CN116310266A - Lake wetland remote sensing identification device and method based on unmanned aerial vehicle hyperspectral - Google Patents
Lake wetland remote sensing identification device and method based on unmanned aerial vehicle hyperspectral Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000001228 spectrum Methods 0.000 claims abstract description 72
- 238000000605 extraction Methods 0.000 claims abstract description 7
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 claims description 23
- 229910052782 aluminium Inorganic materials 0.000 claims description 23
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 15
- 230000017525 heat dissipation Effects 0.000 claims description 13
- 238000012876 topography Methods 0.000 claims description 13
- 239000000463 material Substances 0.000 claims description 9
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 8
- 229910021389 graphene Inorganic materials 0.000 claims description 8
- 238000009434 installation Methods 0.000 claims description 8
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- 238000005457 optimization Methods 0.000 description 4
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- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
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- 238000006731 degradation reaction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
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- G—PHYSICS
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- 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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
- G06V10/12—Details of acquisition arrangements; Constructional details thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/17—Terrestrial scenes taken from planes or by drones
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- 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 belongs to the technical field of wetland recognition, and particularly relates to a lake wetland remote sensing recognition device and method based on unmanned aerial vehicle-mounted hyperspectrum, wherein the device comprises an unmanned aerial vehicle body, an observation module and a connecting piece thereof, and the observation module comprises an observation box, and a laser radar and a spectrum sensor which are positioned on the front surface of the observation box; the connecting piece is a right-angle plate and comprises a first mounting ear and a second mounting ear, and the observation module is mounted at the bottom of the unmanned aerial vehicle body through the first mounting ear or the second mounting ear; judging the landform of the area to be identified, and starting a laser radar and a spectrum sensor to acquire radar data and spectrum data of the area to be identified; preferentially identifying the radar data through an information identification module; according to the invention, the wetland characteristics are extracted by fusing the spectral image of the unmanned aerial vehicle platform and the radar data, so that the extraction precision can be improved, the cost can be further reduced, the radar data is an active emission light source, the weather interference is avoided, and the provided data precision is higher.
Description
Technical Field
The invention belongs to the technical field of wetland recognition, and particularly relates to a lake wetland remote sensing recognition device and method based on unmanned aerial vehicle-mounted hyperspectral.
Background
The sensor carried on the satellite is utilized to take the periodic photos of the earth, so that the distribution of the wetland in different periods can be more accurately and objectively known; by using the remote sensing images in different periods, the wetland map in different periods can be manufactured, so that the change condition of the wetland is further known, the degradation area of the wetland is determined, and the current situation of the damaged wetland ecosystem is reflected. Traditional census or statistical data often have the disadvantages of large error, limitation by administrative division, non-uniform data and the like; the remote sensing technology is utilized to conduct the investigation of the wetland resources, and the method has the advantages of objectivity, accuracy, economy, high efficiency and the like.
The existing remote sensing recognition wetland adopts main satellite remote sensing, the image data source is an optical image, the optical image is early in development, the provided data source is long in time, but is easily influenced by weather such as cloud, rain and the like, so that the recognition accuracy is low; because the spectrum characteristics of the wetland on the remote sensing image have obvious differences and a plurality of similarities with those of other lands, the satellite remote sensing method is used for carrying out monitoring and identification on the wetland and has challenges.
Disclosure of Invention
The invention aims to provide a lake wetland remote sensing identification device and method based on unmanned aerial vehicle-mounted hyperspectrum, so as to solve the problems in the background technology.
