt lake is greatly improved.
2. According to the invention, the collected images are processed, identified, spliced and corrected through the cooperation of an image collecting module, an image processing module, an image identifying module, an image correcting module and an image splicing module in an image system, so that image splicing is carried out according to data collected by a laser radar, the drawing of images around the hot-melt lake is realized, the vegetation coverage rate around the hot-melt lake is obtained through a vegetation coverage module, the speed of water flow around the hot-melt lake is obtained through data monitored by a hovering monitoring module, and finally, the real-time monitoring of the erosion condition of the hot-melt lake is realized through an alarm module according to data obtained from the outside and data in an environment monitoring system.
Drawings
Fig. 1 is a system block diagram of an unmanned aerial vehicle hot-melt lake pond hydrological monitoring system provided by the invention;
FIG. 2 is a system block diagram of an environmental monitoring system of the present invention;
FIG. 3 is a system block diagram of the flight control system of the present invention;
fig. 4 is a system block diagram of an image system in the present invention.
In the figure: 1. a hydrologic monitoring host; 2. an environmental monitoring system; 3. a flight control system; 4. an image system; 5. a data collection module; 6. an alarm module; 7. an image stitching module; 8. a water flow monitoring module; 9. a temperature monitoring module; 10. a vegetation cover module; 11. a deep learning module; 12. a route planning system; 13. a hover monitoring module; 14. a CMOS camera; 15. a laser radar system; 16. an image acquisition module; 17. an image processing module; 18. an image recognition module; 19. and an image rectification module.
Detailed Description
The technical solution of the present invention is further explained with reference to the accompanying drawings and specific embodiments.
Example one
As shown in fig. 1-4, the unmanned aerial vehicle thermal melting lake pond hydrology monitoring system provided by the invention comprises a monitoring unmanned aerial vehicle, a hydrology monitoring host 1 is arranged inside the monitoring unmanned aerial vehicle, the hydrology monitoring host 1 comprises an environment monitoring system 2, a flight control system 3, an image system 4, a data collection module 5 and an alarm module 6, the environment monitoring system 2 comprises a water flow monitoring module 8, a temperature monitoring module 9 and a vegetation cover module 10, and the water flow, the temperature and vegetation cover around the thermal melting lake pond are monitored by the environment monitoring system 2;
the flight control system 3 comprises a deep learning module 11, a route planning system 12, a hovering monitoring module 13, a CMOS camera 14 and a laser radar system 15, the flight control system 3 regulates and controls the flight path and the monitoring position of the monitoring unmanned aerial vehicle, the image system 4 comprises an image acquisition module 16, an image processing module 17, an image recognition module 18, an image correction module 19 and an image splicing module 7, the image system 4 acquires external images, simultaneously performs primary processing and recognition on the acquired images, and then corrects and splices the recognized images;
the data collection module 5 collects external numerical control, the environment monitoring system 2 is in communication connection with the data collection module 5, the alarm module 6 is in communication connection with the image splicing module 7, and the alarm module 6 is in communication connection with the data collection module 5;
the data collection module 5 acquires data in an external weather station through a network, the data collection module 5 arranges the data according to timeliness, only the latest timeliness data is reserved, the data collection module 5 acquires the geographical conditions around the hot melt lake pond, the data collection module 5 is in communication connection with the environment monitoring system 2, and the data collection module 5 is in communication connection with the flight control system 3;
the data collection module 5 transmits the acquired data to the flight control system 3, the route planning system 12 judges whether to monitor the unmanned aerial vehicle according to the external weather conditions, and the deep learning module 11 performs deep learning according to the geographical conditions around the hot melt lake pond acquired in the data collection module 5, so that a flight monitoring path for monitoring the unmanned aerial vehicle is formulated;
the hovering monitoring module 13 enables the monitoring unmanned aerial vehicle to be in a hovering state when shooting water flow, images outside the hot-melt lake are shot through the CMOS camera 14, and specific geographic information outside the hot-melt lake is collected through the laser radar system 15.
