CN114972482A - Application area statistical method for remote sensing image - Google Patents
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Abstract
The invention provides a method for counting the application area of a remote sensing image, which can accurately master the application condition of the remote sensing image, particularly on the national scale, the actual effective coverage capacity and the actual application condition of the remote sensing image, including key parameter information such as the resolution ratio, the shooting time, the space coverage range, the application area and the like of the remote sensing image, and support the overall acquisition, the reasonable layout and the scientific decision of the remote sensing image. The method fully grasps the acquisition capability and the coverage rule of the domestic public service satellite remote sensing image, utilizes the domestic public service satellite remote sensing image to the maximum extent, and can also provide data reference for making and supplementing a domestic and foreign commercial satellite remote sensing image plan in advance.
Description
Technical Field
The invention relates to the technical field of satellite remote sensing image processing, in particular to a method for counting the application condition of remote sensing image data from different sources.
Background
With the rapid development of remote sensing technology, information technology and IT technology, the acquisition capacity of remote sensing images is obviously improved, the engineering application field of the remote sensing images is continuously expanded, the method is substantially applied to the aspects of natural resource investigation and monitoring, supervision and law enforcement, national soil space planning, ecological environment protection and the like, and good social benefit and economic benefit are obtained.
The data source of the remote sensing image relates to different commercial or government institutions in China and abroad, and comprises data acquired by using aviation platforms such as an unmanned aerial vehicle and the like besides satellite data, wherein the satellite data comprises a WorldView high-grade series in the United states, a SPOT high-grade series in France, a BJ high-grade series in China, a GF high-grade series in China and the like. Under the condition that the application of remote sensing images is more and more extensive, if the same remote sensing image data is repeatedly purchased by different department units, the total expenditure of the country is greatly increased, therefore, the country gradually promotes the overall acquisition and sharing application of the remote sensing images from the top level design, and in 28 days 7 and 7 months 2021, the 'natural resource department remote sensing image overall planning and sharing management method' printed by the office hall of the natural resource department is a substantial measure, so that the purpose is to realize the 'one-to-many' purpose of the remote sensing images, promote the overall planning and sharing of the remote sensing images, fully exert the benefits of the remote sensing images, avoid repeated purchase and processing, reduce the waste of resources and greatly improve the application depth and value of the remote sensing images.
The area statistics of the existing remote sensing image application is generally carried out by taking scenes or frames as a unit according to the habit of image management and processing, calculating the area of the coverage area of each scene or frame of remote sensing image, and then carrying out accumulation statistics. There are two statistical ways in which the frequency of the signal,
one method is mainly developed by a remote sensing image acquisition management provider, statistics is carried out from the perspective of providing services for the remote sensing images, and the statistics method is used for mastering the service range and the service capacity of the remote sensing images.
The other method is mainly developed by a remote sensing image user, statistics is carried out from the perspective of remote sensing image application, the statistics is used for mastering the condition that the remote sensing image covers an application area so as to ensure that the remote sensing image is seamlessly covered as guidance, and the statistical method generally does not consider the overlapping coverage condition.
The remote sensing image application areas obtained by the two conventional statistical methods have redundancy, and relatively accurate data cannot be provided.
In the national conditions and national strength investigation projects of national state, such as national state and soil investigation, national geographic national condition monitoring and the like, which are implemented by the government of China, remote sensing images are required to be applied to spatial geographic information acquisition, and the requirements of uniform time points are met, namely the national conditions of which time point are reflected by investigation results. Therefore, for a spatial location, the applied remote sensing image needs to have definite shooting time information, but the overlapping coverage is mixed to cause the result to have time uncertainty. The design is significant for popularization and application of monitoring results, and a user can determine the time point of the spatial position information. Therefore, a full-coverage, non-overlapping coverage and seamless remote sensing image and a corresponding homeland space information result can be formed on the national scale. Meanwhile, the government projects are all national overall guarantee image data sources, domestic public service satellite remote sensing images are fully utilized, and domestic and foreign commercial satellite remote sensing images are replenished and purchased only in areas which cannot meet requirements, so that the remote sensing image acquisition cost can be reduced to the maximum extent. For the application requirement of the remote sensing image, if a statistical method can be provided, the coverage range of the existing remote sensing image resource can be obtained only by using less time in each project, so that the domestic public service satellite remote sensing image can be utilized to the maximum extent, and data reference can be provided for making and supplementing a domestic and foreign commercial satellite remote sensing image plan in advance.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method for counting the application area of a remote sensing image, so as to reduce or avoid the problems mentioned above.
