Control device, control method, and control program

Abstract

A control device (1) is provided with a satellite image analysis part (11) that extracts, from past satellite images, a first observation candidate region in which the variation in pixel values is equal to or lower than a given level; a weather information analysis part (12) that extracts, from past weather information, a second observation candidate region in which, for example, a prescribed weather phenomenon occurred at a given frequency or more; and an observation path setting part (13) that sets an observation path for a platform, by using the first observation candidate region and the second observation candidate region. When there is a positional difference between a prediction region for which an extreme weather is predicted and an observation region based on the observation path for the platform, the observation path setting part (13) compares a first time period taken until the platform passes over the prediction region along the observation path and a second time period which is required for the platform after the first time period to be moved to the prediction region along the shortest distance, and changes, only when the second time period is equal to or longer than the first time period, the observation path so as to move the platform from the present position to the prediction region along the shortest distance.

Description

[Technical Field]

[0001] The present invention relates to a control device, a control method, and a control program. [Background technology]

[0002] Many of the sensors installed on satellites observe the emission and reflection of electromagnetic waves from the atmosphere surrounding the Earth, the earth's surface, the sea surface, etc. Using electromagnetic wave observation data, a variety of observations can be carried out frequently and with high spatial resolution. In the field of weather forecasting, satellites such as Himawari can now frequently obtain a variety of meteorological data on the atmosphere and sea areas, contributing to improving the accuracy of weather forecasts.

[0003] In this regard, although it is now possible to obtain remote sensing data with high spatial and temporal resolution over a wide area, this merely observes electromagnetic waves, and does not actually measure the physical quantities or conditions of the object being measured. Therefore, research and development is being conducted on models that convert electromagnetic wave observation data into values that we want to understand. In particular, in the field of weather forecasting, data assimilation is a technology that is currently being developed as a complementary link between observations and numerical models. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2015-1891 A Summary of the Invention [Problem to be solved by the invention]

[0005] When observing from a remote location, such as a satellite, noise caused by changes in the natural environment is included in the electromagnetic wave observation data, and applying that observation data directly to a model does not result in sufficient accuracy. Therefore, calibration of the observation data before applying the model becomes an issue. Calibration is a correction process that removes electromagnetic waves reflected and emitted from sources other than the object being measured, and is performed using actual measurement data of the reflection and emission from the object.

[0006] Furthermore, while data from permanent observation points such as AMeDAS and Argo floats can be used for data assimilation, there is also the issue of a lack of actual measurement data to improve simulation accuracy.

[0007] Thus, there is a demand for actual measurement data that meets requirements such as spatiotemporal resolution for calibration and simulation.

[0008] In this regard, aerial drone and underwater drone technologies have begun to be used as highly flexible platforms for observing actual measurement data (Patent Document 1). However, their main purpose is to analyze the actual measurement data itself, and they are not intended to obtain actual measurement data for calibration or simulation.

[0009] Furthermore, when observing extreme phenomena (such as typhoons) that occur locally in different areas each time as a simulation target, it is necessary to dynamically adapt the observation route to match the weather forecast of that extreme phenomenon.Furthermore, in addition to the data to be assimilated as input, actual measurement data is also required to evaluate the accuracy of the results of the data assimilation and prediction.

[0010] The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a technique that enables dynamic observation of the acquisition of actual measurement data suitable for calibration and simulation. [Means for solving the problem]

[0011] A control device of one embodiment of the present invention is a control device that controls the observation route of a dynamic platform that observes actual measurement data, and includes: an analysis unit that extracts a first observation candidate area for the actual measurement data for calibration, where the pixel value fluctuation is below a certain level from past satellite images; an analysis unit that extracts a second observation candidate area for the actual measurement data for simulation, where the occurrence frequency or passage frequency of a specified weather phenomenon is above a certain level from past weather information; and a setting unit that sets the observation route of the platform using the first observation candidate area and the second observation candidate area.If there is a positional difference between the predicted area of extreme weather that is forecast to change from moment to moment and the observation area based on the observation route, during the occurrence of the extreme weather, the setting unit compares a first time required for the platform to pass the predicted area on the observation route with a second time required to travel the shortest distance from the platform to the predicted area after the first time has elapsed, and only if the second time is equal to or greater than the first time, changes the observation route related to the actual measurement data for simulation so as to move the platform to the predicted area the shortest distance from its current position.