The invention realizes the above purpose through the following technical scheme:
the lake wetland remote sensing recognition device based on unmanned aerial vehicle-mounted hyperspectrum comprises an unmanned aerial vehicle body, an observation module and a connecting piece thereof, wherein the observation module comprises an observation box, and a laser radar and a spectrum sensor which are positioned on the front surface of the observation box; the connecting piece is a right-angle plate, one plate surface end is provided with a first mounting lug, the other plate surface end is provided with a second mounting lug, and the observation module is mounted at the bottom of the unmanned aerial vehicle body through the first mounting lug or the second mounting lug; the observation module comprises an aluminum frame which is arranged at the bottom of the observation module and is used for installing the laser radar and the spectrum sensor, and the top of the aluminum frame is fixedly connected with the connecting piece;
the identification device also comprises an information identification module and an output module; the information identification module is used for carrying out priority identification on the radar data acquired by the laser radar, if the radar data meets the preset identification condition, then carrying out identification on the spectrum information acquired by the spectrum sensor, and transmitting the identification result to the output module for display after the identification is completed.
As a further optimization scheme of the invention, the inner side of the aluminum frame is fixedly connected with a heat dissipation fin plate, and the laser radar and the spectrum sensor are fixedly arranged on the heat dissipation fin plate.
As a further optimization scheme of the invention, the heat dissipation fin plate is specifically an aluminum plate and heat dissipation fins arranged on the back surface of the aluminum plate, and the laser radar and the spectrum sensor are arranged on the aluminum plate.
As a further optimization scheme of the invention, the connecting piece is made of graphene materials.
As a further optimization scheme of the present invention, the information identification module includes:
extraction unit: the method comprises the steps of comparing radar data of an area to be identified with preset identification conditions preferentially to execute further identification of the spectrum information or terminate identification;
the identification condition is that the water depth of the area to be identified is not more than 6 meters.
GIS unit: and the system is used for executing the identification of the spectrum information so as to extract the spectrum characteristics of the wetland in the spectrum information, comparing the spectrum characteristics of the wetland with the typical spectrum characteristics of the wetland in a database, and transmitting the comparison result to the output module.
A method for remote sensing by using the lake wetland remote sensing recognition device based on unmanned aerial vehicle carried hyperspectral according to any one of the above steps, comprising the following steps:
s1: judging the topography of the area to be identified, if the area to be identified is valley topography or gully topography, installing the observation module below the unmanned aerial vehicle body through the second installation lugs, otherwise, installing the observation module below the unmanned aerial vehicle body through the first installation lugs;
s2: starting the unmanned aerial vehicle body to fly above the area to be identified, and simultaneously starting the laser radar and the spectrum sensor to acquire radar data and spectrum data of the area to be identified;
s3: the radar data are preferentially identified through the information identification module, and if the water depth of the area to be identified in the radar data is higher than 6 meters, the identification process is stopped; otherwise, the spectrum information is further identified, and the identification result is transmitted to the output module for display after the identification is completed.
The invention has the beneficial effects that:
(1) According to the invention, the wetland characteristics are extracted by fusing the spectral image of the unmanned aerial vehicle platform and the radar data, so that the extraction precision can be improved, the cost can be further reduced, the radar data is an active emission light source and is not interfered by weather, and the provided data precision is higher;
(2) According to the invention, the connecting piece of the unmanned aerial vehicle body and the observation module is made of the graphene material, the overall weight of the connecting piece is reduced by the graphene material, the flying duration of the unmanned aerial vehicle is improved, in addition, the connecting piece is directly connected with the aluminum frame, and the connecting structure of the unmanned aerial vehicle and the unmanned aerial vehicle can be directly used as the observation module by utilizing the excellent thermal conductivity and the excellent rigidity of the graphene material, so that the heat dissipation effect is further improved, and two purposes are achieved;
(3) According to the method, the acquired radar data are preferentially identified through the arrangement of the information identification module, and because the identification process of the spectrum information is complex, the area to be detected in the radar data can be rapidly pre-classified by intuitively comparing the water depth of the area to be detected with the standard water depth range of the wetland, and if the water depth condition of the wetland is not met, the identification process is stopped, so that the complex identification process of the spectrum information is omitted, and the wetland identification efficiency is improved.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a schematic view of the structure of the observation module and the connector according to the present invention;
FIG. 3 is a schematic view of the structure of the connector of the present invention;
FIG. 4 is a front cross-sectional view of a viewing module and connector of the present invention;
FIG. 5 is a schematic diagram showing the connection of the observation module to the unmanned aerial vehicle body when the laser radar and the spectrum sensor are vertically downward;
fig. 6 is a flow chart of the monitoring method of the present invention.