The invention provides a statistical method for remote sensing image application area, which obtains accurate statistical data of the remote sensing image application area by analyzing available remote sensing image data in a specified geographic area at a plurality of specified times, and comprises the following steps:
and step A, selecting a plurality of standby remote sensing image data for the designated geographical area at the designated time, and respectively carrying out orthorectification according to a unified coordinate system. The selected remote sensing image data cover the designated geographical area, and the shooting time can be within 90 days before and after the designated time.
And B, selecting one of the digital ortho images obtained in the step A as a first reference image according to the priority of resolution, shooting time and quality, if the first reference image cannot fully cover the designated geographic area, selecting a second reference image to supplement the designated geographic area, and so on until the designated geographic area is fully covered to generate a fully covered image, selecting the content of the reference image with high priority as the content of an overlapped area when the reference images are overlapped with each other in the fully covered image, performing extraction processing on the area with invalid value coverage and cloud coverage in the fully covered image, and sequentially selecting effective and non-cloud-coverage data in the reference image with the second priority to replace the effective and non-cloud-coverage data.
And step C, according to the full-coverage digital ortho-images of the designated geographic area obtained in the step B, for polygons formed by the boundaries of all the digital ortho-images, creating metadata of a vector data structure, and calculating the area of each polygon in the metadata to obtain the plane area of each polygon under a unified coordinate system. Thereby obtaining the accurate data of the application area of the remote sensing image data in the step B.
And D, processing available remote sensing image data in a specified geographical area of a plurality of specified time according to the method from the step A to the step C, so that accurate statistical data of the application area of the remote sensing image in a large range can be obtained.
Preferably, in step a, the coordinate system is a 2000 national geodetic coordinate system.
Preferably, in step a, the number of the standby remote sensing image data is 2-5.
Preferably, in step B, the calculation formula of the priority is,
priority k 1/resolution + k2 (100-difference in acquisition time)/100 + k3 mass
In the above formula, the resolution is a parameter of the data source of each spare remote sensing image data,
the shooting time difference is the date difference between the shooting time of each spare remote sensing image data and the appointed time,
the quality is percentage data obtained by taking the area of the range covering the specified geographic area as a denominator and the area of a part covered by an invalid value and a cloud in the range covering the specified geographic area as a numerator in each spare remote sensing image data.
k1, k2, and k3 are adjustment constants for balancing the respective parameters, where k1 is 0.4, k2 is 0.4, and k3 is 0.2.
Preferably, in step B, for the area with invalid value coverage and cloud coverage, a straight line segment polygon mode is adopted when performing the matting processing. The boundary portion between different reference images is processed into line segments.
Preferably, in step C, the metadata is in a shape format.
Preferably, in step C, the metadata records a storage resolution and a shooting time in addition to the application area.
The method for counting the application areas of the remote sensing images can accurately master the application conditions of the remote sensing images, particularly on the national scale, the actual effective coverage capacity and the actual application conditions of the remote sensing images, including key parameter information such as resolution, shooting time, space coverage, application area and the like of the remote sensing images, and supports the overall acquisition, reasonable layout and scientific decision of the remote sensing images. The method fully grasps the acquisition capability and the coverage rule of the domestic public service satellite remote sensing image, utilizes the domestic public service satellite remote sensing image to the maximum extent, and can also provide data reference for making and supplementing a domestic and foreign commercial satellite remote sensing image plan in advance.