[0012] In one embodiment of the control method of the present invention, a control device controls the observation path of a dynamic platform that observes actual measurement data, and the control device performs the following steps: for the actual measurement data for calibration, extracting a first observation candidate area from past satellite images where the pixel value fluctuation is below a certain level; for the actual measurement data for simulation, extracting a second observation candidate area from past weather information where the occurrence frequency or passage frequency of a predetermined weather phenomenon is above a certain level; setting the observation path of the platform using the first observation candidate area and the second observation candidate area; and, if there is a positional difference between a predicted area of extreme weather that changes from moment to moment as predicted by weather forecasts and an observation area based on the observation path, comparing a first time required for the platform to pass the predicted area on the observation path during the occurrence of the extreme weather with a second time required to travel the shortest distance from the platform to the predicted area after the first time has elapsed, and only if the second time is equal to or greater than the first time, changing the observation path related to the actual measurement data for simulation so as to move the platform to the predicted area by the shortest distance from its current position.

[0013] A control program according to one aspect of the present invention causes a computer to function as the control device. [Effects of the Invention]

[0014] According to the present invention, it is possible to provide a technique that enables dynamic observation of the acquisition of actual measurement data suitable for calibration and simulation. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram showing the overall configuration of the observation route control system. [Figure 2] FIG. 2 is a diagram showing the overall implementation procedure. [Figure 3] FIG. 3 is a diagram showing a specific example of the implementation procedure. [Figure 4] FIG. 4 is a diagram showing a specific example of the implementation procedure. [Figure 5]FIG. 5 is a diagram showing a specific example of the stability of each pixel. [Figure 6] FIG. 6 is a diagram showing a specific example of weather information. [Figure 7] FIG. 7 is a diagram showing specific examples of the frequency of occurrence of extreme weather events in each region. [Figure 8] FIG. 8 is a diagram showing a specific example of the starting point of an observation route. [Figure 9] FIG. 9 is a diagram showing a specific example of the dynamic cost. [Figure 10] FIG. 10 is a diagram showing an example of changing the observation route based on a weather forecast. [Figure 11] FIG. 11 is a diagram showing an example of setting a new observation route based on the current weather conditions. [Figure 12] FIG. 12 is a diagram showing an example of setting a new observation route based on the current weather conditions. [Figure 13] FIG. 13 is a diagram illustrating a hardware configuration of the control device. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the description of the drawings, the same parts are designated by the same reference numerals and the description thereof will be omitted.

[0017] [overview] The present invention discloses a technology for controlling the observation path of a platform that observes actual measurement data in order to efficiently and effectively obtain actual measurement data for calibrating input data or embedding it into simulations in various simulations that use wide-area remote sensing data such as satellite images.

[0018] As mentioned above, observation of actual data is being carried out using platforms such as aerial drones and underwater drones. However, the main purpose is to analyze the actual data itself, not to obtain actual data for calibration or simulation, and it is not possible to flexibly change the observation route to match uncertain weather forecasts.

[0019] Therefore, in this invention, the observation route is controlled to carry out efficient and effective observation while adapting the pre-planned observation route to the weather forecast as needed. In other words, for uncertain weather phenomena predicted by the weather forecast, the optimal observation route for the platform is set in real time based on the priority according to the required travel time to the uncertain weather phenomenon, according to the lead time of the weather forecast.

[0020] This enables sensing that takes into account ever-changing weather conditions, dynamically observes the acquisition of measured data suitable for calibration and simulation, and acquires the measured data necessary for highly accurate data assimilation. It also reduces the operational costs of measuring measured data, increases the reliability of calibration, and improves the accuracy of simulation results.

[0021] [Overall configuration of the observation path control system] 1 is a diagram showing the overall configuration of an observation route control system according to this embodiment. The control system includes a control device 1, an observation platform 2, a satellite information management device 3, a weather information management device 4, and a client terminal 5.

[0022] The observation platform 2 is a dynamic platform for observing actual measurement data, such as an aerial drone or an underwater drone.

[0023] The satellite information management device 3 is a device that manages satellite information.