In the figure: 1. an unmanned aerial vehicle body; 2. an observation module; 3. a connecting piece; 21. a laser radar; 22. a spectral sensor; 23. a heat radiation hole; 24. an aluminum frame; 25. a heat dissipation fin; 26. a storage passage; 27. an electric telescopic member; 31. a first mounting ear; 32. and a second mounting ear.
Detailed Description
The invention will now be described in further detail with reference to the accompanying drawings, wherein it is to be understood that the following detailed description is for the purpose of illustration only and is not to be construed as limiting the scope of the invention, as various insubstantial modifications and adaptations of the invention to those skilled in the art may be made in light of the foregoing disclosure.
Example 1
As shown in fig. 1-6, the lake wetland remote sensing recognition device based on unmanned aerial vehicle-mounted hyperspectrum comprises an unmanned aerial vehicle body 1, an observation module 2 and a connecting piece 3 thereof, wherein the observation module 2 comprises an observation box, a laser radar 21 and a spectrum sensor 22 which are positioned on the front surface of the observation box, and a heat radiation hole 23 is formed in the side surface of the observation box; the laser radar 21 is used for acquiring water depth data of the area to be identified, and the spectrum sensor 22 is used for acquiring spectrum information of the geomorphic characteristics of the area to be identified; the connecting piece 3 is a right-angle plate, referring to fig. 3, one plate surface end is provided with a first mounting lug 31, the other plate surface end is provided with a second mounting lug 32, and the observation module 2 is mounted at the bottom of the unmanned aerial vehicle body 1 through the first mounting lug 31 or the second mounting lug 32; if the area to be identified is a valley topography or a gully topography, the observation module 2 is installed below the unmanned aerial vehicle body 1 through the second installation lug 32, referring to fig. 1, so that radar data and spectrum information under the topography are conveniently collected, and if the laser radar 21 and the spectrum sensor 22 are adopted under the topography to vertically and downwards obtain, the unmanned aerial vehicle body 1 has the risk of impacting an obstacle; if other features are obtained, the observation module 2 is installed below the unmanned aerial vehicle body 1 through the first installation ear 31, and referring to fig. 5, the laser radar 21 and the spectrum sensor 22 acquire radar data and spectrum information vertically downwards.
Because the land feature of the wetland comprises valley land feature or gully land feature, under the land feature, because of the large land fall, if the laser radar 21 and the spectrum sensor 22 at the lower end of the unmanned aerial vehicle body 1 are used for vertically and downwards acquiring information, the unmanned aerial vehicle body 1 is at risk of collision, and the right-angle structure of the connecting piece 3 is limited based on the defects, so that the observation module 2 can be installed in different positions.
It should be noted that, in the prior art, the limiting of the wetland comprises that the falling water depth of the region to be identified is not higher than 6 meters, and the identification device is further optimized based on the limiting, so that the identification steps are reduced, and the extraction efficiency is improved; and preferentially acquiring water depth data of the area to be identified through the laser radar.
The observation module 2 comprises an aluminum frame 24 which is arranged at the inner bottom of the observation module and is used for installing the laser radar 21 and the spectrum sensor 22, and the top of the aluminum frame 24 is fixedly connected with the connecting piece 3; in the invention, a heat dissipation fin plate 25 is fixedly connected to the inner side of an aluminum frame 24, a laser radar 21 and a spectrum sensor 22 are fixedly arranged on the heat dissipation fin plate 25, the heat dissipation fin plate 25 is specifically an aluminum plate and heat dissipation fins arranged on the back surface of the aluminum plate, and the laser radar 21 and the spectrum sensor 22 are arranged on the aluminum plate.
