JP3466095B2 - Apparatus and method for analyzing global environment information based on satellite images - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to monitoring the global environment such as weather and ocean, and relates to an analyzing apparatus and method for analyzing global environment information based on image data.

[0002]

2. Description of the Related Art Today, Geostationary Meteorological Satellit
It has been attempted to analyze the temporal change of global environmental information by using the image of the earth taken by an artificial satellite such as e, GMS). Conventionally, environmental information at a certain point on the earth is obtained from an image and the temporal change at that point is analyzed.

However, there are few cases in which image data of a geostationary satellite, which is imaged hourly every day, is continuously used for analysis. It is considered that such an analysis was not performed because it is difficult to obtain the data and the data amount and the calculation amount thereof are huge.

For example, in analyzing the amount of solar radiation, data in the time zone after noon when the sun is highest becomes important.
However, in a global-scale image obtained from a geostationary satellite, there is a time difference of 8 hours in the local time (Local Time) at the eastern end and the western end of the image. Here, the local time represents a time based on the local meridian, and is compared with the standard time or the universal time.

For this reason, it becomes necessary to refer to different images depending on the longitude of the analysis point, and it is very difficult to compare the amount of solar radiation at all points included in the image in the same time zone. In addition, it is difficult to collectively calculate the time variation of the amount of solar radiation at those points.

An object of the present invention is to provide an analyzing device and method for efficiently comparing and analyzing environmental information on a global scale by utilizing images obtained from geostationary satellites and the like.

[0007]

FIG. 1 is a diagram showing the principle of an analyzing apparatus according to the present invention. The analysis device in FIG. 1 includes a dividing unit 1, a generating unit 2, a processing unit 3, and an output unit 4.

According to the first principle of the invention, the dividing means 1
Divides the image data 5 in the longitude direction to generate a plurality of divided image data 6, and the generation means 2 connects the divided image data 6 corresponding to the same local time to generate a local time image 7. Then, the output means 4 outputs the generated local time image 7.

For example, when the image data 5 relating to the environmental information is obtained from the satellite every hour, the dividing means 1 divides each image data 5 at a longitude interval of 15 degrees corresponding to the time difference of 1 hour, and divides the image data 5 for 1 hour. The divided image data 6 having a width of 15 degrees corresponding to each local time is generated. Further, the generation means 2 connects some of the divided image data 6 corresponding to the same local time to generate one local time image 7, and the output means 4
Output it.

As described above, by generating one local time image 7 from the divided image data 6 having almost the same local time and outputting it, the user can see the output local time image 7 and see the same local time. Environmental information at each point in the belt can be easily compared.

According to the second principle of the present invention, the dividing means 1 divides the image data 5 in the longitudinal direction to generate a plurality of divided image data 6, and the generating means 2 uses the same local time. Corresponding divided image data 6 are connected to generate a local time image 7. Then, the processing means 3 performs image processing using the generated local time image 7, and the output means 4 outputs the result of the image processing.

The generating means 2 generates a local time image 7 for each environmental information to be analyzed, for example. The processing means 3 also performs image processing such as generating a monthly average image from each local time image 7 and generating a difference image from two corresponding monthly average images of two years. And
The output unit 4 outputs, for example, a difference image for each environment information.

In this way, the local time image 7 is generated for one or a plurality of environmental information, and the image information of the same local time is averaged over one month or the difference between two image information is obtained. As a result, information indicating the time change of the environmental information can be obtained. The user can easily compare the time change of the environmental information at each point in the same time zone while looking at the output difference image. Further, by comparing the difference images of different environmental information, it is possible to estimate the causal relationship between the environmental information.

For example, the dividing means 1, the generating means 2 in FIG.
The processing means 3 corresponds to a CPU (central processing unit) 61 and a memory 62 of FIG. 11 described later, and the output means 4 of FIG. 1 corresponds to the output device 64 of FIG. Also, local time corresponds to the local time in the embodiment described later,
The image data 5 of FIG. 1 corresponds to the physical quantity image data 12 of FIG. 2, which will be described later, the divided image data 6 of FIG. 1 corresponds to the longitude-based divided image data 13 of FIG. 2, and the local time image 7 of FIG.
Corresponds to the same local time image data 14 of FIG.