[0024] The weather information management device 4 is a device that manages weather information.

[0025] The client terminal 5 is a client device of a user who operates the control device 1.

[0026] The control device 1 is a server device that controls the observation route of the observation platform 2. The control device 1 is connected to the observation platform 2, satellite information management device 3, weather information management device 4, and client terminal 5 via a communication network 6 such as a wired network or a wireless network so that they can communicate with each other.

[0027] The control device 1 includes a control unit 10 and a storage unit 20. The control unit 10 includes a satellite image analysis unit 11, a weather information analysis unit 12, an observation route setting unit 13, an actual measurement data analysis unit 14, and an operation monitoring unit 15. The storage unit 20 includes a satellite image storage unit 21, a weather information storage unit 22, an observation route storage unit 23, and an actual measurement data storage unit 24.

[0028] The satellite image analysis unit (analysis unit) 11 has a function of analyzing a first observation candidate area for observing actual measurement data for calibration from past satellite images. Specifically, the satellite image analysis unit 11 has a function of reading past data of the satellite image to be calibrated from the satellite image storage unit 21, extracting a stable area in the satellite image where pixel values are stable and the fluctuation of pixel values is below a certain level, and storing the stable area in the observation route storage unit 23 as a first observation candidate area.

[0029] The weather information analysis unit (analysis unit) 12 has a function of analyzing a second observation candidate area for observing actual measurement data for simulation from past weather information. Specifically, the weather information analysis unit 12 has a function of reading past data of weather information to be simulated from the weather information accumulation unit 22, extracting unstable areas in the weather information where the occurrence frequency or passage frequency of a predetermined weather phenomenon (extreme weather) is higher than a certain level, and storing the unstable areas in the observation route accumulation unit 23 as second observation candidate areas.

[0030] The observation route setting unit (setting unit) 13 has the function of using the first observation candidate area extracted by the satellite image analysis unit 11 and the second observation candidate area extracted by the weather information analysis unit 12 to select (set) an observation route and observation area, taking into consideration the takeoff and landing positions and movement speed of the observation platform 2, formulating an observation plan for observing the observation route and observation area, and storing the observation plan in the observation route storage unit 23.

[0031] In addition, the observation route setting unit 13 has the function of modifying the observation plan based on the provided weather forecast when an externally predicted and announced weather forecast for extreme weather is provided while observation is being carried out on the observation platform 2 based on the observation plan, and storing the modified observation plan in the observation route storage unit 23 if there is a locational difference between the ever-changing predicted area of extreme weather and the observation area of the observation plan.

[0032] Specifically, if there is the above-mentioned difference, the observation route setting unit 13 compares a first time required for the observation platform 2 to pass through the predicted area of extreme weather on the observation route of the observation plan during the occurrence of extreme weather with a second time required to travel the shortest distance from the observation platform 2 to the predicted area of extreme weather after the first time has passed, and changes the observation route related to the actual measurement data for the simulation so that the observation platform 2 moves the shortest distance from its current position to the predicted area of extreme weather only if the second time is longer than the first time.

[0033] In addition, the observation route setting unit 13 has the function of acquiring the actual weather conditions reported externally after the weather phenomenon (extreme weather) in the above-mentioned weather forecast has ended or after the observation platform 2 has passed through the weather phenomenon (extreme weather) in the above-mentioned weather forecast, formulating a new observation plan based on the acquired actual weather conditions, and storing the new observation plan in the observation route storage unit 23.

[0034] The measurement data analysis unit 14 has the function of reading the measurement data that is sequentially transmitted from the observation platform 2 and stored in the measurement data storage unit 24, checking the quality of the measurement data, and if there is an area where the quality is insufficient, storing that area in the observation route storage unit 23 as a candidate for a re-observation area.

[0035] The operation monitoring unit 15 has a function to display on a screen the current position of the observation platform 2, the observation route, the observation area, the actual measurement data, the quality of the actual measurement data, weather information, etc. The operation monitoring unit 15 also has a function to send a change control signal to the observation platform 2 when there is a change in the observation route.

[0036] The satellite image storage unit 21 has a function of acquiring satellite information and satellite images from the satellite information management device 3 and storing the satellite information and satellite images.

