JP6184901B2 - Satellite image data processing apparatus, satellite image data processing system, satellite image data processing method and program - Google Patents

Description

  The present invention relates to a system for automatically joining a large amount of satellite image data to generate a wide range of joined satellite image data.

  Optical earth observation satellites are affected by clouds in order to observe human-visible information from outer space. Clouds often appear in the satellite image data acquired by the visible light sensor of the Earth observation satellite, and information on the area covered by the clouds cannot be confirmed from the satellite image. In such a case, normally, an alternative satellite image captured at another date and time is separately prepared, and a process of replacing an area covered with a cloud with data extracted from the alternative satellite image is performed (Patent Document). 1, 2).

JP 2001-143054 JP 2010-218434 A

  Recently, the amount of data observed by earth observation satellites is enormous, and it is required to create a wide range of joined satellite image data from a large amount of satellite image data. However, the techniques described in Patent Documents 1 and 2 are intended only for correction of a single satellite image data, and an optimum satellite image is extracted from a large number of satellite image candidates and joined to obtain a wide range of satellite images. It is not considered to generate.

  When trying to create a wide range of joined satellite image data from a large amount of satellite image data, it is often performed by visual inspection and manual selection, and the work becomes complicated and there is a risk of oversight.

On the other hand, there is a high possibility that clouds cannot be avoided by automatic processing.
An object of the present invention is to suppress the influence of clouds and improve the creation accuracy of satellite image data.

  According to one aspect of the present invention, there is provided a satellite image data processing device that automatically generates satellite image data including a region of the plurality of satellite image data by joining a plurality of satellite image data having different imaging conditions. Receiving satellite image data to be joined, cloud coverage condition (and photographing period) which is a joining process condition of the satellite image data, and grid parameters indicating the size of the grid dividing the satellite image into a plurality of regions. A grid data generating unit that generates grid data covering all of the satellite image data based on the grid parameters; and a target for calculating a cloud coverage in the grid defined by the grid data for the satellite image data. The satellite image data is rearranged in the plane direction so as to satisfy the cloud coverage ratio and the cloud coverage calculation processing unit, and the coverage in the overlay direction. Incidence and satellite image data combining processing section for joining the satellite images, satellite image data processing apparatus characterized by having a is provided by the superimposed said satellite image data so as to minimize.

  By processing satellite images in smaller grid units so that the cloud coverage is minimized, satellite images with a low cloud coverage can be obtained over a wide range. Can be reduced.

A land area classification processing unit for classifying a sea area and a land area based on a pixel value of the satellite image data, and the satellite image data joining processing unit is a land area classified in the sea area land classification processing unit The satellite images are joined by superimposing the satellite image data so that the cloud coverage is minimized.
The influence of clouds on land can be reduced.

  The sea area land classification processing unit calculates NDWI for each pixel value, creates a histogram of the NDWI values in the satellite image data, and determines the NDWI values that divide the peak between the land side and the sea side into the sea area and the land area. Is used as a threshold value for classifying.

The cloud coverage calculation processing unit is configured to determine whether or not the calculated cloud coverage is reduced to an allowable value (the influence of the cloud is suppressed and the land can be seen), and an allowable value. A re-setting unit that resets the joint processing conditions of the satellite image data when it is determined that the cloud coverage is not lowered to the above, and the joint processing conditions of the reset satellite image data are It is characterized by using and reprocessing.
Thereby, a good image can be obtained automatically.

The cloud coverage calculation processing unit is configured to determine whether or not the calculated cloud coverage is reduced to an allowable value (the influence of the cloud is suppressed and the land can be seen), and an allowable value. And a resetting unit that resets the grid parameter when it is determined that the cloud coverage is not lowered until the cloud coverage is reduced, and reprocessing is performed using the reset grid parameter. To do.
Thereby, a good image can be obtained automatically.

  As the joining process condition, an imaging period is used instead of the cloud coverage ratio condition or together with the cloud coverage ratio condition.

  The present invention also provides a satellite image data processing device that automatically generates satellite image data including a region of the plurality of satellite image data by combining a plurality of satellite image data having different imaging conditions. Receiving the satellite image data to be executed, the cloud coverage rate condition (and the imaging period) that is a joining process condition of the satellite image data, and the grid parameter indicating the size of the grid that divides the satellite image into a plurality of regions, A grid data generation unit that generates grid data that covers all of the satellite image data based on the parameters, and a cloud coverage calculation that calculates a cloud coverage in the grid defined by the grid data for the satellite image data The satellite image data is rearranged in the plane direction so as to satisfy the cloud coverage condition with the processing unit, and the cloud coverage is maximized in the overlay direction. A satellite image data combining processing section for joining the satellite images by the superimposing satellite image data so that a satellite image data processing apparatus characterized by having a.