[0015]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described in detail below with reference to the drawings. In this embodiment, in order to facilitate comparison of environmental information in the same time zone between points having different longitudes, the satellite image data is divided in the longitudinal direction at regular intervals, and image pieces corresponding to substantially the same local time are divided. Create an image of the same area as the original image by connecting the. As a result, it becomes possible to collectively compare the environmental information at each point and to process the information collectively. In the following description, this local time will be referred to as the local time, and the combined images will be referred to as the same local time image.

FIG. 2 shows a process for creating the same local time image from the geostationary satellite image data taken every hour.
The analysis device equipped with a computer first uses the visible sensor, infrared 1 sensor, and infrared 2 sensor
Insolation and sea surface temperature (SST) based on the satellite image data 11 taken every hour
Physical quantities (environmental information) such as are estimated, and physical quantity image data 12 representing the estimated physical quantities are generated (process P1).

Here, the universal time c
0-23 UTC daily according to
The satellite image data 11 at each time (1 hour interval) is given to the analysis device, and the physical quantity image data 12 at each time of 00 to 23 UTC is generated. In the physical quantity image data 12, the distribution of physical quantities is usually expressed by the difference in color and gradation of each pixel.

As a method for generating the physical quantity image data 12 from the satellite image data 11, any method can be used. For example, as a method for estimating the amount of solar radiation, a recursive method or a physical method based on image data observed by a visible sensor is used (C. Gautier, G. Diak and S.
Masse, “A Simple Physical Model to Estimate Incid
ent Solar Radiation at the Surface from GOES Satel
lite Data ”, Journal of Applied Meteorology, vol.
19, pp. 1005-1012, 1980 / C. Gautier, “Mesoscale I
nsolation Variability Derived from Satellite Dat
a ”, Journal of Applied Meteorology, vol. 21, pp. 5
1-58, 1982.).

In the recursive method, the amount of reflection and the amount of solar radiation are directly linked by a regression coefficient based on a statistical relationship. In the physical method, the amount of solar radiation is intervened by a model considering the physical process of radiation. Presumed.

In addition, as the method for estimating the sea surface temperature, infrared rays 1,
Spli based on image data observed by infrared 2 sensor
t Window method is used (DA May, MM Parmeter,
DS Olszewski and BD Mckenzie, “Operational P
rocessing of Satellite Sea Surface Temperature Ret
rievals at the Naval Oceanographic Office ”, Bulle
tin of American Meteorological Society, vol. 79, N
o. 3, pp. 397-407, 1998.). Besides, it is possible to generate the physical quantity image data 12 from the satellite image data 11 for the physical quantities such as the temperature, the amount of water vapor, the wind direction, and the wind speed.

Next, the analysis device uses each physical quantity image data 1
2 is divided in the longitudinal direction at intervals of 15 degrees to generate longitude-divided divided image data 13 (process P2). Then, they are joined together to synthesize the same local time image data 14 every hour (process P3).

Since the sun goes around the earth in 24 hours, an interval of 15 degrees in longitude corresponds to a time difference of 1 hour in local time. Therefore, when the physical quantity image data 12 is prepared every hour, the divided image data 13 can be joined together without waste by dividing them every 15 degrees.

In general, the generated physical quantity image data 12
If the time interval of Δt time is Δt time, the divided image data 13 can be joined without waste by dividing them by 15Δt degrees in the longitude direction.

FIG. 3 shows the specifications of the satellite image data 11 obtained from a certain geostationary satellite. In this case, the imaging area is in the range of (80 degrees east longitude, 60 degrees north latitude) to (160 degrees west longitude, 60 degrees south latitude), and the number of pixels thereof is 2400 × 24.
00. In addition, a square lattice is used for projection conversion,
The imaging frequency is hourly. However, the imaging by the visible sensor is limited to the time zone of 21 to 10 UTC.

FIG. 4 shows an example of the gradation conversion table of the physical quantity image data 12. Here, as for the amount of solar radiation, one gradation corresponds to 5 W / m ² , and the amount of solar radiation of 0 to 1280 W / m ² is expressed using 256 gradations of 0 to 255. Regarding the sea surface temperature, one gradation corresponds to 0.2 ° C, and a temperature of -16.2 to 35.0 ° C is expressed using 256 gradations of 0 to 255.