[0037] The weather information storage unit 22 has a function of acquiring weather information and weather images from the weather information management device 4 and storing the weather information and weather images.

[0038] The observation route storage unit 23 has the function of storing a first observation candidate area, a second observation candidate area, an observation plan including an observation route and an observation area, a changed observation plan including a changed observation route and observation area, a new observation plan including a new observation route and observation area, a re-observation candidate area, etc.

[0039] The measured data storage unit 24 has a function of storing the position information and measured data successively transmitted from the observation platform 2.

[0040] [Overall implementation procedure] FIG. 2 is a diagram showing the overall implementation procedure.

[0041] Step S1; The control device 1 formulates an observation plan (including observation routes and observation areas) based on past statistical data and weather forecasts. For calibration, it is based on stable areas with statistically little weather fluctuation. For simulation, it is based on unstable areas identified from areas with a high frequency of past weather information and weather phenomena that contribute to improving accuracy. The observation plan is formulated based on stable and unstable areas. Before extreme weather occurs, the observation platform 2 observes actual measurement data based on the observation plan.

[0042] Step S2; When a weather forecast of extreme weather (strong winds, torrential rain, etc.) is provided and there is a locational difference between the predicted area of the extreme weather and the observation area, the control device 1 changes the observation plan for the measured data for simulation. For example, the control device 1 takes into account the lead time of the weather forecast (extreme weather) and reconfigures the route using the position and movement speed of the observation platform 2 and the predicted location of the extreme weather that changes from moment to moment so that the measured data for calibration and the measured data for simulation can be acquired efficiently and effectively.

[0043] Step S3; The control device 1 formulates a new observation plan for acquiring data for calibration and accuracy evaluation of simulation results based on the actual weather conditions after the extreme weather event has ended or after the extreme weather event has passed over the observation platform 2. Because changes due to weather phenomena are also important for comparing simulation results of weather phenomena, the location of the weather phenomenon is identified and acquired from actual values rather than predicted values.

[0044] [Specific example of implementation procedure] 3 and 4 are diagrams showing specific examples of implementation procedures.

[0045] Steps S101, S102; The satellite image analysis unit 11 reads out past data of the satellite image to be calibrated from the satellite image storage unit 21, extracts stable areas in the satellite image where pixel values are stable, stores the stable areas in the observation route storage unit 23 as the first observation candidate area, and transmits a request for development of an observation plan including the first observation candidate area to the observation route setting unit 13.

[0046] Steps S103, S104; The weather information analysis unit 12 reads out past weather information data for the simulation target from the weather information storage unit 22, extracts unstable areas within the weather information where a specified weather phenomenon (extreme weather) has a high frequency of occurrence or passage, stores the unstable areas as second observation candidate areas in the observation route storage unit 23, and sends a request to develop an observation plan including the second observation candidate area to the observation route setting unit 13.

[0047] Step S105; The observation route setting unit 13 uses the first observation candidate area extracted in step S101 and the second observation candidate area extracted in step S103 to select an observation route and observation area, taking into consideration the takeoff and landing positions and movement speed of the observation platform 2, and formulates an observation plan for observing the observation route and observation area, and stores it in the observation route storage unit 23.

[0048] Steps S106 to S109; After starting operation, the observation platform 2 reads the observation plan from the observation route storage unit 23, observes actual measurement data along the observation route in the observation area of the observation plan, associates the actual measurement data with the position information of the observation platform 2, and stores them in the actual measurement data storage unit 24. The observation platform 2 sequentially transmits its own position information to the operation monitoring unit 15, and sequentially transmits the actual measurement data to the actual measurement data analysis unit 14.

[0049] Step S110; The operation monitoring unit 15 creates an actual observation route based on the position information of the observation platform 2 sequentially transmitted from the observation platform 2, and stores the actual observation route in the observation route storage unit 23.

[0050] Step S111; If a weather forecast of extreme weather is provided during observation at the observation platform 2 and there is a large locational difference between the ever-changing predicted area of the extreme weather and the observation area of the observation plan, the observation route setting unit 13 determines that the observation route related to the measured data for simulation has been changed. Then, the process proceeds to step S113. On the other hand, if a weather forecast of extreme weather is provided but there is only a small locational difference between the predicted area and the observation area of the observation plan, the observation route setting unit 13 determines that the observation route has not been changed. Then, the process proceeds to step S114.

