CN102033898A - Extraction method for local cloud cover information metadata of moderate resolution imaging spectral image - Google Patents
Extraction method for local cloud cover information metadata of moderate resolution imaging spectral image Download PDFInfo
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Abstract
The invention discloses new remote sensing image metadata, and describes an extraction method of the metadata in detail. In the extraction method, by extracting the local cloud cover information of a moderate resolution imaging spectroradiometer, the concrete cloud cover information is provided for a user in the process of retrieving the remote sensing data of a specific study area, and the extraction method belongs to the field of remote sensing metadata. The method mainly aims to solve the problem of how to extract the cloud cover information of the area from a cloud mask image of the moderate resolution imaging spectroradiometer by a local vector boundary, and the method realizes quick extraction of the cloud cover information of the area by the following steps: judging the cloud mask image range of the moderate resolution imaging spectroradiometer and the study area range, mosaicking the image, preprocessing abnormal data of the edge of the image, superposing and cutting vector data and raster data, extracting the cloud cover information, and the like. The extraction method provided by the invention can accurately and quickly provide the local cloud cover information for users, thereby greatly improving the retrieval efficiency of the remote sensing data.
Description
Technical field
The invention belongs to remote sensing metadata field, it is a kind of new metadata that proposes at the metadata disappearance that reflects local remote sensing image quality in the remotely-sensed data retrieval, and the method for the local cloud amount information of rapid extraction, main local cloud amount information extraction by Moderate Imaging Spectroradiomete (MODIS), make the user in the process of retrieval particular studies regional remote sensing data, obtain concrete local cloud amount information, and, improve the efficient of data retrieval as the retrieval restrictive condition.
Background technology
The extraction of cloud amount information has great significance for remote sensing application research in the remote sensing image.Cloud covers or even approaches cloud for the various face of land of inverting parameter important influence.For the zone that influenced by cloud and mist, regional accurately local cloud amount information, be the important evidence of judging and select remote sensing image, thereby be necessary the regional cloud amount information of remote sensing image is extracted, and with its metadata item as description and retrieval remote sensing image.
In existing remote sensing image metadata standard, the metadata item of describing cloud amount information is less, among the remote sensing image metadata standard ISO 19115-2 that formulates as International Organization for Standardization, that describes remote sensing image cloud amount information only has a CloudCover Percentage (cloud amount number percent).China's geography information is shared in the metadata standard of field, this description entry of clouding coating ratio is also only arranged, among the sensor information metadata standard FGDC-STD-012-2002 that the geodata council of the United States Federal (FGDC) formulates, average cloud amount is equally also only arranged, all lack the description of local cloud amount information in the main remote sensing metadata standard.
Because the disappearance of above metadata, design to existing remote sensing image searching system and remote sensing image base management system exerts a certain influence, present system does not generally provide or only provides average cloud amount or four jiaos of cloud amount of remote sensing image, remote sensing image for wide coverage, for example the sweep length of MODIS image is 2330 kilometers, because cloud amount is spatially gone up the irregularities that distributes with the time, the judgement of the definite and quality of data of survey region position is all comparatively difficult, the situation that only can not reflect local cloud amount with average cloud amount or four jiaos of cloud amount information, make the user in the process of remote sensing image retrieval, not only to expend a large amount of time, and be difficult to the remote sensing image quality in particular studies zone is made right judgement.
With respect to average cloud amount and four jiaos of cloud amount, local cloud amount is the reflecting regional quality of image more accurately, make the retrieval of remotely-sensed data have more specific aim, particularly for the user in non-Remote Sensing Study field, can make the user can obtain the information of cloud amount accurately of survey region fast, thereby greatly improve user's recall precision.Simultaneously, this method can extend to the extraction of arbitrary polygon zone cloud amount information.
Thereby be necessary in the design of sensor information metadata, introduce " local cloud amount " this data item, make the user can carry out the inquiry of cloud amount information, and can analyze, judge the regional remote sensing quality of image with this to cloud amount information that should the zone in the retrieval time scope to the particular studies zone.
Summary of the invention
The object of the present invention is to provide a kind of local cloud amount information word data extraction method of intermediate-resolution imaging spectral image, by the local cloud amount information extraction of Moderate Imaging Spectroradiomete (MODIS), for the user provides concrete cloud amount information in the process of retrieval particular studies regional remote sensing data.