FIG. 5 shows the relationship between the longitude and the local time in the imaging area (80 degrees east to 160 degrees west) of the satellite image data 11. For example, when capturing a satellite image of 03 UTC, the geostationary satellite starts capturing the image at 02:30 UTC and captures the entire earth in the direction from the North Pole to the South Pole for 30 minutes. Therefore, the imaging time near the equator is around 02:45 UTC (around 11:45 Japan time).

At this time, since the sun is southward at a point of 140 degrees east longitude, here, an image piece cut out from the physical quantity image data 12 of 03 UTC with a width of 15 degrees centering on 140 degrees east longitude (E140 degrees). , As the divided image data 13 at 12 o'clock local time.

Corresponding to this, from the physical quantity image data 12 of 03 UTC, E80 °, E95 °, E110 °, E
Each image piece cut out with 125 ° as the center,
Adopted as the divided image data 13 at the local time of 8, 9, 10 and 11:00, and from the physical quantity image data 12 of 03 UTC,
E155 °, E170 °, W (West longitude) 175 °, W16
The image pieces cut out with 0 ° as the center are adopted as the divided image data 13 at the local times 13, 14, 15 and 16 o'clock.

The local time of each image piece cut out from the physical quantity image data 12 corresponding to another imaging time is 03UT.
Compared with the local time of each image piece cut out from the physical quantity image data 12 of C, it is shifted back and forth by an integral multiple of one hour.

In this way, in the image pickup area, the local time advances by 1 hour each time it moves east by 15 degrees, and
At the 60 degree point, local time is 8 hours ahead of the 80 degree east longitude point.

FIG. 6 shows an area of the physical quantity image data 12 corresponding to the imaging area shown in FIG. This image area is divided into divided image data 13 having a width of 15 degrees centered on each longitude position shown in FIG. 5, and the divided image data 13 corresponding to the same local time are connected to each other to obtain the same hourly data. The local time image data 14 is generated. In the same local time image data 14, the local time of each point is set to be substantially the same within the range of the time difference corresponding to the division interval.

The above-mentioned 03UTC physical quantity image data 12
In the case of, an image piece 2 with a width of 15 degrees centered on 140 degrees east longitude
5 is adopted as the divided image data 13 at 12 o'clock local time. The other image pieces 21, 22, 23, 24 are
The image pieces 26, 27, and 2 are adopted as the divided image data 13 at the local time of 8:00, 9:00, 10:00, and 11:00, respectively.
8 and 29 are local time 13:00, 14:00, and 15 respectively.
It is adopted as the divided image data 13 at 16:00. However, the image pieces 21 and 29 at both ends are cut out not in the 15 degree width but in the 7.5 degree width.

FIG. 7 shows a process for synthesizing the same local time image data 14 at 12 o'clock local time from the nine physical quantity image data 12 corresponding to the time zone of 23 to 07 UTC. 23UTC, 00UTC, 01UTC, 02UT
C, 03UTC, 04UTC, 05UTC, 06UT
In each of C and 07UTC images,
Image pieces ,,,,,, and correspond to 12:00 local time.

Then, these image pieces are joined together,
The same local time image at 12 o'clock local time is generated. Further, the other remaining image pieces are used to synthesize the same local time image of the corresponding other local time.

The same local time image generated in this way is
In addition to being displayed on the screen for presentation to the user, it can be used for analysis of the time change of physical quantities. Figure 8
Shows processing for creating a difference image from the same local time image for such analysis.

Here, the difference image refers to an image in which the difference in the value of each pixel between two images is calculated and the result is represented again as the value of each pixel. By obtaining a difference image from the same local time image of two different local times for a specific physical quantity, it is possible to express the change of the physical quantity between those times.

In FIG. 8, the analyzer processes, for example, the same local time image data 31 at 12 o'clock local time in July of this year, and monthly average image data 3 representing the average value for one month.
3 is generated (process P11). Similarly, the same local time image data 32 at 12 o'clock local time in July last year is processed to generate monthly average image data 34 (process P1).
1).

Next, subtracting each pixel value of the monthly average image data 34 of July last year from each pixel value of the monthly average image data 33 of July this year, the differential image data 35 is generated (process P12). Then, the difference image data 35 is visualized,
It is displayed on the screen of the monitor or printed using a color printer (process P13).