Drawings
The drawings are only for purposes of illustrating and explaining the present invention and are not to be construed as limiting the scope of the present invention. Wherein the content of the first and second substances,
FIG. 1 is a schematic diagram of a designated geographic area for remote sensing image application area statistics in accordance with one embodiment of the present invention;
FIG. 2 is a schematic illustration of a digital orthophoto image of a remote-sensing image covering the designated geographic area of FIG. 1;
FIG. 3 is a schematic illustration of a digital ortho image of another remote sensing image covering the designated geographic area of FIG. 1;
FIG. 4 is a schematic diagram of the digital ortho images of FIGS. 2 and 3 in an overlapped state;
FIG. 5 is a schematic diagram of a full-coverage digital ortho image of the designated geographic area of FIG. 1 obtained by the adjustment of the digital ortho images of FIGS. 2 and 3;
FIG. 6 is a diagram illustrating the corrected full-coverage digital ortho image of FIG. 5;
fig. 7 is a schematic diagram of the fully-covered digital ortho image of fig. 6 after boundary vectorization.
Detailed Description
In order to more clearly understand the technical features, objects, and effects of the present invention, embodiments of the present invention will now be described with reference to the accompanying drawings.
The invention provides a statistical method for remote sensing image application area, which obtains accurate statistical data of the remote sensing image application area by analyzing available remote sensing image data in a specified geographic area at a plurality of specified times, and comprises the following steps:
and step A, selecting a plurality of standby remote sensing image data for the designated geographical area at the designated time, and respectively carrying out orthorectification according to a unified coordinate system. The selected remote sensing image data cover the designated geographical area, and the shooting time can be within 90 days before and after the designated time.
The main source of the remote sensing image data is satellite data, and different satellites have respective operation rules, so that the satellite remote sensing image data cannot be guaranteed to exist at a specific time point for a specific designated geographic area, and therefore, in practical project application, the shooting time of the satellite data can be widened to the time period within the first 90 days and within the last 90 days of the designated time point, and satellite data covering the designated geographic area can be guaranteed to be obtained. In addition, since different satellite data may not necessarily ensure complete coverage for the designated geographic area, it is possible to cover only a portion of the designated geographic area, and the selected satellite data may cover at least 5% of the designated geographic area for the sake of computational efficiency.
The remote sensing image data obtained by different satellites have different mathematical bases, and the major projects have uniform requirements on a coordinate system, so that after a plurality of spare remote sensing image data are selected, a uniform coordinate system needs to be defined, and different satellite data related to the spare remote sensing image data can be subjected to orthorectification according to the uniform coordinate system, so that a digital orthoimage taking a scene or a frame as a unit is generated, and a 2000 national geodetic coordinate system is commonly used in China.
With the development of aerospace technology in China, satellite image data which can be provided by China is more and more abundant, in order to facilitate visual analysis for major national conditions and national forces investigation projects such as national state survey, national geographic national conditions monitoring and the like, high-resolution satellite image data with the resolution ratio not greater than 2.5 m and the key area not greater than 1 m is mainly used as data supplement, and when the number of the high-resolution satellite image data is not enough to cover a specified geographic area, the satellite image data with the resolution ratio lower than 2.5 m can also be used as standby remote sensing image data.
Because satellite data may have areas covered by invalid values and areas covered by clouds, in order to ensure the integrity of information acquisition of the specified geographic area, theoretically, the more spare remote sensing image data is, the better the data is, but the more data is, the more operation complexity is increased, and by researching and inventing by an inventor team, generally speaking, 2-5 spare remote sensing image data can better take account of the problems of data coverage and calculation power balance.