Concrete technical scheme of the present invention is: adopt the overlapping seek of latitude data on the adjacent scanning strip column direction to go out overlapping areas, revise the overlapping of latitude data with linear interpolation, revise the overlapping of image data with distance weighted interpolation, realize the stack of vector and raster data with high-order moment match and least square method, and obtain local cloud amount image by the raster data cutting, cloud pixel point and total pixel point number calculate cloud amount information in the statistical regions.
Its concrete steps are as follows:
Step 1: the Moderate Imaging Spectroradiomete image has the territory, cloud sector to extract
A) read Moderate Imaging Spectroradiomete cloud mask product image
Moderate Imaging Spectroradiomete cloud mask product image is that per unit information is with 6 bits with the binary file of IMG form storage, and the mode that every byte is 8 is stored, and the mode of this The data binary stream reads file content, and then reads cloud mask data content;
B) two-value is divided cloud and cloudless zone
In Moderate Imaging Spectroradiomete cloud mask product image readme file, the criterion that whether pixel point is had cloud, the binary data of each pixel that this step a) is read carries out bit arithmetic, whether the pixel point as a result that obtains is covered by cloud, and according to cloud covering result, all pixel points in the image are carried out two-value divide, territory, cloud sector assignment 255 is wherein arranged, cloudless area assignment 0;
Step 2: the longitude and latitude data that read image
Use function in the hierarchy type file layout class libraries to carry out reading of longitude and latitude data in the Moderate Imaging Spectroradiomete image data, its step is as follows:
A) open hierarchy type file layout file and initialization interface;
The science data set name that b) will read claims to be converted to call number;
C) open corresponding science data collection according to the call number of science data collection;
D) if the science data collection that reads is multidimensional science data collection, then to defines reference position and the final position of being read the science data collection, otherwise needn't specify;
E) read the information of science data collection.When reading the longitude and latitude data,, leave in the row and column of two-dimensional array correspondence the data that read position according to scan line and scan columns correspondence;
F) visit of end science data collection;
G) judge whether to run through the science data collection of all appointments;
H) finish interface, close hierarchy type file layout file;
Step 3: read study area vector border vector data
Use the function in the ShapeLib class libraries to carry out reading of SHAPE form vector polygon data, its step is as follows:
A) open file and initialization interface;
B) read the polygon information of this document;
C) read appointment polygon object according to polygonal call number;
D) directly read each vertex information of polygon;
E) destroy the polygon object;
F) judge whether to run through the polygon of all appointments;
G) finish interface and close file;
Step 4: image and vector border coverage are extracted
Read the longitude and latitude data of all pixel points of four edges circle of Moderate Imaging Spectroradiomete image, and with the coverage of the polygon after all pixel point connections as image, all polygon vertex data on the vector border of reading, and with the coverage of the polygon after all summits connections as the vector border;
Step 5: whether image covers study area
According to the coverage on image and vector border, judge whether the image that reads covers the overlay area on vector border;
Step 6: image is searched
If image covers study area fully, then do not carry out this step, search otherwise carry out image according to following steps;
A) imaging time reads
Utilize the function of hierarchy type file layout class libraries directly to read the imaging time of Moderate Imaging Spectroradiomete image, concrete described identical with step 2;
B) the adjacent image of space-time is searched
Because the Moderate Imaging Spectroradiomete data time of the same latitude of process is at interval probably about 1 hour 30 minutes, thereby the time interval thought image adjacent on the time at 2 hours with two interior scape images, utilize the result of determination of step 5 simultaneously, find out have living space and go up adjacent image, all times go up remote sensing image adjacent and that cover study area and find out the most at last;
Step 7: the searching and revising of the unusual latitude of image edge data area
A) press scanning strip and divide the latitude data