According to the invention, the fixing parts of the laser radar 21 and the spectrum sensor 22 are made of aluminum materials, so that the light weight is realized, and the heat conducting performance of the laser radar 21 and the spectrum sensor 22 can be improved.
In the invention, the connecting piece 3 is made of graphene materials, the overall weight of the connecting piece 3 is reduced by the graphene materials, the flying duration of the unmanned aerial vehicle is improved, in addition, the connecting piece 3 is directly connected with the aluminum frame 24 in the invention, and the connecting structure with the unmanned aerial vehicle of the observation module 2 can be directly used by utilizing the excellent thermal conductivity and the excellent rigidity of the graphene materials, so that the heat dissipation effect is further improved, and two purposes are achieved.
The identification device also comprises an information identification module 4 and an output module 5; the information recognition module 4 is configured to preferentially recognize the radar data acquired by the laser radar 21, and recognize the spectrum information acquired by the spectrum sensor 22 if the radar data meets a preset recognition condition, and transmit the recognition result to the output module 2 for display after the recognition is completed.
Further, the information identifying module 4 includes:
extraction unit 41: the method comprises the steps of comparing radar data of an area to be identified with preset identification conditions preferentially to execute further identification of spectrum information or terminate identification;
wherein the identification condition is that the water depth of the area to be identified is not more than 6 meters.
GIS unit 42: the method is used for executing identification of the spectrum information to extract the spectrum characteristics of the wetland in the spectrum information, comparing the spectrum characteristics of the wetland with typical spectrum characteristics of the wetland in a database, and transmitting the comparison result to the output module 2.
Referring to fig. 2 and 4, a storage channel 26 for storing the laser radar 21 and the spectrum sensor 2 is arranged on the front surface of an observation box in the observation module 2, and electric telescopic pieces 27 are arranged on the mounting surfaces of the laser radar 21, the spectrum sensor 22 and the aluminum plate, wherein the electric telescopic pieces 27 can be cylinders, electric push rods and the like; the information identification module 4 is also used for controlling the storage of the laser radar 21 and the spectrum sensor 22, and specifically, the electric telescopic piece 27 is controlled to drive the laser radar 21 and the spectrum sensor 22 to be stored in the storage channel 26 or extend out of the observation box for data acquisition. The functional design is based on the fact that under sudden weather conditions such as rain, snow, sand and dust appear in an area to be observed, operators of the ground unmanned aerial vehicle body 1 cannot timely respond, and the information identification module 4 is provided with an active control laser radar 21 and a spectrum sensor 22 to be stored, so that the laser radar 21 and the spectrum sensor 22 are prevented from being damaged in severe weather.
In addition, in order to realize the control function of the information identification module 4 on the electric telescopic member 27 in the severe weather, a rain and snow sensor, a dust sensor and a micro control unit are arranged in the information identification module 4, the output ends of the rain and snow sensor and the dust sensor are electrically connected with the input end of the micro control unit, and the output end of the micro control unit is electrically connected with the control end of the electric telescopic member 27.
A lake wetland remote sensing identification device identification method based on unmanned aerial vehicle-mounted hyperspectrum comprises the following steps:
s1: judging the topography of the area to be identified, if the area to be identified is valley topography or gully topography, installing the observation module 2 below the unmanned aerial vehicle body 1 through the second installation lugs 32, otherwise installing the observation module 2 below the unmanned aerial vehicle body 1 through the first installation lugs 31;
s2: the unmanned aerial vehicle body 1 is started to fly above the area to be identified, and meanwhile, the laser radar 21 and the spectrum sensor 22 are started to acquire radar data and spectrum data of the area to be identified;
s3: the radar data are preferentially identified through the information identification module 4, and if the water depth of the area to be identified in the radar data is higher than 6 meters, the identification process is stopped; otherwise, the spectrum information is further identified, and the identification result is transmitted to the output module 2 for display after the identification is completed.
