CN113340275A - Method for positioning remote sensing mapping image of natural resource - Google Patents
Method for positioning remote sensing mapping image of natural resource Download PDFInfo
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- CN113340275A CN113340275A CN202110615469.6A CN202110615469A CN113340275A CN 113340275 A CN113340275 A CN 113340275A CN 202110615469 A CN202110615469 A CN 202110615469A CN 113340275 A CN113340275 A CN 113340275A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
- G01C11/04—Interpretation of pictures
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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 natural resource remote sensing mapping image positioning method, which belongs to the technical field of remote sensing mapping image positioning and comprises the following specific steps: (1) obtaining an original remote sensing image; (2) processing an original remote sensing image; (3) boundary positioning; (4) mounting an auxiliary datum point; (5) geographic coordinate positioning and area determination; the invention provides a natural resource positioning model to be detected, which is formed by marking a representative region from a natural resource region to be detected as a training region, and then performing remote sensing shooting, preprocessing, decomposition reconstruction and training learning, so that accurate boundary positioning can be performed on natural resources with obvious boundary range characteristics, such as water resources, forest resources and the like; in addition, the unmanned aerial vehicle is used for carrying out remote sensing mapping image positioning on the natural resource to be measured, and compared with ground mapping positioning, the method is time-saving, labor-saving, convenient and quick, and low in cost; thereby being beneficial to providing assistance for the unified investigation of natural resources.
Description
Technical Field
The invention relates to the technical field of remote sensing mapping image positioning, in particular to a natural resource remote sensing mapping image positioning method.
Background
Through retrieval, the Chinese patent No. CN104792321A discloses a land information acquisition system and a method based on auxiliary positioning, and the method of the invention can position the resources of China, but belongs to ground mapping, which is time-consuming, labor-consuming and high in cost, and can not position the boundary of natural resources efficiently and accurately; natural resources refer to substances which can be directly obtained by human beings in nature and are used for production and life, and can be divided into three types, namely, non-renewable resources, such as various metals, non-King-land minerals, fossil fuels and the like, can be formed only after long geological years; renewable resources, namely organisms, water, land resources and the like, can be produced or reproduced circularly in a short time; thirdly, inexhaustible resources, such as wind power, solar energy and the like, are utilized without reducing the storage capacity; for the development of the unified survey of natural resources, the family base is found out, which is the basis of the natural resource assets and is the premise of developing space planning; the spatial distribution of various natural resources is mastered, the boundaries and property rights bodies of various natural resource assets in all the homeland spaces are clearly defined, and a basis is provided for work of uniform right confirmation, supervision on homeland space development and utilization activities according to planning and the like; therefore, it becomes more important to invent a natural resource remote sensing mapping image positioning method;
most of the existing natural resource positioning methods are realized by adopting a ground mapping and positioning mode, and although the precision is higher, the method is time-consuming, labor-consuming and higher in cost, and cannot efficiently and accurately position the boundary of natural resources; therefore, a natural resource remote sensing mapping image positioning method is provided.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a method for positioning a remote sensing mapping image of natural resources.
In order to achieve the purpose, the invention adopts the following technical scheme:
a natural resource remote sensing mapping image positioning method comprises the following specific steps:
(1) obtaining an original remote sensing image: the method comprises the following steps that an unmanned aerial vehicle is controlled to fly to the upper space of a natural resource area to be measured to carry out remote sensing shooting, and a plurality of original remote sensing images are obtained;
(2) processing an original remote sensing image: preprocessing the plurality of original remote sensing images in the step (1), removing errors caused by external factors, and simultaneously fusing the original remote sensing images to obtain target remote sensing images;
(3) and (3) boundary positioning: inputting the target remote sensing image in the step (2) into a natural resource positioning model to be detected for range boundary positioning to obtain a boundary of a natural resource region to be detected;
(4) auxiliary datum point installation: installing a plurality of auxiliary reference points in the natural resource area to be detected in the step (1);
(5) geographic coordinate positioning and area determination: carrying out geographic coordinate positioning on the boundary of the natural resource area to be detected according to the auxiliary reference points in the step (4) and the unmanned aerial vehicle in the step (1), so as to obtain the boundary geographic coordinate of the natural resource area to be detected; and simultaneously, carrying out area calculation on the natural resource region to be detected, namely determining the area of the natural resource region to be detected.
Further, the resources to be detected in the step (1) are water resources, agricultural resources, forest resources, land resources and vegetation resources; the unmanned aerial vehicle comprises a system control module, a power module, a GNSS positioning module, a remote sensing shooting module and an IMU measuring unit, wherein the IMU measuring unit comprises a three-axis accelerometer and a three-axis gyroscope.