Opening steps two e) two-dimensional array of the latitude deposit data that reads since first row, is a unit with the shared pixel of single scanning strip on the single-row direction, is unit with 10 pixels promptly, and the latitude data of these row are divided;
B) search overlapping latitude data
Extract the latitude data of two adjacent scanning strips in order successively, utilize a back scanning strip first row the latitude data and samely list latitude data all in the previous scanning strip and compare, and find out two laps between the scanning strip, the overlapping part of latitude data promptly is the scope of latitude data exception;
C) the overlapping latitude data of deletion
Previous scanning strip in two scanning strips of this step b), with the latitude data deletion of lap, and with the deletion latitude data and the pairing line number of deleted data be recorded in another array;
D) linear interpolation correction
Utilize the latitude data of having deleted the last column that keeps behind the scanning strip of lap data in this step c), and the data of a back scanning strip first row, adopt linear interpolation to fill up the blank latitude data in deletion back;
Step 8: the correction of image edge abnormal image data
A) deletion superimposed image data
Utilize in the Moderate Imaging Spectroradiomete grid image data, there are relation one to one in the image data of single lattice point and latitude data, and unusual latitude data corresponding image data also exist unusually, according to b in the step 7) result that searches directly finds out image data scope unusual in the adjacent scanning strip, and with superimposed image data deletion in the corresponding previous scanning strip, and with the deletion image data and the pairing line number of deleted data be recorded in another array;
B) distance weighted interpolation correction
Find out step 7 d) the revised latitude data that obtain and the step 7 c corresponding with it) the lap latitude data of the deletion of writing down, and the latitude data corresponding image data of the lap of deletion, find out latitude data with the most contiguous two deletions of revised latitude data, calculate the distance on this point and its most contiguous latitude at 2, and fill up the image data of deletion with distance weighted interpolation;
Step 9: grid, vector data stack
A) screen coordinate and image coordinate match
In the cloud mask image, uniformly-spaced extract the latitude and longitude coordinates and the corresponding screen coordinate thereof of each pixel correspondence according to scan line, adopt the transformational relation between quadratic polynomial match two coordinate systems, and determine the coefficient of quadratic polynomial to obtain two kinds of conversion formulas between coordinate system with least square method;
B) the accurate stack of vector point
Screen coordinate that step 9 a) obtains and image latitude and longitude coordinates conversion formula, the latitude and longitude coordinates of vector border vertices is converted to screen coordinate, and with the conversion after screen coordinate be the center, in the window of 15 pixels on the cloud mask image * 15 pixel sizes, find out the latitude and longitude coordinates of all pixel correspondences, calculate and this longitude and latitude variance, and find out the point of variance minimum, this point is exactly the position of vector border vertices on the cloud mask image;
Step 10: raster data cutting
Vector frontier point after the stack is linked, be depicted as the grid border, and in image, use the raster data cutting-out method, cut out local cloud mask image;
Step 11: local cloud amount information extraction
Read the pixel value of all local cloud mask image successively, total pixel number that cloud is covered in pixel and the zone is added up respectively, finally calculates the number percent that this zone cloud covers;
Step 12: output.
Described grid, vector data are superposed to: with the point of equal interval sampling screen coordinate and image coordinate, realize screen coordinate and image coordinate match with high-order moment and least square method, employing is the interior minimum variance modes of 15 * 15 windows at center with the match point, realizes the accurate stack of vector point.
The invention has the beneficial effects as follows: in existing remotely-sensed data metadata standard now, also not about this description entry of local metadata, and in the existing remotely-sensed data retrieving, the user also is difficult to obtain or only obtain cloud amount information local in the less image, difficult quality for the remote sensing image of reality is judged effectively, local cloud amount information extracting method provided by the invention, can be accurately fast for the user provide local cloud amount information, thus the recall precision of remotely-sensed data greatly improved.