According to the method, the acquired radar data are preferentially identified through the arrangement of the information identification module 4, and because the identification process of the spectrum information is complex, the area to be detected in the radar data can be rapidly pre-classified by intuitively comparing the water depth of the area to be detected with the standard water depth range of the wetland, and if the water depth condition of the wetland is not met, the identification process is stopped, the complex identification process of the spectrum information is omitted, and the wetland identification efficiency is improved.
In addition, compared with the prior art that the remote sensing image of the region to be detected is obtained by adopting satellite remote sensing influence, the image is easily influenced by weather such as cloud, rain and the like, so that the recognition precision is low; the method has the advantages that the spectrum features of the wetland on the remote sensing image are obviously different from those of other lands, and the recognition difficulty is greatly increased due to the fact that the spectrum features of the wetland on the remote sensing image are similar to those of other lands, and the method can improve the extraction precision and further reduce the cost by fusing the spectrum images of the unmanned aerial vehicle platform with radar data to extract the features of the wetland.
The above examples merely represent a few embodiments of the present invention, which are described in more detail and are not to be construed as limiting the scope of the present invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention.
Claims (6)
1. Lake wetland remote sensing recognition device based on unmanned aerial vehicle carries hyperspectrum, its characterized in that: the unmanned aerial vehicle comprises an unmanned aerial vehicle body (1), an observation module (2) and a connecting piece (3) thereof, wherein the observation module (2) comprises an observation box, and a laser radar (21) and a spectrum sensor (22) which are positioned on the front surface of the observation box; the connecting piece (3) is a right-angle plate, one plate surface end is provided with a first mounting lug (31), the other plate surface end is provided with a second mounting lug (32), and the observation module (2) is mounted at the bottom of the unmanned aerial vehicle body (1) through the first mounting lug (31) or the second mounting lug (32); the observation module (2) comprises an aluminum frame (24) which is arranged at the inner bottom of the observation module and is used for installing the laser radar (21) and the spectrum sensor (22), and the top of the aluminum frame (24) is fixedly connected with the connecting piece (3);
the identification device also comprises an information identification module (4) and an output module (5); the information identification module (4) is used for carrying out priority identification on the radar data acquired by the laser radar (21), if the radar data meets the preset identification condition, then carrying out identification on the spectrum information acquired by the spectrum sensor (22), and transmitting the identification result to the output module (2) for display after the identification is completed.
2. The lake wetland remote sensing identification device based on unmanned aerial vehicle hyperspectrum according to claim 1, wherein: the inner side of the aluminum frame (24) is fixedly connected with a heat dissipation fin plate (25), and the laser radar (21) and the spectrum sensor (22) are fixedly arranged on the heat dissipation fin plate (25).
3. The lake wetland remote sensing identification device based on unmanned aerial vehicle hyperspectrum according to claim 2, wherein: the radiating fin plate (25) is specifically an aluminum plate and radiating fins arranged on the back surface of the aluminum plate, and the laser radar (21) and the spectrum sensor (22) are arranged on the aluminum plate.
4. The lake wetland remote sensing identification device based on unmanned aerial vehicle hyperspectrum according to claim 1, wherein: the connecting piece (3) is made of graphene materials.
5. The lake wetland remote sensing identification device based on unmanned aerial vehicle hyperspectrum according to claim 1, wherein: the information identification module (4) comprises:
extraction unit (41): the method comprises the steps of comparing radar data of an area to be identified with preset identification conditions preferentially to execute further identification of the spectrum information or terminate identification;
the identification condition is that the water depth of the area to be identified is not more than 6 meters.
GIS unit (42): and the system is used for executing the identification of the spectrum information so as to extract the spectrum characteristics of the wetland in the spectrum information, comparing the spectrum characteristics of the wetland with the typical spectrum characteristics of the wetland in a database, and transmitting the comparison result to the output module (2).