FIG. 1 is a schematic diagram of a designated geographic area for remote sensing image application area statistics in accordance with one embodiment of the present invention; FIG. 2 is a schematic illustration of a digital ortho image of a remote sensing image covering the designated geographic area of FIG. 1; FIG. 3 is a schematic illustration of a digital ortho image of another remote sensing image covering the designated geographic area of FIG. 1; referring to fig. 1-3, in a specific embodiment, a specific remote sensing image project needs to process data of a designated geographic area shown in fig. 1, the designated time point is 6 months and 30 days in 2021, the inventor team finds two remote sensing images covering the designated geographic area shown in fig. 1 from remote sensing image data 90 days before and after 30 days in 2021, the resolution of the two remote sensing images is 1 meter, the shooting time is 28 days in 2021 years and 4 months and 15 days in 2021 years, after performing an orthorectification process according to a 2000 national geodetic coordinate system, the digital orthoimages shown in fig. 2 and 3 are obtained, the shooting time of fig. 2 is 28 days in 2021 years and 6 months, and the shooting time of fig. 3 is 15 days in 2021 years and 4 months.
And B, selecting one of the digital ortho images obtained in the step A as a first reference image according to the priority of resolution, shooting time and quality, if the first reference image cannot fully cover the designated geographic area, selecting a second reference image to supplement the designated geographic area, and so on until the designated geographic area is fully covered to generate a fully covered image, selecting the content of the reference image with high priority as the content of an overlapped area when the reference images are overlapped with each other in the fully covered image, performing extraction processing on the area with invalid value coverage and cloud coverage in the fully covered image, and sequentially selecting effective and non-cloud-coverage data in the reference image with the second priority to replace the effective and non-cloud-coverage data.
As described above, since different satellites have respective operation rules, it is not necessary that the optimally selected satellite image fully covers the designated geographic area, and the remote sensing image data obtained from different satellites have differences in parameters such as shooting angle, resolution, coverage band, etc., and therefore, among the plurality of digital ortho images obtained in step a, it is necessary to select the reference images sequentially numbered according to the priority of resolution, shooting time, and quality, and specifically, the priority of the backup remote sensing image data can be set according to the following formula,
priority k 1/resolution + k2 (100-difference in acquisition time)/100 + k3 mass
In the above formula, the resolution is the parameter of the data source (satellite, aerial) of each spare remote sensing image data,
the difference in shooting time is a difference in date between the shooting time of each piece of backup remote sensing image data and the designated time, for example, if the shooting time is the same day as the designated time, the difference in shooting time is 0, if the shooting time is 30 days before or 30 days after the designated time, the difference in shooting time is 30,
the quality is percentage data obtained by taking the area of the range covering the specified geographic area as a denominator and the area of a part covered by an invalid value and a cloud in the range covering the specified geographic area as a numerator in each spare remote sensing image data.
k1, k2, and k3 are adjustment constants for balancing the respective parameters set by the inventors, and in the course of the studies by the inventors, it was found that the respective spare remote sensing image data can be balanced well when the values are set as follows, respectively, where k1 is 0.4, k2 is 0.4, and k3 is 0.2.
Taking the digital ortho-images shown in fig. 2 and 3 as an example, the resolution of both the backup remote sensing image data shown in fig. 2 and 3 is 1 meter, the shooting time in fig. 2 is 28/6/2021, and the shooting time in fig. 3 is 15/4/2021. Through the calculation of the computer, the computer can obtain the required data,
the resolution of fig. 2 is 1 meter, the difference in imaging time is 2 days, and the mass is about 92%, so that the priority of fig. 2 is 0.4/1+0.4 (100-2)/100+0.2 × 92%, 0.4+0.392+0.184, or 0.976.
The resolution of fig. 3 is 1 meter, the difference in imaging time is 76 days, and the mass is about 99%, so that the priority of fig. 3 is 0.4/1+0.4 (100-76)/100+0.2 × 99%, and 0.4+0.096+0.198 is 0.694.
Thus, for the designated geographic area shown in fig. 1, the digital ortho image shown in fig. 2 may be selected as the first reference image and the digital ortho image shown in fig. 3 may be selected as the second reference image.