[0051] Step S112; The measurement data analysis unit 14 checks the quality of the measurement data sequentially transmitted from the observation platform 2, and if there is an area where the quality is insufficient, it sets that area as a candidate for a re-observation area and determines that the observation route has been changed. Then, the process proceeds to step S113.

[0052] Step S113; If the operation monitoring unit 15 determines in step S111 that the observation route has been changed, it transmits a change control signal to change the observation route to the observation platform 2. If the operation monitoring unit 15 determines in step S112 that the observation route has been changed, it transmits a change control signal to the observation platform 2 to include the re-observation area candidate in the observation route. The observation platform 2 observes the actual measurement data based on the observation route changed based on the change control signal.

[0053] Step S114; If the observation route setting unit 13 determines in step S111 that the observation route has not been changed, after the extreme event that has occurred has ended or after the observation platform 2 has passed through the extreme event, it sends a repetition end notification to the observation platform 2 to end the repeated observation of the actual measurement data, and proceeds to step S116.

[0054] Step S115; After repeatedly receiving the end notification, the observation platform 2 ends the observation of the actual measurement data.

[0055] Steps S116, S117; The observation route setting unit 13 acquires externally reported weather conditions and extracts observation point candidates based on the acquired weather conditions. The observation route setting unit 13 then formulates a new observation plan to observe the extracted observation point candidates, stores it in the observation route accumulation unit 23, and transmits an observation change notification based on the new observation plan to the operation monitoring unit 15.

[0056] Steps S118, S119; Upon receiving the observation change notification, the operation monitoring unit 15 refers to the new observation plan stored in the observation route storage unit 23 and sends a change control signal to the observation platform 2 to change the observation route to the observation route of the new observation plan.

[0057] Steps S120 to S122; When the observation platform 2 receives the change control signal, it reads the new observation plan from the observation route storage unit 23, observes the actual measurement data along the new observation route in the observation area of the new observation plan, associates the actual measurement data with the position information of the observation platform 2, and stores them in the actual measurement data storage unit 24. The observation platform 2 sequentially transmits its own position information to the operation monitoring unit 15, and sequentially transmits the actual measurement data to the actual measurement data analysis unit 14.

[0058] Step S123; The operation monitoring unit 15 creates an actual observation route based on the position information of the observation platform 2 sequentially transmitted from the observation platform 2, and stores the actual observation route in the observation route storage unit 23.

[0059] Step S124; The measurement data analysis unit 14 checks the quality of the measurement data sequentially transmitted from the observation platform 2, and if there is an area where the quality is insufficient, it sets that area as a candidate for a re-observation area and determines that the observation route has been changed. Then, the process proceeds to step S124.

[0060] Step S125; If it is determined in step S124 that the observation route has been changed, the operation monitoring unit 15 transmits a change control signal to the observation platform 2 to include the re-observation area candidate in the new observation route. The observation platform 2 observes the actual measurement data based on the observation route changed based on the change control signal.

[0061] Step S126; The operation monitoring unit 15 checks the position information successively transmitted from the observation platform 2 along the new observation route, and when the observation platform 2 is located at the final position of the observation route, it sends a repetition end notification to the observation platform 2 to end the repeated observation of the actual measurement data.

[0062] Steps S127, S128; After repeatedly receiving the termination notice, the observation platform 2 terminates the observation of the actual measurement data and ends the operation.

[0063] The control device 1 can execute the processes of steps S107 to S115 every time it acquires weather forecast information. The control device 1 can execute the processes of steps S116 to S127 every time it acquires current weather information. The control device 1 repeats the processes of steps S107 to S115 and steps S116 to S127 every time it acquires weather forecast information and current weather information, and can switch between each process at the optimal timing to plan (change or re-plan) an observation route.

[0064] [Specific processing example of the satellite image analysis unit] As described above, the satellite image analysis unit 11 extracts a stable area in the satellite image where pixel values are stable as a first observation candidate area.

[0065] A stable pixel value means that the spatial and temporal variations of the pixel of interest are small. Spatial variation is the difference in pixel value between the pixel of interest and the eight surrounding pixels. Temporal variation is the variation of the pixel of interest over time.