6. A method for remote sensing identification of lake wetland remote sensing identification device based on unmanned aerial vehicle carried hyperspectral according to any one of claims 1 to 5, wherein: the method comprises the following steps:
s1: judging the topography of the area to be identified, if the area to be identified is valley topography or gully topography, installing the observation module (2) below the unmanned aerial vehicle body (1) through the second installation lugs (32), otherwise installing the observation module (2) below the unmanned aerial vehicle body (1) through the first installation lugs (31);
s2: starting the unmanned aerial vehicle body (1) to fly above the area to be identified, and simultaneously starting the laser radar (21) and the spectrum sensor (22) to acquire radar data and spectrum data of the area to be identified;
s3: the radar data are preferentially identified through the information identification module (4), and if the water depth of the area to be identified in the radar data is higher than 6 meters, the identification process is stopped; otherwise, the spectrum information is further identified, and the identification result is transmitted to the output module (2) for display after the identification is completed.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110673159A (en) * | 2019-09-30 | 2020-01-10 | 中国海洋大学 | Unmanned aerial vehicle active radar hyperspectral detection system and method for marine environment monitoring |
| CN112416020A (en) * | 2020-12-10 | 2021-02-26 | 金祺创（北京）技术有限公司 | Multispectral unmanned aerial vehicle acquisition control system |
| CN212861863U (en) * | 2020-07-27 | 2021-04-02 | 中南安全环境技术研究院股份有限公司 | Plant community statistics monitoring system based on unmanned aerial vehicle |
| CN215180895U (en) * | 2021-04-20 | 2021-12-14 | 深圳市源清环境技术服务有限公司 | Soil erosion evaluation data acquisition device |
| CN114155450A (en) * | 2021-12-09 | 2022-03-08 | 中科计算技术西部研究院 | Hyperspectrum-based tree species identification method and system and storage medium |
| WO2022092438A1 (en) * | 2020-10-30 | 2022-05-05 | 한국건설기술연구원 | System for managing river using drone and method therefor |
| WO2022092437A1 (en) * | 2020-10-30 | 2022-05-05 | 한국건설기술연구원 | System and method for recognizing river facilities using drone |
| KR20220106492A (en) * | 2021-01-22 | 2022-07-29 | 주식회사 공간정보 | drone operating system of river specialization |
| CN115797807A (en) * | 2022-11-28 | 2023-03-14 | 南方科技大学 | Ocean garbage monitoring method, system and medium based on data of unmanned aerial vehicle-mounted spectrometer |
-
2023
- 2023-03-20 CN CN202310272612.5A patent/CN116310266B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110673159A (en) * | 2019-09-30 | 2020-01-10 | 中国海洋大学 | Unmanned aerial vehicle active radar hyperspectral detection system and method for marine environment monitoring |
| CN212861863U (en) * | 2020-07-27 | 2021-04-02 | 中南安全环境技术研究院股份有限公司 | Plant community statistics monitoring system based on unmanned aerial vehicle |
| WO2022092438A1 (en) * | 2020-10-30 | 2022-05-05 | 한국건설기술연구원 | System for managing river using drone and method therefor |
| WO2022092437A1 (en) * | 2020-10-30 | 2022-05-05 | 한국건설기술연구원 | System and method for recognizing river facilities using drone |
| CN112416020A (en) * | 2020-12-10 | 2021-02-26 | 金祺创（北京）技术有限公司 | Multispectral unmanned aerial vehicle acquisition control system |
| KR20220106492A (en) * | 2021-01-22 | 2022-07-29 | 주식회사 공간정보 | drone operating system of river specialization |
| CN215180895U (en) * | 2021-04-20 | 2021-12-14 | 深圳市源清环境技术服务有限公司 | Soil erosion evaluation data acquisition device |
| CN114155450A (en) * | 2021-12-09 | 2022-03-08 | 中科计算技术西部研究院 | Hyperspectrum-based tree species identification method and system and storage medium |
| CN115797807A (en) * | 2022-11-28 | 2023-03-14 | 南方科技大学 | Ocean garbage monitoring method, system and medium based on data of unmanned aerial vehicle-mounted spectrometer |
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