As described above, the difference image is generated between the same months of two consecutive years and the difference image is visualized to present the user with the distribution of the temporal change of the physical quantity during those two years. be able to. The user can grasp the temporal change of the physical quantity at each point by looking at the visualized difference image.

Although the difference image is visualized and output in FIG. 8, the same local time image itself can be visualized and output in the same manner. in this case,
The user can grasp the distribution status of the physical quantity at each point by looking at the visualized same local time image.

Further, in order to investigate the causal relationship between the environmental information, it is conceivable to create a difference image from the same local time image which is monthly averaged by the method of FIG. 8 for each physical quantity and compare them. According to this comparison method, the influence of the environmental element (for example, the sun altitude) that does not fluctuate year by year in the natural world is removed, and therefore it can be effective when investigating the causal relationship of the environmental elements that influence each other.

FIG. 9 shows an example of analyzing such a causal relationship between environment information. Here, the amount of solar radiation and the sea surface temperature are adopted as comparison targets, and the causal relationship between them is analyzed.

First, the analyzing device first detects the visible sensor (or
From the satellite image data 41 obtained by the infrared 1 and infrared 2 sensors), the solar radiation image data 42 is generated according to the solar radiation estimation model (P21). Then, the solar radiation amount image data 42 is divided by the processing shown in FIG. 2 to generate the same local time image data 43 of the solar radiation amount (P22).

Similarly, the sea surface temperature image data 45 is generated from the satellite image data 44 obtained by the infrared 1 and infrared 2 sensors according to the sea surface temperature estimation model (P2).
3). Then, the sea surface temperature image data 45 is divided to generate the same local time image data 46 of the sea surface temperature (P2).
4).

Next, the same local time image data 4 of the same amount of solar radiation
Of the three, the monthly average is calculated using, for example, the one in the time zone of 10 to 15 o'clock, and the monthly average image data 47 of the amount of solar radiation is generated (P25). Further, among the same local time image data 46 of the sea surface temperature, for example, the one at the time of 12:00 is used to calculate the monthly average, and the monthly average image data 48 of the sea surface temperature is generated (P26).

Then, for each of the amount of solar radiation and the sea surface temperature, the difference image data 49 between the same month of the previous year is generated by the processing shown in FIG. 8 and displayed / printed (P27).

FIG. 10 shows a difference image between the amount of solar radiation and the sea surface temperature displayed in this way. In the sea surface temperature monthly average difference image 51 of FIG. 10, the difference ΔSST between the monthly average of sea surface temperature between this year and last year is displayed. Here, ΔSST in the regions a, b, and c are respectively
2 ° C, 3 ° C and 4 ° C. Further, in the monthly average amount of solar radiation difference image 52, the difference ΔRAD of the monthly average of the amount of solar radiation between this year and last year is displayed. Here, ΔRAD in the regions d, e, and f is 150 W /
m ² , 200 W / m ² and 250 W / m ² .

In these images, when the user designates a specific spot 54 using a pointing device or the like, the environmental information of the spot 54 is automatically displayed in the display area 53. Here, the coordinates of point 54 (x1, y1)
And the values of ΔSST and ΔRAD at point 54 are displayed. As the coordinates (x1, y1), convenient coordinate values on the screen can be displayed, and longitude and latitude can also be displayed.

The user can display the two difference images 5 displayed.
By comparing 1 and 52, it is possible to easily estimate the causal relationship between the temporal change in sea surface temperature and the temporal change in solar radiation. In addition, by designating a point to be compared and displaying the information of the point, it is possible to quickly grasp the environmental information of the point.

In the embodiment described above, one same local time image may be stored in one file,
You may divide and store in several files. However, when performing processing such as monthly average image generation or difference image generation, 1
It is considered that processing as a single file will improve the processing efficiency.

Further, the interval for dividing the physical quantity image does not necessarily have to be 15 degrees, and an arbitrary interval can be used according to the satellite image capturing interval, the time required for image capturing, and the like.

By the way, the above-mentioned analyzing apparatus can be constructed by using an information processing apparatus (computer) as shown in FIG. The information processing apparatus of FIG. 11 has a CPU
A central processing unit 61, a memory 62, an input device 63, an output device 64, an external storage device 65, a medium drive device 66, and a network connection device 67 are provided, which are the bus 6
8 are connected to each other.