  The satellite image data joint processing unit cuts out the satellite image into a grid range immediately before the process of joining the satellite images by superimposing the satellite image data so that the cloud coverage is minimized in the overlay direction. It is characterized by.

It has an exclusion processing unit for excluding satellite image data that does not meet the shooting date and time conditions among the joint processing conditions of the satellite image data in advance.
This eliminates unnecessary processing.

  The present invention also provides a satellite image data processing method for automatically generating satellite image data including a region of the plurality of satellite image data by joining a plurality of satellite image data having different imaging conditions. Receiving the satellite image data to be executed, the cloud coverage rate condition (and the imaging period) that is a joining process condition of the satellite image data, and the grid parameter indicating the size of the grid that divides the satellite image into a plurality of regions, A grid data generation step for generating grid data covering all of the satellite image data based on the parameters, and a cloud coverage calculation for calculating a cloud coverage in the grid defined by the grid data for the satellite image data Processing step, and rearranging the satellite image data in a plane direction so as to satisfy the cloud coverage ratio, a superposition direction Cloud coverage is a satellite image data processing method characterized by having a satellite image data bonding process step of bonding the satellite image by superimposing the satellite image data so as to minimize.

  The present invention may be a program for causing a computer to execute the satellite image data processing method described above.

The present invention also provides a satellite image data processing device that automatically generates satellite image data including a region of the plurality of satellite image data by combining a plurality of satellite image data having different imaging conditions. Receiving the satellite image data to be executed, the cloud coverage rate condition (and the imaging period) that is a joining process condition of the satellite image data, and the grid parameter indicating the size of the grid that divides the satellite image into a plurality of regions, A grid data generation unit that generates grid data that covers all of the satellite image data based on the parameters, and a cloud coverage calculation that calculates a cloud coverage in the grid defined by the grid data for the satellite image data The satellite image data is rearranged in the plane direction so as to satisfy the cloud coverage condition with the processing unit, and the cloud coverage is maximized in the overlay direction. And satellite image data combining processing section for joining the satellite images by the superimposing satellite image data so as to, a satellite image data processing apparatus characterized by having;
A satellite image data processing system comprising: a joint processing condition for the satellite image data; and a terminal device that transmits the grid parameters to the satellite image data processing device.

    According to the present invention, the selection and rearrangement work of satellite image data by the operator's visual observation is reduced. In addition, it is possible to reduce the risk of misjudgment in selecting satellite image data, the risk of overlooking the optimum image, and the burden on the operator.

It is a functional block diagram which shows the example of 1 structure of the satellite image data processing system by the 1st Embodiment of this invention. It is a functional block diagram which shows the example of 1 structure of a cloud coverage calculation process part. It is a flowchart figure which shows the flow of the satellite image data processing by the 1st and 2nd embodiment of this invention. It is a figure which shows the example of the automatic adjustment process of the parameter by the 2nd Embodiment of this invention. It is a figure which shows an example of the data stored in the grid data storage part. It is a figure which shows the mode of the 1st image processing by embodiment of this invention. It is a figure which shows the mode of the 2nd image processing by embodiment of this invention. It is a figure which shows the mode of the 3rd image processing by embodiment of this invention. It is a figure which shows the mode of the 4th image processing by embodiment of this invention. It is a figure which shows the mode of the 5th image processing by embodiment of this invention. It is a figure which shows the example of the histogram produced for every satellite image by embodiment of this invention. It is a figure which shows the mode of the 6th image processing by embodiment of this invention. It is a figure which shows the mode of the image processing by the 3rd Embodiment of this invention. It is a flowchart figure which shows the flow of the satellite image data process by the 3rd Embodiment of this invention.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

In the present embodiment, for example, a large number of satellite image data is used.
FIG. 1A is a functional block diagram illustrating a configuration example of a satellite image data processing system according to the first embodiment of the present invention.

  As shown in FIG. 1A, the satellite image data processing system A includes a satellite image data processing device 1, an input device 11, and a display device 12 that is an output device. These may be integrated devices. The satellite image data processing device 1 may be a server device, the input device may be a terminal device (for example, a portable terminal), and the output device may be a terminal device (for example, a portable terminal).