Fig. 4 is a schematic diagram illustrating an overlapping state of the digital ortho images of fig. 2 and 3, and fig. 5 is a schematic diagram illustrating a full coverage digital ortho image of the designated geographic area of fig. 1 obtained by adjusting the digital ortho images of fig. 2 and 3;
referring to fig. 4, although the digital ortho image shown in fig. 3 covers the designated geographic area more, because the priority of the digital ortho image shown in fig. 2 is higher, the digital ortho image shown in fig. 5 is still the main digital ortho image shown in fig. 2 in the full coverage image of the designated geographic area, that is, the digital ortho image shown in fig. 2 is selected as the first reference image, and the digital ortho image shown in fig. 3 is selected as the second reference image.
Referring to fig. 5, the white area in the middle of fig. 5 is an area covered by an invalid value or covered by clouds in the digital ortho-image shown in fig. 2, and for this area, a matting process needs to be performed and corresponding area data in the digital ortho-image of fig. 3 is used for replacement. The white area in fig. 5 has irregular boundaries, and if the white area is scratched out according to the irregular boundaries, the operation efficiency is greatly affected.
FIG. 6 is a diagram illustrating the corrected full-coverage digital ortho image of FIG. 5; referring to fig. 6, for the irregular area to be extracted in fig. 5, the inventor team selects a polygon mode for processing, specifically, the boundary end point of the irregular area can be first calibrated on the computer, as shown in fig. 5 and 6, the upper right corner end point and the lower right corner end point can be first calibrated, the two end points are connected, if the whole right side boundary of the irregular area can be covered, the connection line is selected as a right side straight line boundary, then the lower left corner end point of the irregular area is selected, the lower left corner end point and the lower right corner end point are connected, if the whole lower boundary of the irregular area can be covered, the connection line is selected as a lower straight line boundary, then the upper left corner end point of the irregular area is selected, the upper left corner end point and the upper right end point are connected, if the whole upper boundary of the irregular area can be covered, the connection line is selected as an upper straight line boundary, then, the upper left end point and the lower left end point are connected, because the connecting line can not cover all left boundaries of the irregular area, the leftmost end point of the irregular area is marked, then the leftmost end point is respectively connected with the upper left end point and the lower left end point, the covering condition is detected, the connecting line of the leftmost end point and the lower left end point can cover the boundaries of the irregular area, therefore, the connecting line is reserved as a lower left straight line boundary, and the connecting line of the leftmost end point and the upper left end point can not cover the boundaries of the irregular area, therefore, a point which is farthest away from the connecting line can be selected as a correction end point in the vertical line direction of the connecting line of the leftmost end point and the upper left end point, and then the correction end point is respectively connected with the leftmost end point and the upper left end point, and an upper left straight line boundary is obtained.
As described above, for the regions covered by invalid values or covered by clouds in the first reference image, the straight-line polygon for cutting and matting can be obtained after analysis is performed according to the boundary nodes of these regions, and according to the foregoing method, the sides of the polygon usually do not exceed eight sides. Therefore, the operation efficiency of the computer can be greatly improved.
In addition, the boundary part between different reference images can be subjected to line segment processing, so that the processing efficiency of a subsequent computer can be improved. The operation of the line segmentation process can be performed by using computer software, and specifically, as shown in fig. 6, for the boundary between the first reference image shown in fig. 2 and the second reference image shown in fig. 3, the boundary can be similarly adjusted to a line segment boundary composed of a plurality of straight lines by using the automatic capture function of the ArcGIS software.
And step C, according to the full-coverage digital ortho-images of the designated geographic area obtained in the step B, for polygons formed by the boundaries of all the digital ortho-images, creating metadata of a vector data structure, and calculating the area of each polygon in the metadata to obtain the plane area of each polygon under a unified coordinate system. Thereby obtaining the accurate data of the application area of the remote sensing image data in the step B.