The memory 62 is, for example, a ROM (read onl
y memory), RAM (random access memory), etc., and stores programs and data used for processing.
The CPU 61 performs necessary processing by executing the program using the memory 62.

The input device 63 is, for example, a keyboard, a pointing device, a touch panel, etc., and is used for inputting instructions and information from the user. Output device 64
Is, for example, a monitor display, a printer, or the like,
It is used for inquiries to users and for outputting images of processing results.

The external storage device 65 is, for example, a magnetic disk device, an optical disk device, a magneto-optical disk (magneto-op).
tical disk) device. In this external storage device 65,
It is also possible to save the above-mentioned programs and data and load them into the memory 62 for use as needed. In addition, the external storage device 65 stores the satellite image data 11, the physical quantity image data 12, the divided image data 13 in FIG.
Also, it can be used as a database for storing the same local time image data 14, the monthly average image data 33 and 34 of FIG. 8, the difference image data 35, and the like.

The medium driving device 66 drives a portable recording medium 69 to access the recorded contents. Portable recording medium 6
9 is a memory card, floppy disk, CD
-A computer-readable recording medium such as a ROM (compact disk read only memory), an optical disk, a magneto-optical disk, or the like is used. It is also possible to store the above-mentioned program and data in this portable recording medium 69 and load them into the memory 62 for use as needed.

The network connection device 67 is a LAN (lo
It communicates with an external device through an arbitrary network (line) such as a cal area network) and performs data conversion accompanying the communication. Further, if necessary, the above-mentioned program and data can be received from an external device and loaded into the memory 62 for use.

FIG. 12 shows a computer-readable recording medium capable of supplying a program and data to the information processing apparatus of FIG. The programs and data stored in the portable recording medium 69 or the external database 70 are loaded into the memory 62. And the CPU 61
Executes the program using the data and performs the necessary processing.

[0059]

EXAMPLES Currently, an hourly solar radiation image and a sea surface temperature image of a 0.05 degree grid can be created from GMS image data obtained every hour. Therefore, in order to analyze the daily temperature rise process of the wide area ocean at the local time, after dividing the hourly solar radiation image and the sea surface temperature image every 15 degrees in the longitudinal direction, connect the image pieces at the same local time. By the above, the same local time image every hour from 10:00 to 15:00 was created.

Next, monthly average image data for 1997 and 1996 are created using the same local time image from 10:00 to 15:00 regarding the amount of solar radiation, and the 1997 average is obtained from these two monthly average image data. And the difference image between 1996 and 1996 was obtained.

FIG. 13 shows the monthly average difference image of solar radiation in April obtained in this way. In FIG.
The white area indicates that the amount of solar radiation in 1997 is larger than that in 1996, and the black area indicates that the amount of solar radiation in 1996 is larger than that in 1997.

A difference image between 1997 and 1996 was obtained using the same local time image at 12 o'clock local time regarding the sea surface temperature. As a result, the same tendency as the global monthly mean sea surface temperature map of the Japan Meteorological Agency Ocean Monthly Report was obtained. Furthermore, by calculating the difference between the same local time images at the local time of 15:00 and 10:00 regarding the sea surface temperature, and creating an image (SST temperature rise distribution image) that averages the difference monthly, the GMS
The SST temperature rise distribution in the imaging region was obtained.

These data are effective information for investigating the influence of the amount of solar radiation on the temperature rise of the sea surface water temperature, and can be used for the analysis of the causal relationship between the amount of solar radiation and the temperature rise of the sea surface water temperature. .

[0064]

According to the present invention, it is possible to display an image of global environment information such as a temporal change in sea surface temperature and the amount of solar radiation as a single image at approximately the same local time. This allows the user to grasp the distribution status of these environmental information at the local time as a geographically continuous image.

Further, the image data thus obtained can be effective information for analyzing the temporal change of global environmental information such as the estimation of the influence of the amount of solar radiation on the temperature rise of the sea surface temperature. Therefore, these image data can be used in the field of global environment monitoring and various industrial fields related to weather and ocean.

[Brief description of drawings]

FIG. 1 is a principle diagram of an analysis apparatus of the present invention.

FIG. 2 is a diagram illustrating a same local time image creation process.

FIG. 3 is a diagram showing specifications of geostationary satellite image data.