[0066] In order to evaluate both spatial and temporal variations in a balanced manner, the satellite image analysis unit 11 calculates the stability S of each pixel using equation (1), assuming that the pixel value of pixel (x, y) at time t is F(x, y, t).

[0067]

number

[0068] i is the position of the pixel on the x-axis. j is the position of the pixel on the y-axis. k is the time. i, j, k = -1, 0, 1, and i = j = k = other than 0. The smaller the value of stability S calculated by equation (1), the smaller the pixel's fluctuation and stability. The satellite image analysis unit 11 prioritizes pixels with small values of stability S as observation candidate areas, and stores these observation candidate areas in the observation route accumulation unit 23.

[0069] Note that all areas (x, y) and all times t included in the satellite image may be targeted, or may be limited to a specific space or time range. Time t may also be limited to a specific season or a specific observation time. Here, the stability of each pixel is expressed as S1, S2, S3, ... in ascending order of the stability S value (= ascending order of stability) (see Figure 5).

[0070] [Specific processing example of the weather information analysis unit] As described above, the weather information analysis unit 12 determines an unstable area in the weather information where extreme weather events occur frequently or pass frequently as a second observation candidate area.

[0071] For example, the weather information analysis unit 12 calculates the occurrence frequency of extreme weather events, etc., for the entire weather information area shown in Figure 6, limited to a predetermined observable area, taking into account restrictions such as travel distance and territorial waters. The unit of the area for calculating the occurrence frequency, etc., is roughly set to a unit that matches the mesh of the data assimilation model. The weather information analysis unit 12 determines the candidate observation areas in descending order of frequency, and stores these candidate observation areas in the observation route accumulation unit 23. Here, the frequency of each area is expressed as H1, H2, H3, ... in descending order of frequency (see Figure 7).

[0072] [Specific processing example of the observation route setting section] (Development of observation plans) As described above, the observation route setting unit 13 sets an observation route using the first observation candidate area and the second observation candidate area, taking into consideration the takeoff and landing positions and movement speed of the observation platform 2. When setting the observation route, in order to observe meteorological phenomena, the route is positioned to give priority to extreme weather events with a high frequency of occurrence or passage (frequency in the second observation candidate area).

[0073] For example, in order to locate the points closer to the frequency H, the observation path setting unit 13 obtains points HG1, HG2, and HG3 by dividing the distance from each region (vertex) H1, H2, and H3 to the center of gravity G1 by the reciprocal of the frequency, as shown in FIG. 8, and then determines the center of gravity G2 of the figure connecting the points HG1, HG2, and HG3 as the location to be located.

[0074] The center of gravity G1(xg1,yg1) of the triangle with vertices H1(x1,y1), H2(x2,y2), and H3(x3,y3) can be calculated using equations (2) and (3).

[0075]

number

[0076] When the frequency of vertex H1 is f1, HF1(xf1, yf1) is the point that divides the line connecting vertex H1 and center of gravity G1 internally at 1:(f1-1), and can be calculated using equations (4) and (5). HF2(xf2, yf2) and HF3(xf3, yf3) can be calculated in the same way.

[0077]

number

[0078] The center of gravity G2(xg2, yg2) is calculated using equations (6) and (7).

[0079]

number

[0080] The observation route setting unit 13 sets up an observation route that starts from the center of gravity G2 and connects pixels (pixels in the first observation candidate area) in order of stability. For example, it sets up an observation route such as G2 → S1 → S2 → S3 → ... → G2.

[0081] On the other hand, since the travel distance of the observation platform 2 is proportional to the travel time, it is also important to set the observation route efficiently while taking priority into consideration. Therefore, as shown in Figure 9, the observation route setting unit 13 can estimate the dynamic cost C of travel from the center of gravity G2 to each pixel and set the route based on that dynamic cost.

[0082] For example, the observation path setting unit 13 may calculate a dynamic cost C (= d × S) by multiplying the physical distance d from the center of gravity G2 to each pixel by the stability S of each pixel, and then set an observation path selectively from the pixel with the smallest dynamic cost. In this case, to standardize the stability, a dynamic cost C (= d × S / S') based on the value obtained by dividing the stability S of each pixel by the average value S' of S may be used. When determining the next destination from the start point of a movement, the observation path setting unit 13 calculates the above movement costs for all unobserved points and selects the smallest one to set the observation path.