Furthermore, the control module is used for receiving instructions of ground control personnel to control other modules and units; the power module is used for supporting the flight of the unmanned aerial vehicle; the GNSS positioning module is used for acquiring the position information of the unmanned aerial vehicle; the three-axis accelerometer is used for measuring acceleration information of the unmanned aerial vehicle; the remote sensing shooting module is used for acquiring an original remote sensing image of a natural resource area to be detected; the three-axis gyroscope is used for measuring the angular velocity information of the unmanned aerial vehicle.
Further, the processing of the original remote sensing image in the step (2) comprises radiometric calibration processing, geometric correction processing, atmospheric correction processing and image fusion processing.
Further, the natural resource positioning model to be measured in the step (3) is obtained after deep learning training, and the specific forming process is as follows:
s1: firstly, drawing a representative area from a natural resource area to be detected as a training area;
s2: then, acquiring a plurality of sample original remote sensing images of the training area in the step S1 by using an unmanned aerial vehicle; preprocessing the plurality of sample original remote sensing images simultaneously to obtain a plurality of sample target remote sensing images;
s3: decomposing and reconstructing the plurality of sample target remote sensing images in the step S2 by using a depth variation self-encoder to obtain a plurality of reconstructed sample target remote sensing images;
s4: extracting pixel values of natural resources to be detected in the multiple reconstructed sample target remote sensing images in the step S3; meanwhile, manually calibrating the pixel threshold range, and taking the calibrated pixel threshold as a training set;
s5: and (4) constructing an SVM classifier, and inputting the training set in the step S4 into the SVM classifier to obtain the natural resource positioning model to be detected.
Further, the specific process of geographic coordinate positioning and area determination in step (5) is as follows:
SS 1: acquiring the position information of the unmanned aerial vehicle through a GNSS positioning module, measuring the acceleration information and the angular velocity information of the unmanned aerial vehicle by using a three-axis accelerometer and a three-axis gyroscope, and eliminating the deviation of the position information of the unmanned aerial vehicle acquired by the GNSS positioning module through fusion calculation to obtain the space three-dimensional coordinate of the unmanned aerial vehicle;
SS 2: acquiring three-dimensional coordinates of a plurality of auxiliary reference points;
SS 3: calculating the boundary of the natural resource area to be detected by taking the space three-dimensional coordinates of the unmanned aerial vehicle in the step SS1 and the three-dimensional coordinates of the auxiliary reference points in the step SS2 as reference points to obtain the boundary geographical coordinates of the natural resource area to be detected;
SS 4: and calculating the area of the natural resource area to be detected according to the boundary geographical coordinates of the natural resource area to be detected in the step SS3, namely determining the area of the natural resource area to be detected.
Compared with the prior art, the invention has the beneficial effects that:
1. the natural resource remote sensing mapping image positioning method provides a natural resource positioning model to be detected, which is formed by drawing a representative region from a natural resource region to be detected as a training region, and then performing remote sensing shooting, preprocessing, decomposition reconstruction and training learning, thereby being beneficial to realizing boundary positioning of natural resources;
2. according to the natural resource remote sensing mapping image positioning method, the unmanned aerial vehicle is used for carrying out remote sensing mapping image positioning on the natural resource to be measured, and compared with ground mapping positioning, the method is time-saving, labor-saving, convenient and quick, and low in cost;
3. the unmanned aerial vehicle in the natural resource remote sensing mapping image positioning method is provided with a GNSS positioning module and an IMU (inertial measurement unit) measuring unit besides a remote sensing shooting module, the position information of the unmanned aerial vehicle can be acquired through the GNSS positioning module, meanwhile, the position deviation of the unmanned aerial vehicle can be reduced by combining the IMU measuring unit, then, the three-dimensional coordinates of a plurality of auxiliary datum points are combined to perform geographic coordinate positioning on a natural resource area, the area of the natural resource area is favorably calculated, and further, the assistance is favorably provided for the unified investigation of natural resources.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is an overall flowchart of a method for positioning a remote sensing mapping image of natural resources according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
Referring to fig. 1, the embodiment discloses a method for positioning a remote sensing mapping image of natural resources, which comprises the following specific steps:
(1) obtaining an original remote sensing image: the method comprises the following steps that an unmanned aerial vehicle is controlled to fly to the upper space of a natural resource area to be measured to carry out remote sensing shooting, and a plurality of original remote sensing images are obtained;
specifically, the resource to be detected is water resource, agricultural resource, forest resource, land resource and vegetation resource; it should be noted that the resources to be measured include not only those listed above, but also all natural resources having the characteristics of an obvious boundary range can be located by using the invention for boundary and geographic coordinate positioning;
specifically, the unmanned aerial vehicle comprises a system control module, a power module, a GNSS positioning module, a remote sensing shooting module and an IMU measuring unit, wherein the IMU measuring unit comprises a three-axis accelerometer and a three-axis gyroscope;
specifically, the control module is used for receiving instructions of ground control personnel to control other modules and units; the power module is used for supporting the flight of the unmanned aerial vehicle; the GNSS positioning module is used for acquiring the position information of the unmanned aerial vehicle; the remote sensing shooting module is used for acquiring an original remote sensing image of a natural resource area to be detected; the three-axis accelerometer is used for measuring acceleration information of the unmanned aerial vehicle; the three-axis gyroscope is used for measuring the angular velocity information of the unmanned aerial vehicle.