FIG. 4 is a diagram showing a gradation conversion table of physical quantity image data.

FIG. 5 is a diagram showing a relationship between longitude and local time.

FIG. 6 is a diagram showing a method of dividing image data.

FIG. 7 is a diagram showing a method of synthesizing the same local time image.

FIG. 8 is a diagram illustrating a difference image creation process.

FIG. 9 is a diagram showing an example of environmental information analysis.

FIG. 10 is a diagram showing a comparison between sea surface temperature and the amount of solar radiation.

FIG. 11 is a configuration diagram of an information processing device.

FIG. 12 is a diagram showing a recording medium.

FIG. 13 is a diagram showing an example of a solar radiation amount difference image.

[Explanation of symbols]

1 dividing means 2 generating means 3 processing means 4 output means 5 image data 6 divided image data 7 local time images 11, 41, 44 geostationary satellite image data 12, 42, 45 physical quantity image data 13 divided image data by longitude 14, 31, 32, 43, 46 Same local time image data 21, 22, 23, 24, 25, 26, 27, 28, 2
Image pieces 33, 34, 47, 48 Monthly average image data 35, 49, 51, 52 Difference image data 53 Display area 61 CPU 63 Input device 64 Output device 65 External storage device 66 Medium Drive device 67 Network connection device 68 Bus 69 Portable recording medium 70 Database

─────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-11-211560 (JP, A) JP-A 1-277944 (JP, A) (58) Fields investigated (Int.Cl. ⁷ , DB name) G06T 1/00 285

Claims (11)

(57) [Claims] 1. A dividing means for dividing a plurality of pieces of divided image data by dividing the image data obtained at every fixed time in the longitudinal direction at a constant interval, and the divided image data corresponding to the same local time are connected to each other.
An analyzing apparatus comprising: a generation unit that generates a local time image; and an output unit that outputs the local time image. 2. The dividing means divides image data representing the distribution of physical quantities corresponding to global environment information to generate the plurality of divided image data, and the generating means calculates the distribution of physical quantities. The analysis device according to claim 1, wherein the local time image is generated. 3. A dividing unit that divides image data obtained at regular time intervals at a constant interval in the longitudinal direction to generate a plurality of divided image data and connected divided image data corresponding to the same local time,
An analyzing apparatus comprising: a generating unit that generates a local time image; a processing unit that performs image processing using the local time image; and an output unit that outputs a result of the image processing. 4. The analysis apparatus according to claim 3 , wherein the processing means generates a difference image from two local time images, and the output means outputs the difference image. 5. The analysis apparatus according to claim 4 , further comprising a designation unit that designates a position in the difference image, wherein the output unit outputs environment information corresponding to the designated position. Wherein said processing means, said generating a monthly average image from the local time image, said output means, according to claim 3, characterized in that outputs the image information obtained from該月average image
The described analyzer. 7. The generating means generates the local time image for each environmental information to be analyzed, and the processing means generates a monthly average image from each local time image, corresponding to two years. The analysis apparatus according to claim 3 , wherein a difference image is generated from the two monthly average images, and the output unit outputs the difference image for each environment information. 8. The image data obtained every hour is set to 1 in the longitudinal direction.
Dividing at 5 degree intervals and connecting the dividing means for generating a plurality of divided image data and the divided image data corresponding to the same local time,
An analyzing apparatus comprising: a generation unit that generates a local time image; and an output unit that outputs the local time image. 9. A recording medium in which a program for a computer is recorded, wherein image data obtained at fixed time intervals are set at fixed intervals in the longitudinal direction.
In divided and, by joining and splitting means <br/> for generating a plurality of divided image data, the divided image data corresponding to the same local time,
A computer-readable recording medium recording a program for causing the computer to function as a generating unit that generates a local time image. 10. A dividing means divides image data obtained at fixed time intervals in the longitudinal direction at a constant interval to generate a plurality of divided image data, and the generating means corresponds to the same local time. The analysis method is characterized in that the divided image data are combined to generate a local time image, and the processing means performs image processing using the local time image. 11. The generation means generates the local time image for each environmental information to be analyzed, and the processing means performs image processing using each local time image to cause a mutual cause of environmental information. The analysis method according to claim 10 , wherein the relationship is analyzed.