  The satellite image data processing device 1 includes a satellite image data storage unit 2 that stores satellite image data, and a grid data generation unit 3 that generates grid data that divides the satellite image data into, for example, small grid (grid-like) regions. A grid data storage unit 3a that stores grid data and image data in units of grids), a cutout processing unit 4 that cuts out satellite image data based on the grid data (an exclusion processing unit 4a that excludes certain satellite image data from the processing) Land area, land area for classifying sea areas, sea area classification processing unit 5, satellite image data rearrangement processing unit 6, cloud cover rate calculating unit 7 for calculating cloud cover rate, satellite image data joining process unit 8, It has a jointed satellite image data storage unit 9.

  The satellite image data storage unit 2 stores satellite image data to be joined, but two or more satellite image data to be joined are required. The grid data generation unit 3 is a part that generates a grid representing a region where the satellite image data is rearranged and joined, and the system user can specify the size of the grid from the input device 11.

  The satellite image data cutout processing unit 4 is a part that cuts out the satellite image data in the grid data area. The exclusion processing unit 4a excludes satellite image data that does not meet the conditions such as the shooting date input from the input device 11 from the processing target before input to the satellite image data cutout processing unit 4.

  The land area / sea area classification processing unit 5 is a part that performs processing for classifying (distinguishing) land areas and sea areas in the satellite image data. For example, NDWI (normalized water index) is calculated for each pixel (pixel) of the satellite image, and the land area and the sea area are classified based on threshold values.

  The satellite image data rearrangement processing unit 6 is a part for rearranging the satellite image data according to the priority order parameter for each grid area. The cloud coverage calculation processing unit 7 calculates the cloud coverage in consideration of the land and sea area information acquired by the land and sea classification processing unit 5, and a combination of satellite image data satisfying the cloud coverage input by the user. Search for.

  The satellite image data joining processing unit 8 is a part that joins satellite image data for each grid area. The spliced satellite image data storage unit 9 is a part for storing spliced satellite image data. The satellite image data processing device 1 can be connected to the display device 12 and can be visually recognized by displaying the satellite image data.

  FIG. 2 shows an example of a processing flow for automatically joining the satellite image data held in the satellite image data storage unit 2 in the satellite image data processing system A according to the first embodiment of the present invention. FIG. There are roughly three automatic image processing processes for satellite image data. The first process is to extract satellite image data into a grid area based on grid data. Search for satellite image data in units of grid areas according to priority parameters. A second process of (selecting) includes a third process of generating satellite image data of a wider area by joining the satellite image data searched for each grid area.

  FIG. 4 is a diagram illustrating an example of data stored in the grid data storage unit 3a. As shown in FIG. 4, the grid data storage unit 3a includes a grid number, a target image management table No, a flag for cloud coverage calculation processing (in the case of Yes in S11) described later, and a cloud coverage in the grid. And the calculation result is stored. With this data, it is possible to obtain which image data is used, whether the cloud coverage calculation processing has been completed, and the calculation result of the cloud coverage in the grid by the cloud coverage calculation processing. Thereby, in the satellite image joining process described later, a grid with the minimum cloud coverage can be easily obtained, so that the grid to be joined can be quickly acquired.

  As shown in FIG. 2, the process is started, and in step S <b> 1, from the input device 11, the candidate satellite image data to be joined, the shooting date and cloud coverage, which are indices for rearrangement during the joining process, Enter parameters such as grid data. For example, “use satellite image data after or before a certain date”, “use cloud coverage of 0.01 or less”, “use grid size of 10 m × 10 m” (satellite image size The input device 11 designates a condition such as 1/10 of the size.

  As shown by satellite image data 21a, 21b, etc. in FIG. 5, it is rare that the same area is captured in the satellite image, and images with different shooting areas and shooting dates overlap in many layers. Is. The satellite image data 21a, 21b and the like hold information such as the region (region information based on latitude and longitude) and the shooting date. Therefore, by collecting satellite image data groups in areas where latitude and longitude (position) are close to a certain extent, image data in a desired wide range area including all the satellite image data groups as shown in FIG. Can be obtained.

  Here, the cloud coverage parameter indicating the ratio of the cloud 23a covering the area is the ratio of the cloud amount included in each grid area. When analyzing the state of the surface of the earth, the cloud in the sea area has less influence than the cloud in the land area, so it is possible to set the cloud coverage for each land area and sea area. The tolerance of the cloud cover can be changed.