Description of drawings
Fig. 1 is a process flow diagram of the present invention
Fig. 2 is that the present invention carries out the process flow diagram that geodata reads
Fig. 3 is that the present invention carries out the process flow diagram that vector data reads
Fig. 4 is an embodiment of the invention cloud mask image, the design sketch after the local enlarged drawing of research and the vector data stack
Fig. 5 is the local cloud amount of embodiment of the invention extraction and the comparison diagram of the whole cloud amount of image
Fig. 6 is the forward and backward extraction of an embodiment of the invention geometry correction comparison diagram as a result
Embodiment
Consult Fig. 1, Fig. 2 and Fig. 3, the present invention provides local cloud amount this data item for the remote sensing image retrieval, eliminate the edge abnormal data for the influence of extracting the result by the unusual data pre-service of image edge, stack and cutting by vector border data field grid remotely-sensed data, and the local cloud mask data that obtains carried out statistical study, calculate local cloud amount data, its concrete steps are:
Step 1: Moderate Imaging Spectroradiomete image 10 has the territory, cloud sector to extract
A) read the MOD35 cloud mask image 20 of storing by the IMG form
Moderate Imaging Spectroradiomete cloud mask product image is that per unit information is with 6 bits with the binary file of IMG form storage, and the mode that every byte is 8 is stored, and the mode of this The data binary stream reads file content, and then reads cloud mask data content;
B) two-value is divided cloud and cloudless regional 40
In the MOD35 readme file, the criterion that whether pixel point is had cloud, the binary data of each pixel that this step a) is read carries out bit arithmetic, whether the pixel point as a result that obtains is covered by cloud, and according to cloud covering result, all pixel points in the image are carried out two-value divide, territory, cloud sector assignment 255 is wherein arranged, cloudless area assignment 0;
Step 2: the longitude and latitude data 50 that read image
Function in the main use HDF class libraries carries out reading of MODIS longitude and latitude data, and the function of its step and use is as follows:
A) open HDF file and initialization SD interface (SDstart) 51;
The science data set name that b) will read claims (name as the latitude data set is called Latitude) to be converted to the call number (SDnametoindex) 52 of science data collection;
C) open corresponding science data collection (SDselect) 53 according to the call number of science data collection;
D), then to define reference position and the final position (start, edge) of being read the science data collection, otherwise needn't specify 54 if the science data collection that reads is a multidimensional science data collection (more than the one dimension);
E) read the information (SDreaddata) of science data collection.If what read is the longitude and latitude data,, leave in the row and column of two-dimensional array correspondence 55 in then with the data that read position according to scan line and scan columns correspondence;
F) visit (SDendaccess) 56 of end science data collection;
G) judge whether to run through the science data collection 57 of all appointments;
H) finish the SD interface, close HDF file (SDend) 58;
Step 3: study area vector data boundary 20 read 60
Function in the main use ShapeLib class libraries carries out reading of shape form vector polygon data, and the function of its step and use is as follows:
A) open file and initialization interface (SHPOpen) 61;
B) read the polygon information (SHPGetInfo) 62 of this document;
C) read appointment polygon object (SHPObject) 63 according to polygonal call number;
D) directly read each vertex information 64 of polygon;
E) destroy polygon object (SHPDestroyObject) 65;
F) judge whether to run through the polygon 66 of all appointments;
G) finish interface and close file (SHPClose) 67;
Step 4: image and vector border coverage extract 70
Read the longitude and latitude data of all pixel points of MODIS image four edges circle, and with the coverage of the polygon after all pixel point connections as image, all polygon vertex data on the vector border of reading, and with the coverage of the polygon after all summits connections as the vector border;
Step 5: whether image covers study area 80
According to the coverage on image and vector border, judge whether the image that reads covers the overlay area on vector border, and how many scopes of covering has;
Step 6: image searches 90
If image covers study area fully, then do not carry out this step, search otherwise carry out image according to following steps;
A) imaging time reads 91
Utilize the function of HDF class libraries directly to read the imaging time of MODIS image, concrete step is described identical with the function of use and step 2;
B) the adjacent image of space-time searches 92
Because the MODIS data time of the same latitude of process is at interval probably about 1 hour 30 minutes, thereby we thought time on adjacent image at 2 hours with two interior scape images with the time interval, utilize the result of determination of step 5 simultaneously, find out have living space and go up adjacent image, all times go up remote sensing image adjacent and that cover study area and find out the most at last;
Step 7: the unusual latitude of image edge data area search and revise 100
A) press scanning strip and divide latitude data 101
Opening steps two e) two-dimensional array of the latitude deposit data that reads from first row of array, is a unit with single scanning strip shared pixel number (10) on column direction, the latitude data is divided, and be arranged in order according to the order of scanning strip;
B) search overlapping latitude data 102