[0083] (Changes in observation route based on weather forecasts) As described above, the observation route setting unit 13 is provided with an externally predicted and announced weather forecast for extreme weather, and if there is a locational difference between the ever-changing predicted area of extreme weather and the observation area of the observation plan, the observation route setting unit 13 changes the observation plan based on the provided weather forecast.

[0084] For example, assume that the observation platform 2 is predicted to pass through a predicted extreme weather region R1 on its current observation route in time T. In other words, the observation platform 2 needs to move into the predicted region R after time T (first time).

[0085] At this time, as shown in FIG. 10, the observation route setting unit 13 calculates the shortest distance between the position of the observation platform 2 after time T and the predicted region R1, and calculates the travel time T required to travel that shortest distance. move (second time) is calculated.

[0086] Then, the observation path setting unit 13 determines whether T≦T move In the case of T ≦ T , the observation route is changed so that the observation platform 2 moves from the current position to within the predicted region R1 in the shortest distance. move In other cases, the observation route setting unit 13 calculates the travel time T move Calculate the travel time T move Compare with the above T, and T≦T mov e The process is repeated until T≦T move If this is no longer the case, the observation route is changed so as to move to the prediction region R1.

[0087] Since the weather forecast of extreme weather is updated from time to time, the observation route setting unit 13 sets the forecast area R of the extreme weather, the time T, and the travel time T min At this time, if the current weather area R2 is approaching, the shortest distance to the current weather area R2 is also calculated.

[0088] (New observation route based on current weather conditions) As described above, after the extreme weather event has ended or the observation platform 2 has passed through the extreme weather event, the observation route setting unit 13 acquires the actual weather information reported externally and formulates a new observation plan based on the acquired actual weather information. Note that the accuracy of the weather forecast and the actual weather information increases and they become closer as they approach a certain area (as the number of days until arrival decreases).

[0089] As shown in Figure 11, when the observation platform 2 is in a predicted area R1 of extreme weather, the observation route setting unit 13 calculates the shortest distance between the predicted area R1 and the actual weather area R2, and formulates an observation route so that the observation platform 2 moves along this shortest distance. At this time, since the weather forecast and actual weather are updated from time to time, the observation route setting unit 13 updates the predicted area R1 and the actual weather area R2 with each update and calculates the shortest distance. After the observation platform 2 reaches the actual weather area R2, an observation plan is formulated to retrace the progress of the actual weather area R2 in reverse.

[0090] 12, if the observation platform 2 is not within the predicted area R1, the observation route setting unit 13 finds the shortest distances between the predicted area R1 and the actual area R2, and calculates the travel times T1 and T2. Next, if the time required for the observation platform 2 to move from its current position to the next pre-planned observation point is Ts, when T1 > T2 or Ts > T2, the pre-planned observation is interrupted and the observation platform 2 is moved to the predicted area R1.

[0091] [Example of processing by the actual measurement data analysis unit] As described above, the measurement data analysis unit 14 checks the quality of the measurement data measured by the observation platform 2, and if there is an area where the quality is insufficient, it designates that observation area as a candidate for a re-observation area. For example, the measurement data analysis unit 14 determines that the quality is insufficient if there are missing values in some of the items to be observed, if the observed values contain a lot of noise, or if the observation position has shifted from the planned observation position due to the influence of waves or wind.