  The parameter of the grid data is indicated by, for example, the length of one side of each grid area of the generated grid data.

  Based on these parameters, it is possible to automatically determine the joining order of the satellite image data and perform the joining process.

  In step S2, based on the input grid data parameters, the grid data generation unit 3 generates grid data 25 so as to cover all the satellite image candidates 21a as much as possible as shown in FIG. To do. The grid data 25 is imaged in the grid data storage unit 3a.

  In step S3, the exclusion processing unit 4a excludes, from the joining process, satellite image data that does not meet the photographing date input by the user from the satellite image data candidates.

  In step S4, the satellite image data cutout processing unit 4 cuts out all satellite image data not excluded using the grid data 25 generated in step S2 in each grid area 25a as shown in FIG.

  In step S5, as shown in FIG. 8, the land area / sea area classification processing unit 5 uses the normalized vegetation index NDWI (Normalized Difference Water Index) for each pixel value to classify the land area and the sea area for the satellite image data. ). With NDWI, it is possible to distinguish between sea area and land area. Other indices may be used.

  The left figure of FIG. 8 is a diagram showing a state of the satellite image data 31 in which the land area 33, the sea area 35, and the clouds 37 straddling the boundary are shown. Here, as shown in Expression (1), the NDWI is calculated for each satellite image data 31, and the result of rearranging the calculation results for each pixel is shown in the right figure.

  Next, in step S6, the land area / sea area classification processing unit 5 creates a histogram of NDWI values in each satellite image data 31, as shown in FIG. FIG. 10 is a diagram illustrating an example of a histogram created for each satellite image. As shown in FIG. 10, when NDWI is taken on the horizontal axis and frequency (number of pixels) is taken on the vertical axis, the land-side histogram has a frequency distribution with a peak at the smaller NDWI, and the sea-side histogram is NDWI. The frequency distribution has a peak in the larger one. A valley portion between the two histograms is set as a threshold value for dividing the land area and the sea area. The threshold value is preferably calculated for each satellite image data 31.

  Next, in step S7, the land area (black) 33b and the sea area (white) 35b are classified as shown in the right figure of FIG. 9 using the threshold values obtained in step S6.

  FIG. 1B is a functional block diagram illustrating a configuration example of a cloud coverage calculation processing unit 7 that performs a process of calculating the cloud coverage. The cloud coverage calculation processing unit 7 includes a cloud coverage calculation unit 7-1, a cloud coverage determination unit 7-2, a resetting unit 7-3, and a calculation determination unit 7-4.

  In step S8, the satellite image data rearrangement processing unit 6 rearranges the satellite image data for each grid area according to the priority order parameter. That is, all the candidates for the rearrangement processing of the satellite image data are searched.

  In step S9, the cloud coverage calculation processing unit 7 calculates the cloud coverage for each grid data. More specifically, the cloud coverage calculation unit 7-1 calculates the cloud coverage in the grid under the conditions specified in step S1. An example of the calculation result is shown in FIG. Here, the conditions are, for example, as priority order parameters, the shooting date is January 1, 2013 or later, and the cloud coverage for each feature is 0.05 (5%) on the sea side and 0 on the land side. .01 (1%).

  In step S10, the cloud coverage determination unit 7-2 determines whether or not the cloud coverage (such as the set value in step S1) has decreased to an allowable value at which the influence of the clouds is suppressed and the land and the like can be seen. . As a result, when it is determined that the cloud coverage rate has decreased to the allowable value or less (Yes), the process proceeds to step S11. When it is determined that the cloud coverage has not decreased to the allowable value (No), in step S16, the process is repeated. The setting unit 7-3 resets parameters and the like, and returns to step S2 to perform processing under the reset conditions. This resetting process will be described in detail in the second embodiment.

  Next, in step S11, the calculation determination unit 7-4 determines whether or not the calculation of the cloud coverage is completed by searching for the rearrangement of the satellite image data in all the superimposition patterns and all the grids. Returning to S9 and continuing the process, if Yes, the process proceeds to Step S12.

  As shown in FIG. 11, the cloud coverage is calculated by superimposing the satellite images (for example, L1-L6), and calculating the cloud coverage in the grid by the rearrangement pattern of the satellite images (41). . When rearranged, reference numeral 43 is obtained.