Extract the latitude data of two adjacent scanning strips in order successively, utilize a back scanning strip first row the latitude data and samely list latitude data all in the previous scanning strip and compare, and find out two laps between the scanning strip, the overlapping part of latitude data promptly is the scope of latitude data exception;
C) the overlapping latitude data 103 of deletion
Previous scanning strip in two scanning strips of this step b), with the latitude data deletion of lap, and with the deletion latitude data and the pairing line number of deleted data be recorded in another array;
D) the linear interpolation correction 104
Utilize in this step c), deleted the latitude data of the last column that keeps behind the scanning strip of lap data, and the data of a back scanning strip first row, utilize approach based on linear interpolation to fill up the blank latitude data in deletion back;
Step 8: the correction 110 of image edge abnormal image data
A) deletion superimposed image data 111
Because in the MODIS grid image data, there are relation one to one in the image data of single lattice point and latitude data, thereby unusual latitude data corresponding image data also exist unusually, can utilize this corresponding relation, according to b in the step 7) result that searches directly finds out image data scope unusual in the adjacent scanning strip, and with superimposed image data deletion in the corresponding previous scanning strip, and with the deletion image data and the pairing line number of deleted data be recorded in another array;
B) distance weighted interpolation correction 112
Find out step 7 d) the revised latitude data that obtain and the step 7 c corresponding with it) the lap latitude data of the deletion of writing down, and the latitude data corresponding image data of the lap of deletion, find out latitude data with the most contiguous two deletions of revised latitude data, calculate the distance on this point and its most contiguous latitude at 2, and fill up the image data of deletion with distance weighted interpolation;
Step 9: grid, vector data stack 120
A) screen coordinate and image coordinate match 121
In the cloud mask image, uniformly-spaced extract the latitude and longitude coordinates and the corresponding screen coordinate thereof of each pixel correspondence according to scan line, adopt the transformational relation between quadratic polynomial match two coordinate systems, and determine the coefficient of quadratic polynomial to obtain two kinds of conversion formulas between coordinate system with least square method;
B) the accurate stack 122 of vector point
The screen coordinate and the image latitude and longitude coordinates conversion formula that utilize step 9 a) to obtain, the latitude and longitude coordinates of vector border vertices is converted to screen coordinate, and with the conversion after screen coordinate be the center, in the window of 15 pixels on the cloud mask image * 15 pixel sizes, find out the latitude and longitude coordinates of all pixel correspondences, calculate and this longitude and latitude variance, and find out the point of variance minimum, this point is exactly the position of vector border vertices on the cloud mask image;
Step 10: raster data cutting 130
Vector frontier point after the stack is linked, be depicted as the grid border, and in image, use the raster data cutting-out method, cut out local cloud mask image;
Step 11: local cloud amount information extraction 140
Read the pixel value of all local cloud mask image successively, total pixel number that cloud is covered in pixel and the zone is added up respectively, finally calculates the number percent that this zone cloud covers;
Step 12: output 150.
Embodiment
Consult Fig. 1, Fig. 2, Fig. 3, Fig. 4, Fig. 5 and Fig. 6, extracted the cloud amount in Anhui Province in the MOD35/Terra image on daytime in March, 2010, selecting spatial resolution for use is the image of 1KM.According to process flow diagram of the present invention, through step 1 the cloud information in the MOD35 cloud mask image is extracted, and to having cloud and cloudless zone to carry out the two-value division, there is the territory, cloud sector to be shown as white, cloudless zone is shown as black, the method that provides with step 2 and step 3 has then read the longitude and latitude data of MOD35 image correspondence and the vector data boundary of survey region respectively.Utilize the method for step 4 to extract the coverage on image and study area vector border, method by step 5 finds out the same day, and all cover all adjacent remote sensing image of time and space of this study area, use the algorithm of step 6 and step 7, with revising unusually of all cloud mask image borders that extract, comprise unusual latitude data and unusual image data.Adopt the accurately method of stack of screen coordinate and image coordinate match and vector point, vector data boundary and grid image data are superposeed, and the method for use raster data cutting, obtain local cloud mask image, by the pixel number that statistics cloud wherein covers and the zone is overall respectively, finally obtain the cloud amount information in zone.
Fig. 4 is the Terra/MODIS cloud mask product on May 17th, 2008, this image covers Anhui Province fully, the whole cloud amount of this image is 72.98%, and the cloud amount in Anhui Province is 1.36%, extract the result as can be seen from Anhui Province's cloud amount, local cloud amount can not be subjected to the interference of whole cloud amount, more accurately the remote sensing image quality in image study zone.Simultaneously, local cloud amount shown in Figure 5 extracts result and the average cloud amount contrast of image, and the extraction interpretation of result of the local cloud amount of the forward and backward image of geometric correction shown in Figure 6, can further find out the raising of local cloud amount on the reflection particular studies regional remote sensing quality of image.