The working principle of the unmanned aerial vehicle hot-melt lake water-hydrological monitoring system based on the first embodiment is that when the unmanned aerial vehicle hot-melt lake water-hydrological monitoring system works, the data collection module 5 firstly obtains data in an external meteorological station through a network, the data collection module 5 arranges the data according to timeliness, only latest timeliness data are reserved, and meanwhile, the data collection module 5 collects the geographical environment around the hot-melt lake to be monitored in the process of obtaining the data through the network;
the route planning system 12 judges whether to monitor the unmanned aerial vehicle according to external weather conditions, and when the route planning system 12 judges that the external environment is suitable for the unmanned aerial vehicle to execute tasks, the deep learning module 11 performs deep learning according to the geographical conditions around the hot melt lake acquired by the data collection module 5, so that a flight monitoring path for monitoring the unmanned aerial vehicle is formulated;
in the process of monitoring the unmanned aerial vehicle to execute the task, the hovering monitoring module 13 enables the monitoring unmanned aerial vehicle to be in a hovering state when shooting water flow, so that the accuracy rate of detection on the water flow speed is ensured;
the CMOS camera 14 shoots images outside the thermal fusion lake, and then collects specific geographic information outside the thermal fusion lake through the laser radar system 15.
Example two
As shown in fig. 1 to 4, based on the first embodiment, the flight control system 3 is in communication connection with the image system 4, the flight control system 3 transmits monitored data to the image system 4, the image acquisition module 16 acquires the transmitted data, the image acquisition module 16 transmits the acquired data to the image processing module 17, and the image processing module 17 performs preliminary processing on the image, so as to reduce noise in the image and enhance the brightness of the image;
the image processing module 17 is in communication connection with the image recognition module 18, the image recognition module 18 recognizes the processed image, so that textures in the image are extracted, the textures are combined and recognized, and the contents recognized by the image recognition module 18 comprise the positions of vegetation around the hot melt lake and lake water;
the image identification module 18 is in communication connection with the image correction module 19, the image correction module 19 further corrects data identified in the image identification module 18 and corrects the distortion position in the image data, so that the identified image data is corrected, the image correction module 19 is in communication connection with the image splicing module 7, and the image splicing module 7 performs image splicing according to the image correction module 19 and data collected by a laser radar, so that images around the hot melt lake are drawn.
In this embodiment, the image acquisition module 16 acquires the transmitted image data, and the image processing module 17 performs preliminary processing on the image, so as to reduce noise in the image and enhance the brightness of the image, thereby increasing the accuracy and efficiency of subsequent identification heat;
the image recognition module 18 recognizes the processed image, so that textures in the image are extracted, the textures are combined and recognized, the content recognized by the image recognition module 18 comprises positions of vegetation around the hot melt pond and lake water, the image correction module 19 further corrects the data recognized by the image recognition module 18, and the position where distortion occurs in the image data is corrected, so that the correction of the recognized image data is realized;
and the image splicing module 7 performs image splicing according to the image correction module 19 and the data acquired by the laser radar, so that the drawing of the images around the hot-melt lake pond is realized.
EXAMPLE III
As shown in fig. 1 to 4, based on the first or second embodiment, the image system 4 is in communication connection with the environment monitoring system 2, the environment monitoring system 2 obtains the vegetation coverage rate around the hot-melt lake through the vegetation coverage module 10 according to the image data in the image system 4, the water flow monitoring module 8 obtains the speed of the water flow around the hot-melt lake through the data monitored by the hovering monitoring module 13, and the alarm module 6 realizes real-time monitoring of the erosion situation of the hot-melt lake according to the external data and the data in the environment monitoring system 2.
In the embodiment, in operation, the image system 4 draws according to the image data in the environment monitoring system 2 and the images around the hot-melt lake, so that the vegetation coverage rate around the hot-melt lake is obtained through the vegetation coverage module 10, at this time, the data of erosion of the external hot-melt lake is imported into the deep learning module 11, the erosion model of the hot-melt lake is established through the deep learning module 11, then the data obtained by the unmanned aerial vehicle which is monitored at this time is imported into the erosion model of the hot-melt lake, so that whether the erosion phenomenon occurs in the detected hot-melt lake is judged, when the erosion phenomenon occurs, an alarm is given out through the alarm module 6, and the hot-melt lake is conveniently managed in time.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered as the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (8)
1. The hydrological monitoring system for the unmanned aerial vehicle thermal melting lake pond comprises a monitoring unmanned aerial vehicle, wherein a hydrological monitoring host (1) is arranged inside the monitoring unmanned aerial vehicle, and is characterized in that the hydrological monitoring host (1) comprises an environment monitoring system (2), a flight control system (3), an image system (4), a data collection module (5) and an alarm module (6), the environment monitoring system (2) comprises a water flow monitoring module (8), a temperature monitoring module (9) and a vegetation covering module (10), and the water flow, the temperature and vegetation covering around the thermal melting lake pond are monitored by the environment monitoring system (2);
the flight control system (3) comprises a deep learning module (11), a route planning system (12), a hovering monitoring module (13), a CMOS camera (14) and a laser radar system (15), the flight control system (3) regulates and controls a flight path and a monitoring position of a monitoring unmanned aerial vehicle, the image system (4) comprises an image acquisition module (16), an image processing module (17), an image recognition module (18), an image correction module (19) and an image splicing module (7), the image system (4) acquires external images, simultaneously performs primary processing and recognition on the acquired images, and then corrects and splices the recognized images;
the data collection module (5) collects external numerical control, the environment monitoring system (2) is in communication connection with the data collection module (5), the alarm module (6) is in communication connection with the image splicing module (7), and the alarm module (6) is in communication connection with the data collection module (5).