  Next, in step S12, the satellite image joining process is started. In step S13, the satellite image data joining processing unit 8 has the position of the grid area 45 known as shown in FIG. By performing the joining process using a combination of satellite image data with the least cloud coverage, an optimum joining process result 47 can be obtained. In step S14, it is determined whether the joining process has been completed in all grid areas. If No, the process returns to step S13, and if Yes, the process ends in step S14. The joined satellite image data is stored in, for example, the joined satellite image data storage unit 9 in a state of being associated with each other including the position. The joined satellite image data is satellite image data with a low cloud coverage rate, whereby a good satellite image with little influence of clouds can be obtained over a wide area. The joined satellite image can be displayed on the display device 12 in step S15.

  According to the present embodiment, there is no need to select or rearrange satellite image data by the operator's visual observation, and it is possible to reduce the risk of erroneous determination of satellite image data selection, oversight of the optimum image, and the burden on the operator.

  The calculation based on the different cloud coverage depending on the sea area and the land area is arbitrary, and the processing may be performed for each grid based on the cloud coverage not depending on the sea area and the land area.

  As described above, according to the present embodiment, it is possible to automatically generate satellite image data that has been subjected to wide-area joining processing, which is optimal for a user who prioritizes shooting date and cloud coverage from a large amount of satellite image data. When the user inputs the shooting date and cloud coverage information of the satellite image data that he / she wants to generate, the system automatically selects the optimum image from the candidate satellite image data and executes the joining process. ing.

Next, a second embodiment of the present invention will be described.
In the present embodiment, in step S10 in FIG. 2, the cloud coverage determination unit 7-2 causes the cloud coverage to reach an allowable value at which the influence of clouds is suppressed and the land and the like can be seen (the set value in step S1 and the like). As a result of determining whether or not the cloud coverage rate has decreased to the allowable value (No), the resetting unit 7-3 performs parameter resetting in step S16. Under the conditions reset in step S16, the process returns to step S2 for processing.

  Regarding the resetting process, there are a first resetting process by a user input process and a second resetting process for automatically obtaining a reset value.

  In the first resetting process, for example, since the cloud coverage does not fall to the allowable value in the setting values of the priority order parameter and the grid parameter in step S1, for example, the shooting date in step S1 is set to January 2013. If the setting is traced back to one day, it is highly possible that the condition of the cloud coverage will be cleared if traced back to a previous time. Therefore, it is possible to cope with the setting by going back to January 1, 2012.

  FIG. 3 is a diagram showing an example of the second resetting process for automatically obtaining the reset value, and showing an example of automatically obtaining the parameter reset value. FIG. 3A is a diagram showing the dependence of the cloud coverage on the grid size. Based on the values plotted by repeating the actual calculation, the grid size for obtaining the desired cloud coverage is obtained and set to that value. Reset it. In this case, if the grid size is made smaller, it is highly possible that the cloud coverage condition can be cleared. Therefore, a grid size that can be cleared is obtained, and the value is automatically reset and processed. .

  FIG. 3B is a diagram showing the shooting date dependency of the cloud coverage, and based on the values plotted by repeating actual calculation up to the shooting date when a desired cloud coverage is obtained. The retroactive date is automatically determined and reset to be processed.

  As described above, according to the present embodiment, there is an advantage that a good satellite image can be obtained by automatically continuing processing until a desired cloud coverage is obtained.

Next, a third embodiment of the present invention will be described.
FIG. 13 is a flowchart showing the flow of satellite image data processing according to the present embodiment. FIG. 13 is a diagram corresponding to FIG. 2, and differences from FIG. 2 will be mainly described. In the present embodiment, at the stage where the grid data is generated (step S22), the satellite image is not cut out in the range of the grid, and in step S31, the superimposed pattern that satisfies the conditions of the cloud coverage of the land area and the sea area in the grid. As shown in FIG. 12, in step S32, the corresponding satellite image is cut out in the range of the grid in step S32, and in step S33, the joining process is performed with the pattern having the smallest cloud coverage in the land area. Do.

  That is, in the third embodiment, only grids that satisfy the conditions of the cloud coverage of the land area and the sea area are cut out, and grid joining processing is performed in a pattern with the minimum cloud coverage of the land area. What is the first embodiment that cuts out and extracts a superposition pattern that satisfies the conditions of the cloud coverage in the land and the sea, and then performs a satellite image joining process with a pattern with the minimum cloud coverage in the land? Is different. In the third embodiment, management of satellite images for each grid as shown in FIG. 4 is unnecessary.