(2) Processing an original remote sensing image: preprocessing a plurality of original remote sensing images obtained in the step (1), removing errors caused by external factors, and simultaneously performing fusion processing on the original remote sensing images to obtain target remote sensing images;
specifically, the original remote sensing image processing comprises radiometric calibration processing, geometric correction processing, atmospheric correction processing and image fusion processing; it should be noted that the above processing method is determined according to actual conditions, and some of the processing methods may be omitted in special cases.
(3) And (3) boundary positioning: inputting the target remote sensing image in the step (2) into a natural resource positioning model to be detected for range boundary positioning to obtain the boundary of the natural resource region to be detected;
(4) auxiliary datum point installation: installing a plurality of auxiliary reference points in the natural resource area to be detected in the step (1);
(5) geographic coordinate positioning and area determination: carrying out geographic coordinate positioning on the boundary of the natural resource area to be detected according to the auxiliary reference points in the step (4) and the unmanned aerial vehicle in the step (1), and obtaining the boundary geographic coordinate of the natural resource area to be detected; meanwhile, area calculation is carried out on the natural resource area to be detected, namely the area of the natural resource area to be detected is determined;
specifically, the specific process of the geographic coordinate positioning and area determination is as follows:
SS 1: acquiring the position information of the unmanned aerial vehicle through a GNSS positioning module, measuring the acceleration information and the angular velocity information of the unmanned aerial vehicle by using a three-axis accelerometer and a three-axis gyroscope, and eliminating the deviation of the position information of the unmanned aerial vehicle acquired by the GNSS positioning module through fusion calculation to obtain the space three-dimensional coordinate of the unmanned aerial vehicle;
SS 2: acquiring three-dimensional coordinates of a plurality of auxiliary reference points;
SS 3: calculating the boundary of the natural resource area to be detected by taking the spatial three-dimensional coordinates of the unmanned aerial vehicle in the step SS1 and the three-dimensional coordinates of the auxiliary reference points in the step SS2 as reference points to obtain the boundary geographical coordinates of the natural resource area to be detected;
SS 4: and calculating the area of the natural resource area to be detected according to the boundary geographical coordinates of the natural resource area to be detected in the step SS3, namely determining the area of the natural resource area to be detected.
Referring to fig. 1, this embodiment discloses a method for positioning a remote sensing mapping image of natural resources, which specifically describes a process for forming a positioning model of natural resources to be measured, except for the same structure as the above embodiment;
specifically, the natural resource positioning model to be measured is obtained after deep learning training, and the specific forming process is as follows:
s1: firstly, drawing a representative area from a natural resource area to be detected as a training area;
s2: then, acquiring a plurality of sample original remote sensing images of the training area in the step S1 by using an unmanned aerial vehicle; preprocessing a plurality of sample original remote sensing images to obtain a plurality of sample target remote sensing images;
s3: decomposing and reconstructing the plurality of sample target remote sensing images in the step S2 by using a depth variation self-encoder to obtain a plurality of reconstructed sample target remote sensing images;
s4: extracting pixel values of natural resources to be detected in the multiple reconstructed sample target remote sensing images in the step S3; meanwhile, manually calibrating the pixel threshold range, and taking the calibrated pixel threshold as a training set;
s5: and (4) constructing an SVM classifier, and inputting the training set in the step S4 into the SVM classifier to obtain the natural resource positioning model to be detected.
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 to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (6)
1. A natural resource remote sensing mapping image positioning method is characterized by comprising the following specific steps:
(1) obtaining an original remote sensing image: the method comprises the following steps that an unmanned aerial vehicle is controlled to fly to the upper space of a natural resource area to be measured to carry out remote sensing shooting, and a plurality of original remote sensing images are obtained;
(2) processing an original remote sensing image: preprocessing the plurality of original remote sensing images in the step (1), removing errors caused by external factors, and simultaneously fusing the original remote sensing images to obtain target remote sensing images;
(3) and (3) boundary positioning: inputting the target remote sensing image in the step (2) into a natural resource positioning model to be detected for range boundary positioning to obtain a boundary of a natural resource region to be detected;
(4) auxiliary datum point installation: installing a plurality of auxiliary reference points in the natural resource area to be detected in the step (1);
(5) geographic coordinate positioning and area determination: carrying out geographic coordinate positioning on the boundary of the natural resource area to be detected according to the auxiliary reference points in the step (4) and the unmanned aerial vehicle in the step (1), so as to obtain the boundary geographic coordinate of the natural resource area to be detected; and simultaneously, carrying out area calculation on the natural resource region to be detected, namely determining the area of the natural resource region to be detected.