Fig. 7 is a schematic diagram of the fully-covered digital ortho image of fig. 6 after boundary vectorization. Fig. 7 is a schematic diagram, in which the boundary points of the right image polygons are not all displayed, as shown in fig. 6 and 7, as described above, in addition to the cutout portions being polygons, the boundaries between different reference images are also line segment boundaries composed of a plurality of straight lines, so that the entire full-coverage digital ortho image is composed of three polygons, which is very beneficial to creating the metadata of the vector data structure. Specifically, the metadata may be created in a shape format. After the metadata of the vector data structure is created, the area of each polygon in the metadata can be easily calculated by using a computer, and the plane area of each polygon under a unified coordinate system is obtained. Therefore, the application area of each reference image, namely each spare remote sensing image data is obtained.
Since the vector data structure is adopted, basic information such as resolution, shooting time, and the like can be recorded in addition to the application area.
And D, processing available remote sensing image data in a specified geographical area of a plurality of specified time according to the method from the step A to the step C to obtain a large amount of metadata, so that accurate statistical data of the application area of the remote sensing image in a large range can be obtained.
After a large amount of metadata in step C is obtained, the resolution may be graded (for example, graded into "better than 1 meter", "1 meter to 2.5 meters", or "lower than 2.5 meters") according to the resolution of the remote sensing image block recorded by the metadata, and the grading result is recorded into the resolution level attribute item, that is, the resolution level of each polygon is marked, and according to the mark, the application area cumulative value of the remote sensing image at each resolution level across the country can be obtained statistically.
Furthermore, the shooting time may be segmented (for example, into "1-3 months in 2021", "4-6 months in 2021", and "7-9 months in 2021") according to the shooting time of the remote sensing image block recorded by the metadata, and the segmentation result may be recorded in the shooting time period attribute item, that is, the shooting time period flag may be performed for each polygon, and the remote sensing image application area accumulated value for each shooting time period across the country may be obtained by statistics according to the flag.
And counting to obtain the area cumulative value of the corresponding attribute on the national scale from the perspective of other attributes according to the requirement.
The metadata of the vector data structure obtained in step C can easily store accurate data of parameters such as application area, resolution, and shooting time. Therefore, as described in the background section, for a large number of remote sensing image application scenes in projects such as national state and soil survey, national geographic and national condition monitoring and the like which are implemented for governments, in different project projects of national scale, the method can accurately grasp the application condition of the remote sensing image, especially on the national scale, the actual effective coverage capacity and the actual application condition of the remote sensing image, including key parameter information such as resolution, shooting time, space coverage, application area and the like of the remote sensing image, and support the overall acquisition, reasonable layout and scientific decision of the remote sensing image. The method fully grasps the acquisition capability and the coverage rule of the domestic public service satellite remote sensing image, utilizes the domestic public service satellite remote sensing image to the maximum extent, and can also provide data reference for making and supplementing a domestic and foreign commercial satellite remote sensing image plan in advance.
It should be appreciated by those of skill in the art that while the present invention has been described in terms of several embodiments, not every embodiment includes only a single embodiment. The description is given for clearness of understanding only, and it is to be understood that all matters in the embodiments are to be interpreted as including technical equivalents which are related to the embodiments and which are combined with each other to illustrate the scope of the present invention.
The above description is only an exemplary embodiment of the present invention, and is not intended to limit the scope of the present invention. Any equivalent changes, modifications and combinations that may be made by those skilled in the art without departing from the spirit and principles of the invention shall fall within the scope of the invention.
Claims (7)
1. A statistical method for remote sensing image application area is characterized in that accurate statistical data of the remote sensing image application area is obtained by analyzing available remote sensing image data in a specified geographic area of a plurality of specified time, and the statistical method comprises the following steps:
and step A, selecting a plurality of standby remote sensing image data for the designated geographical area at the designated time, and respectively carrying out orthorectification according to a unified coordinate system. The selected remote sensing image data cover the designated geographical area, and the shooting time can be within 90 days before and after the designated time.