2. The unmanned aerial vehicle hot melt lake hydrological monitoring system according to claim 1, wherein the data collection module (5) acquires data in an external meteorological station through a network, the data collection module (5) arranges the data according to timeliness and only retains the latest timeliness data, the data collection module (5) acquires geographical conditions around the hot melt lake, the data collection module (5) is in communication connection with the environment monitoring system (2), and the data collection module (5) is in communication connection with the flight control system (3).
3. The unmanned aerial vehicle hot melt lake pond hydrological monitoring system according to claim 2, wherein the data collection module (5) transmits the acquired data to the flight control system (3), the route planning system (12) judges whether unmanned aerial vehicle monitoring is performed according to external weather conditions, and the deep learning module (11) performs deep learning according to geographical conditions around the hot melt lake pond acquired in the data collection module (5), so that a flight monitoring path for monitoring the unmanned aerial vehicle is established.
4. The unmanned aerial vehicle molten lake pond hydrology monitoring system of claim 3, wherein the hovering monitoring module (13) enables the monitoring unmanned aerial vehicle to be in a hovering state when shooting hydrology conditions, real-time image data of the molten lake pond and the periphery is collected through the CMOS camera (14), and specific geographic information outside the molten lake pond is collected through the laser radar system (15).
5. The unmanned aerial vehicle hot melt lake pond hydrology monitoring system of claim 4, wherein the flight control system (3) is in communication connection with the image system (4), the flight control system (3) transmits monitored data to the image system (4), the image acquisition module (16) acquires the transmitted data, the image acquisition module (16) transmits the acquired data to the image processing module (17), and the image processing module (17) performs preliminary processing on the image, so that noise in the image is reduced, and meanwhile, the brightness of the image is enhanced.
6. The unmanned aerial vehicle hot melt pond hydrological monitoring system according to claim 5, wherein the image processing module (17) is in communication connection with the image recognition module (18), the image recognition module (18) recognizes the processed image, so that textures in the image are extracted, and then the textures are subjected to combined recognition, and the content recognized by the image recognition module (18) comprises positions of vegetation and lake water around the hot melt pond.
7. The unmanned aerial vehicle hot melt lake pond hydrological monitoring system according to claim 6, wherein the image recognition module (18) is in communication connection with the image correction module (19), the image correction module (19) further corrects data recognized in the image recognition module (18), corrects a distortion position appearing in image data, and accordingly corrects the recognized image data, the image correction module (19) is in communication connection with the image splicing module (7), and the image splicing module (7) performs image splicing according to the image correction module (19) and data collected by a laser radar, and accordingly draws images around the hot melt lake pond.
8. The unmanned aerial vehicle hot melt pond hydrology monitoring system according to claim 7, wherein the image system (4) is in communication connection with the environment monitoring system (2), and the environment monitoring system (2) obtains vegetation coverage rate around the hot melt pond through the vegetation coverage module (10) according to image data in the image system (4), monitors seasonal change characteristics of the area of the hot melt pond in real time, and further estimates seasonal changes of the hydrology and water quantity of the pond; meanwhile, the water flow monitoring module (8) obtains the speed of water flow around the hot melt lake through data monitored by the hovering monitoring module (13), and the alarm module (6) realizes real-time monitoring of the erosion condition of the hot melt lake according to external data and data in the environment monitoring system (2).
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