  In both the first embodiment and the third embodiment, the cut-out processing in the grid range means the management and processing of data in the grid range in actual information processing. It is not always necessary to actually perform the joining for each cutting grid.

  The input device 11 in FIG. 1 may be a mobile terminal (such as a PC or a smartphone) possessed by a user. Thereby, the user can designate the size of each grid from an arbitrary position. Needless to say, the processed satellite image can also be obtained by the mobile terminal.

  In the above-described embodiment, the configuration and the like illustrated in the accompanying drawings are not limited to these, and can be appropriately changed within a range in which the effect of the present invention is exhibited. In addition, various modifications can be made without departing from the scope of the object of the present invention. Although the influence of clouds has been described here, it does not exclude other factors that have an adverse effect on images (a situation where it is difficult to see the bottom).

  Each component of the present invention can be arbitrarily selected, and an invention having a selected configuration is also included in the present invention.

  The present invention is applicable to a satellite image processing apparatus.

  A ... Satellite image data processing system, 1 ... Satellite image data processing device, 2 ... Satellite image data storage unit, 3 ... Grid data generation unit, 4 ... Satellite image data cut-out processing unit, 5 ... Land area, sea area classification processing unit, 6 ... Satellite image data rearrangement processing unit, 7 ... Satellite image data joining processing unit, 8 ... Joined satellite image data storage unit, 11 ... Input device, 12 ... Display device (result display unit).

Claims (12)