Table-1: Moderate Imaging Spectroradiomete MODIS important technological parameters
The concrete implication of preceding 3 bit bytes of table-2:MODIS cloud mask data
Find according to data-searching, existing remotely-sensed data retrieval, the time range and the spatial dimension of remotely-sensed data retrieval only are provided mostly, small part retrieval and management system provide the cloud amount information of overall cloud amount and four angle points of image of remote sensing image, as one of greatest factor that influences the remote sensing image quality, the cloud amount size has great significance for the judgement of remote sensing image quality, but existing remotely-sensed data retrieval is inaccurate for local cloud amount information description, the remotely-sensed data quality can't be provided for the user in particular studies zone, thereby reduced the efficient of user search remotely-sensed data, for this reason, we adopt the vector data boundary in particular studies zone, from MODIS cloud mask image, directly extract the cloud amount information of study area, for the user provides cloud amount information in the process of retrieve data.
The embodiment of the invention has been extracted the cloud amount in Anhui Province in the MODIS image on the TERRA satellite on daytime in March, 2010, and as can be seen, local cloud amount can reflect the quality of remote sensing image more accurately from extract result (Fig. 5), and carries out the efficient height.
Claims (2)
1. the local cloud amount information word data extraction method of an intermediate-resolution imaging spectral image is characterized in that this method comprises following concrete steps:
Step 1: the Moderate Imaging Spectroradiomete image has the territory, cloud sector to extract
A) read Moderate Imaging Spectroradiomete cloud mask product image
Moderate Imaging Spectroradiomete cloud mask product image is that per unit information is with 6 bits with the binary file of IMG form storage, and the mode that every byte is 8 is stored, and the mode of this The data binary stream reads file content, and then reads cloud mask data content;
B) two-value is divided cloud and cloudless zone
In Moderate Imaging Spectroradiomete cloud mask product image readme file, the criterion that whether pixel point is had cloud, the binary data of each pixel that this step a) is read carries out bit arithmetic, whether the pixel point as a result that obtains is covered by cloud, and according to cloud covering result, all pixel points in the image are carried out two-value divide, territory, cloud sector assignment 255 is wherein arranged, cloudless area assignment 0;
Step 2: the longitude and latitude data that read image
Use function in the hierarchy type file layout class libraries to carry out reading of longitude and latitude data in the Moderate Imaging Spectroradiomete image data, its step is as follows:
A) open hierarchy type file layout file and initialization interface;
The science data set name that b) will read claims to be converted to call number;
C) open corresponding science data collection according to the call number of science data collection;
D) if the science data collection that reads is multidimensional science data collection, then to defines reference position and the final position of being read the science data collection, otherwise needn't specify;
E) read the information of science data collection.When reading the longitude and latitude data,, leave in the row and column of two-dimensional array correspondence the data that read position according to scan line and scan columns correspondence;
F) visit of end science data collection;
G) judge whether to run through the science data collection of all appointments;
H) finish interface, close hierarchy type file layout file;
Step 3: read study area vector border vector data
Use the function in the ShapeLib class libraries to carry out reading of SHAPE form vector polygon data, its step is as follows:
A) open file and initialization interface;
B) read the polygon information of this document;
C) read appointment polygon object according to polygonal call number;
D) directly read each vertex information of polygon;
E) destroy the polygon object;
F) judge whether to run through the polygon of all appointments;
G) finish interface and close file;
Step 4: image and vector border coverage are extracted
Read the longitude and latitude data of all pixel points of four edges circle of Moderate Imaging Spectroradiomete image, and with the coverage of the polygon after all pixel point connections as image, all polygon vertex data on the vector border of reading, and with the coverage of the polygon after all summits connections as the vector border;
Step 5: whether image covers study area
According to the coverage on image and vector border, judge whether the image that reads covers the overlay area on vector border;
Step 6: image is searched
If image covers study area fully, then do not carry out this step, search otherwise carry out image according to following steps;
A) imaging time reads
Utilize the function of hierarchy type file layout class libraries directly to read the imaging time of Moderate Imaging Spectroradiomete image, concrete described identical with step 2;