[0092] [effect] According to this embodiment, the control device 1 that controls the observation route of a dynamic platform that observes actual measurement data includes a satellite image analysis unit 11 that extracts, for actual measurement data for calibration, a first observation candidate area where the pixel value fluctuation is below a certain level from past satellite images, a weather information analysis unit 12 that extracts, for actual measurement data for simulation, a second observation candidate area where the occurrence frequency or passage frequency of a predetermined weather phenomenon is above a certain level from past weather information, and an observation route setting unit 13 that sets the observation route of the platform using the first observation candidate area and the second observation candidate area, and the observation route setting unit 13 compares a predicted area of extreme weather that changes from moment to moment in a weather forecast with an observation area based on the observation route. If there is a locational difference between the two, during the occurrence of the extreme weather, a first time it takes for the platform to pass through the prediction area on the observation path is compared with a second time required to travel the shortest distance from the platform to the prediction area after the first time has elapsed, and only if the second time is equal to or greater than the first time, the observation path related to the measured data for simulation is changed so that the platform moves to the prediction area the shortest distance from its current position. This enables sensing to be performed taking into account constantly changing weather conditions, enables dynamic observation of the acquisition of measured data suitable for calibration and simulation, and enables the acquisition of measured data necessary for highly accurate data assimilation. It also reduces the cost of processing measured data, increases the reliability of calibration, and improves the accuracy of simulation results.

[0093] [others] The present invention is not limited to the above-described embodiment, and various modifications are possible within the scope of the present invention.

[0094] The control device 1 of the present embodiment described above can be realized, for example, by using a general-purpose computer system including a CPU 901, a memory 902, a storage 903, a communication device 904, an input device 905, and an output device 906, as shown in Fig. 13. The memory 902 and the storage 903 are storage devices. In the computer system, the CPU 901 executes a predetermined program loaded onto the memory 902, thereby realizing each function of the control device 1.

[0095] The control device 1 may be implemented by one computer. The control device 1 may be implemented by multiple computers. The control device 1 may be a virtual machine implemented on a computer. The program for the control device 1 may be stored in a computer-readable recording medium such as an HDD, SSD, USB memory, CD, or DVD. The program for the control device 1 may also be distributed via a communication network. [Explanation of symbols]

[0096] 1: Control device 2: Observation platform 3:Satellite information management device 4: Weather information management device 5: Client terminal 10: Control unit 11: Satellite Image Analysis Department 12: Weather Information Analysis Department 13: Observation path setting section 14: Measurement data analysis section 15: Flight Monitoring Department 20: Memory unit 21: Satellite image storage unit 22: Weather information storage unit 23: Observation path storage unit 24: Measurement data storage unit

Claims

1. A control device for controlling an observation path of a dynamic platform that observes actual measurement data, an analysis unit that extracts a first observation candidate area in which pixel value fluctuations are equal to or less than a certain value from past satellite images for the actual measurement data for calibration; an analysis unit that extracts a second observation candidate area in which a predetermined weather phenomenon occurs or passes through at a certain frequency or more from past weather information for the actual measurement data for the simulation; a setting unit that sets an observation route for the platform using the first observation candidate area and the second observation candidate area, The setting unit When there is a locational difference between the predicted area of ever-changing extreme weather predicted by weather forecasts and the observation area based on the observation route, a control device compares a first time required for the platform to pass through the predicted area on the observation route during the occurrence of the extreme weather with a second time required to travel the shortest distance from the platform to the predicted area after the first time has elapsed, and changes the observation route related to the actual measurement data for simulation so as to move the platform to the predicted area the shortest distance from its current position only if the second time is equal to or greater than the first time.

2. The setting unit The control device according to claim 1 , wherein after the extreme weather event has ended or passed, the observation route is newly set based on actual weather conditions that are reported after the extreme weather event has ended or passed.

3. A control method for controlling an observation path of a dynamic platform that observes actual measurement data, comprising: The control device extracting a first observation candidate area from past satellite images for actual measurement data for calibration, the first observation candidate area having pixel value fluctuations less than a certain level; extracting a second observation candidate area in which a predetermined weather phenomenon occurs or passes through at a certain frequency or more from past weather information for the actual measurement data for simulation; setting an observation route for the platform using the first observation candidate area and the second observation candidate area; When there is a location difference between a predicted area of ever-changing extreme weather predicted by weather forecasts and an observation area based on the observation route, during the occurrence of the extreme weather, a first time taken for the platform to pass through the predicted area on the observation route is compared with a second time required to travel the shortest distance from the platform to the predicted area after the first time has elapsed, and only if the second time is equal to or longer than the first time, an observation route related to the actual measurement data for simulation is changed so as to move the platform from its current position to the predicted area by the shortest distance; A control method for performing the above.

4. A control program that causes a computer to function as the control device according to claim 1 or 2.

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