A satellite image data processing device that automatically generates satellite image data including a region of the plurality of satellite image data by joining a plurality of satellite image data with different imaging conditions,
Satellite image data that is to be joined, cloud coverage conditions that are joining processing conditions of the satellite image data, and grid parameters that indicate the size of the grid that divides the satellite image into a plurality of regions are received and based on the grid parameters A grid data generating unit for generating grid data covering all of the satellite image data;
With respect to the satellite image data, a cloud coverage calculation processing unit that calculates a cloud coverage in a grid defined by the grid data;
The satellite image data is arranged in the plane direction so as to satisfy the cloud coverage condition, and the satellite image is joined by superimposing the satellite image data so that the cloud coverage is minimized in the overlapping direction. A data junction processing unit;
A sea area land classification processing unit that classifies a sea area and a land area based on a pixel value of the satellite image data,
The satellite image data joining processor is
A satellite image data processing apparatus for joining the satellite images by superimposing the satellite image data so that the cloud coverage of the land area classified by the sea area land area classification processing unit is minimized . The sea area land classification processing unit,
Calculate the NDWI for each pixel value, create a histogram of the NDWI values in the satellite image data, and use the NDWI values that divide the peak between the land side and the sea side as threshold values for classifying the sea area and the land area. The satellite image data processing apparatus according to claim 1 . A satellite image data processing device that automatically generates satellite image data including a region of the plurality of satellite image data by joining a plurality of satellite image data with different imaging conditions,
Satellite image data that is to be joined, cloud coverage conditions that are joining processing conditions of the satellite image data, and grid parameters that indicate the size of the grid that divides the satellite image into a plurality of regions are received and based on the grid parameters A grid data generating unit for generating grid data covering all of the satellite image data;
With respect to the satellite image data, a cloud coverage calculation processing unit that calculates a cloud coverage in a grid defined by the grid data;
The satellite image data is arranged in the plane direction so as to satisfy the cloud coverage condition, and the satellite image is joined by superimposing the satellite image data so that the cloud coverage is minimized in the overlapping direction. A data joining processing unit,
The cloud coverage calculation processing unit,
A cloud coverage determination unit that determines whether or not the calculated cloud coverage is reduced to an allowable value;
When it is determined that the cloud coverage is not lowered to an allowable value, a resetting unit that resets the joint processing conditions of the satellite image data, and
You characterized by reprocessing performed using a bonding process conditions of the satellite image data that has been re-set satellite image data processing apparatus. The cloud coverage calculation processing unit,
A cloud coverage determination unit that determines whether or not the calculated cloud coverage is reduced to an allowable value;
When it is determined that the cloud coverage is not lowered to an allowable value, a resetting unit that resets the joint processing conditions of the satellite image data, and
3. The satellite image data processing apparatus according to claim 2, wherein reprocessing is performed using the joint processing conditions of the reset satellite image data. A satellite image data processing device that automatically generates satellite image data including a region of the plurality of satellite image data by joining a plurality of satellite image data with different imaging conditions,
Satellite image data that is to be joined, cloud coverage conditions that are joining processing conditions of the satellite image data, and grid parameters that indicate the size of the grid that divides the satellite image into a plurality of regions are received and based on the grid parameters A grid data generating unit for generating grid data covering all of the satellite image data;
With respect to the satellite image data, a cloud coverage calculation processing unit that calculates a cloud coverage in a grid defined by the grid data;
The satellite image data is arranged in the plane direction so as to satisfy the cloud coverage condition, and the satellite image is joined by superimposing the satellite image data so that the cloud coverage is minimized in the overlapping direction. A data joining processing unit,
The cloud coverage calculation processing unit,
A cloud coverage determination unit that determines whether or not the calculated cloud coverage is reduced to an allowable value;
A resetting unit that resets the grid parameters when it is determined that the cloud coverage is not reduced to an allowable value,
You characterized by reprocessing performed using the grid parameters is reconfigured satellite image data processing apparatus. The cloud coverage calculation processing unit,
A cloud coverage determination unit that determines whether or not the calculated cloud coverage is reduced to an allowable value;
A resetting unit that resets the grid parameters when it is determined that the cloud coverage is not reduced to an allowable value,
4. The satellite image data processing apparatus according to claim 2, wherein reprocessing is performed using the reset grid parameter. The satellite image data processing apparatus according to any one of claims 1 to 6 , wherein an imaging period is used as the joining processing condition instead of the cloud coverage ratio condition or together with the cloud coverage ratio condition. The satellite image data joint processing unit superimposes after extracting satisfy superposition pattern cloud coverage is minimized in the direction to cut out a satellite image corresponding with the grid data within the range of the grid, the satellite The satellite image data processing apparatus according to any one of claims 1 to 3 , wherein the images are joined .   9. The apparatus according to claim 1, further comprising: an exclusion processing unit configured to exclude in advance satellite image data that does not meet the shooting date and time conditions from among the joint processing conditions of the satellite image data. The satellite image data processing apparatus described in 1. A satellite image data processing method for automatically generating satellite image data including a region of the plurality of satellite image data by joining a plurality of satellite image data having different imaging conditions,
Satellite image data that is to be joined, cloud coverage conditions that are joining processing conditions of the satellite image data, and grid parameters that indicate the size of the grid that divides the satellite image into a plurality of regions are received and based on the grid parameters Grid data generating step for generating grid data covering all of the satellite image data;
For the satellite image data, a cloud coverage calculation processing step for calculating a cloud coverage in a grid defined by the grid data;
The satellite image data is arranged in the plane direction so as to satisfy the cloud coverage condition, and the satellite image is joined by superimposing the satellite image data so that the cloud coverage is minimized in the overlapping direction. A data joining process step;
A marine land classification process step for classifying a marine area and a land area based on a pixel value of the satellite image data,
The satellite image data joining process step includes:
A satellite image data processing method characterized by joining the satellite images by superimposing the satellite image data so that the cloud coverage of the land area classified in the sea area land area classification processing step is minimized .   A program for causing a computer to execute the satellite image data processing method according to claim 10. A satellite image data processing device that automatically generates satellite image data including a region of the plurality of satellite image data by joining a plurality of satellite image data with different imaging conditions,
Satellite image data that is to be joined, cloud coverage conditions that are joining processing conditions of the satellite image data, and grid parameters that indicate the size of the grid that divides the satellite image into a plurality of regions are received and based on the grid parameters A grid data generating unit for generating grid data covering all of the satellite image data;
With respect to the satellite image data, a cloud coverage calculation processing unit that calculates a cloud coverage in a grid defined by the grid data;
The satellite image data is arranged in the plane direction so as to satisfy the cloud coverage condition, and the satellite image is joined by superimposing the satellite image data so that the cloud coverage is minimized in the overlapping direction. A data junction processing unit;
A sea area land classification processing unit that classifies the sea area and the land area based on the pixel value of the satellite image data,
The satellite image data joining processor is
A satellite image data processing apparatus that joins the satellite images by superimposing the satellite image data so that the cloud coverage of the land areas classified by the sea area land area classification processing unit is minimized ;
A joint processing condition for the satellite image data, and a terminal device for transmitting the grid parameter to the satellite image data processing device;
A satellite image data processing system.

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