And B, selecting one of the digital ortho images obtained in the step A as a first reference image according to the priority of resolution, shooting time and quality, if the first reference image cannot fully cover the designated geographic area, selecting a second reference image to supplement the designated geographic area, and so on until the designated geographic area is fully covered to generate a fully covered image, selecting the content of the reference image with high priority as the content of an overlapped area when the reference images are overlapped with each other in the fully covered image, performing extraction processing on the area with invalid value coverage and cloud coverage in the fully covered image, and sequentially selecting effective and non-cloud-coverage data in the reference image with the second priority to replace the effective and non-cloud-coverage data.
And step C, according to the full-coverage digital ortho-images of the designated geographic area obtained in the step B, for polygons formed by the boundaries of all the digital ortho-images, creating metadata of a vector data structure, and calculating the area of each polygon in the metadata to obtain the plane area of each polygon under a unified coordinate system. Thereby obtaining the accurate data of the application area of the remote sensing image data in the step B.
And D, processing available remote sensing image data in a specified geographical area of a plurality of specified time according to the method from the step A to the step C, so that accurate statistical data of the application area of the remote sensing image in a large range can be obtained.
2. The method of claim 1, wherein in step a, the coordinate system is a 2000 national geodetic coordinate system.
3. The method of claim 1, wherein in step a, the number of the spare telemetric image data is 2 to 5.
4. The method according to claim 1, wherein in step B, the priority is calculated by the formula,
priority k 1/resolution + k2 (100-capture time difference)/100 + k3 mass
In the above formula, the resolution is a parameter of the data source of each spare remote sensing image data,
the shooting time difference is the date difference between the shooting time of each spare remote sensing image data and the appointed time,
the quality is percentage data obtained by taking the area of the range covering the designated geographic area as a denominator and the area of a part covered by an invalid value and a cloud in the range covering the designated geographic area as a numerator in each spare remote sensing image data.
k1, k2, and k3 are adjustment constants for balancing the respective parameters, where k1 is 0.4, k2 is 0.4, and k3 is 0.2.
5. The method according to claim 1, wherein in step B, for the area where the invalid value coverage and cloud coverage exist, a straight line segment polygon mode is adopted for the matting processing. The boundary portion between different reference images is subjected to line segment processing.
6. The method according to claim 1, wherein in step C, the metadata is in shape format.
7. The method according to claim 1, wherein in step C, the metadata records a saving resolution, a shooting time, in addition to an application area.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106327452A (en) * | 2016-08-14 | 2017-01-11 | 曾志康 | Fragmented remote sensing image synthesis method and device for cloudy and rainy region |
| CN107527014A (en) * | 2017-07-20 | 2017-12-29 | 武汉珈和科技有限公司 | Crops planting area RS statistics scheme of sample survey design method at county level |
| CN112906455A (en) * | 2020-12-28 | 2021-06-04 | 国家海洋信息中心 | Coastal zone ecological system remote sensing identification method |
| WO2021255458A1 (en) * | 2020-06-16 | 2021-12-23 | Dark Horse Technologies Ltd | System and method for crop monitoring |
| CN114140477A (en) * | 2021-12-02 | 2022-03-04 | 青海省气象科学研究所 | Remote sensing extraction method, device, server and storage medium for Chinese wolfberry planting area |
-
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106327452A (en) * | 2016-08-14 | 2017-01-11 | 曾志康 | Fragmented remote sensing image synthesis method and device for cloudy and rainy region |
| CN107527014A (en) * | 2017-07-20 | 2017-12-29 | 武汉珈和科技有限公司 | Crops planting area RS statistics scheme of sample survey design method at county level |
| WO2021255458A1 (en) * | 2020-06-16 | 2021-12-23 | Dark Horse Technologies Ltd | System and method for crop monitoring |
| CN112906455A (en) * | 2020-12-28 | 2021-06-04 | 国家海洋信息中心 | Coastal zone ecological system remote sensing identification method |
| CN114140477A (en) * | 2021-12-02 | 2022-03-04 | 青海省气象科学研究所 | Remote sensing extraction method, device, server and storage medium for Chinese wolfberry planting area |
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