2. The method for positioning the remote sensing mapping image of natural resources according to claim 1, wherein the resources to be measured in the step (1) are water resources, agricultural resources, forest resources, land resources and vegetation resources; the unmanned aerial vehicle comprises a system control module, a power module, a GNSS positioning module, a remote sensing shooting module and an IMU measuring unit, wherein the IMU measuring unit comprises a three-axis accelerometer and a three-axis gyroscope.
3. The method for positioning remote sensing mapping images of natural resources according to claim 2, wherein the control module is used for receiving instructions of ground operators to control other modules and units; the power module is used for supporting the flight of the unmanned aerial vehicle; the GNSS positioning module is used for acquiring the position information of the unmanned aerial vehicle; the remote sensing shooting module is used for acquiring an original remote sensing image of a natural resource area to be detected; the three-axis accelerometer is used for measuring acceleration information of the unmanned aerial vehicle; the three-axis gyroscope is used for measuring the angular velocity information of the unmanned aerial vehicle.
4. The method for locating the remote sensing mapping image of natural resource according to claim 1, wherein the processing of the original remote sensing image in the step (2) includes a radiometric calibration process, a geometric calibration process, an atmospheric calibration process and an image fusion process.
5. The method for positioning the remote sensing mapping image of natural resources according to claim 1, wherein the natural resource positioning model to be measured in the step (3) is obtained by deep learning training, and the specific forming process is as follows:
s1: firstly, drawing a representative area from a natural resource area to be detected as a training area;
s2: then, acquiring a plurality of sample original remote sensing images of the training area in the step S1 by using an unmanned aerial vehicle; preprocessing the plurality of sample original remote sensing images simultaneously to obtain a plurality of sample target remote sensing images;
s3: decomposing and reconstructing the plurality of sample target remote sensing images in the step S2 by using a depth variation self-encoder to obtain a plurality of reconstructed sample target remote sensing images;
s4: extracting pixel values of natural resources to be detected in the multiple reconstructed sample target remote sensing images in the step S3; meanwhile, manually calibrating the pixel threshold range, and taking the calibrated pixel threshold as a training set;
s5: and (4) constructing an SVM classifier, and inputting the training set in the step S4 into the SVM classifier to obtain the natural resource positioning model to be detected.
6. The method for locating the remote sensing mapping image of natural resources according to claim 1, wherein the specific process of geographic coordinate locating and area determining in the step (5) is as follows:
SS 1: acquiring the position information of the unmanned aerial vehicle through a GNSS positioning module, measuring the acceleration information and the angular velocity information of the unmanned aerial vehicle by using a three-axis accelerometer and a three-axis gyroscope, and eliminating the deviation of the position information of the unmanned aerial vehicle acquired by the GNSS positioning module through fusion calculation to obtain the space three-dimensional coordinate of the unmanned aerial vehicle;
SS 2: acquiring three-dimensional coordinates of a plurality of auxiliary reference points;
SS 3: calculating the boundary of the natural resource area to be detected by taking the space three-dimensional coordinates of the unmanned aerial vehicle in the step SS1 and the three-dimensional coordinates of the auxiliary reference points in the step SS2 as reference points to obtain the boundary geographical coordinates of the natural resource area to be detected;
SS 4: and calculating the area of the natural resource area to be detected according to the boundary geographical coordinates of the natural resource area to be detected in the step SS3, namely determining the area of the natural resource area to be detected.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114518104A (en) * | 2022-03-14 | 2022-05-20 | 山东三津房地产评估有限公司 | Territorial surveying and mapping method, system and storage medium based on dynamic remote sensing monitoring technology |
| CN117115694A (en) * | 2023-10-18 | 2023-11-24 | 江苏中天吉奥信息技术股份有限公司 | Natural resource detection method based on survey and video data |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114518104A (en) * | 2022-03-14 | 2022-05-20 | 山东三津房地产评估有限公司 | Territorial surveying and mapping method, system and storage medium based on dynamic remote sensing monitoring technology |
| CN117115694A (en) * | 2023-10-18 | 2023-11-24 | 江苏中天吉奥信息技术股份有限公司 | Natural resource detection method based on survey and video data |
| CN117115694B (en) * | 2023-10-18 | 2024-01-26 | 江苏中天吉奥信息技术股份有限公司 | Natural resource detection method based on survey and video data |
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