B) the adjacent image of space-time is searched
Because the Moderate Imaging Spectroradiomete data time of the same latitude of process is at interval probably about 1 hour 30 minutes, thereby the time interval thought image adjacent on the time at 2 hours with two interior scape images, utilize the result of determination of step 5 simultaneously, find out have living space and go up adjacent image, all times go up remote sensing image adjacent and that cover study area and find out the most at last;
Step 7: the searching and revising of the unusual latitude of image edge data area
A) press scanning strip and divide the latitude data
Opening steps two e) two-dimensional array of the latitude deposit data that reads since first row, is a unit with the shared pixel of single scanning strip on the single-row direction, is unit with 10 pixels promptly, and the latitude data of these row are divided;
B) search overlapping latitude data
Extract the latitude data of two adjacent scanning strips in order successively, utilize a back scanning strip first row the latitude data and samely list latitude data all in the previous scanning strip and compare, and find out two laps between the scanning strip, the overlapping part of latitude data promptly is the scope of latitude data exception;
C) the overlapping latitude data of deletion
Previous scanning strip in two scanning strips of this step b), with the latitude data deletion of lap, and with the deletion latitude data and the pairing line number of deleted data be recorded in another array;
D) linear interpolation correction
Utilize the latitude data of having deleted the last column that keeps behind the scanning strip of lap data in this step c), and the data of a back scanning strip first row, adopt linear interpolation to fill up the blank latitude data in deletion back;
Step 8: the correction of image edge abnormal image data
A) deletion superimposed image data
Utilize in the Moderate Imaging Spectroradiomete grid image data, there are relation one to one in the image data of single lattice point and latitude data, and unusual latitude data corresponding image data also exist unusually, according to b in the step 7) result that searches directly finds out image data scope unusual in the adjacent scanning strip, and with superimposed image data deletion in the corresponding previous scanning strip, and with the deletion image data and the pairing line number of deleted data be recorded in another array;
B) distance weighted interpolation correction
Find out step 7 d) the revised latitude data that obtain and the step 7 c corresponding with it) the lap latitude data of the deletion of writing down, and the latitude data corresponding image data of the lap of deletion, find out latitude data with the most contiguous two deletions of revised latitude data, calculate the distance on this point and its most contiguous latitude at 2, and fill up the image data of deletion with distance weighted interpolation;
Step 9: grid, vector data stack
A) screen coordinate and image coordinate match
In the cloud mask image, uniformly-spaced extract the latitude and longitude coordinates and the corresponding screen coordinate thereof of each pixel correspondence according to scan line, adopt the transformational relation between quadratic polynomial match two coordinate systems, and determine the coefficient of quadratic polynomial to obtain two kinds of conversion formulas between coordinate system with least square method;
B) the accurate stack of vector point
Screen coordinate that step 9 a) obtains and image latitude and longitude coordinates conversion formula, the latitude and longitude coordinates of vector border vertices is converted to screen coordinate, and with the conversion after screen coordinate be the center, in the window of 15 pixels on the cloud mask image * 15 pixel sizes, find out the latitude and longitude coordinates of all pixel correspondences, calculate and this longitude and latitude variance, and find out the point of variance minimum, this point is exactly the position of vector border vertices on the cloud mask image;
Step 10: raster data cutting
Vector frontier point after the stack is linked, be depicted as the grid border, and in image, use the raster data cutting-out method, cut out local cloud mask image;
Step 11: local cloud amount information extraction
Read the pixel value of all local cloud mask image successively, total pixel number that cloud is covered in pixel and the zone is added up respectively, finally calculates the number percent that this zone cloud covers;
Step 12: output.
2. data extraction method according to claim 1, it is characterized in that: described grid, vector data are superposed to: with the point of equal interval sampling screen coordinate and image coordinate, realize screen coordinate and image coordinate match with high-order moment and least square method, employing is the interior minimum variance modes of 15 * 15 windows at center with the match point, realizes the accurate stack of vector point.
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| CN102854513A (en) * | 2012-09-05 | 2013-01-02 | 环境保护部卫星环境应用中心 | Cloud detection method of CCD (charge coupled device) data of environment first satellite HJ-1A/B |
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