Information processing device, information processing method, and program

Abstract

Provided is an information processing device 1 including a control unit, a communication unit, and a storage unit, wherein the control unit executes an operation including acquiring time-series data of a backscatter coefficient on the basis of data measured by the synthetic aperture radar of an artificial satellite 3 that transmits radio waves to a geographical region, determining the occurrence state of fallen leaves of plants on the basis of the time-series data, and outputting information relating to the occurrence state.

Description

Information processing device, information processing method, and program

[0001] The present disclosure relates to an information processing device, an information processing method, and a program.

[0002] 2. Description of the Related Art Conventionally, a system for detecting the state of leaf fall on trees using an optical sensor on an artificial satellite is known (for example, see Patent Document 1).

[0003] International Publication No. 2022 / 080418

[0004] Rainy tropical regions where rubber plantations are located are often cloudy, making it difficult for satellite optical sensors to assess the vegetation conditions in cloudy areas. Therefore, when attempting to assess the vegetation conditions using optical sensors, observation frequency must be increased. However, when optical sensor data is acquired frequently, the spatial resolution of the resulting images decreases. The spatial resolution of the above-mentioned background art is 500 m.

[0005] The present disclosure has been made in consideration of the above circumstances, and aims to accurately determine the state of leaf abscission in plants.

[0006] An information processing device according to one embodiment of the present disclosure is an information processing device including a control unit, a communication unit, and a memory unit, wherein the control unit performs operations including: acquiring time series data of backscattering coefficients based on data measured by a synthetic aperture radar of a satellite that transmits radio waves to a geographical region; determining the occurrence status of defoliation of plants based on the time series data; and outputting information related to the occurrence status.

[0007] An information processing method according to one embodiment of the present disclosure is an information processing method by an information processing device including a control unit, a communication unit, and a memory unit, and includes: acquiring time series data of backscattering coefficients based on data measured by a synthetic aperture radar of a satellite that transmits radio waves to a geographical region; determining the occurrence status of defoliation of plants based on the time series data; and outputting information related to the occurrence status.

[0008] A program according to an embodiment of the present disclosure is a program for causing a computer to function as an information processing device.

[0009] According to an embodiment of the present disclosure, the state of leaf abscission of a plant can be determined with high accuracy.

[0010] It is a schematic diagram of an information processing system. It is a block diagram showing the configuration of an information processing device. It is a graph showing canopy coverage. It is a graph showing time series data of backscattering coefficient. It is a diagram showing the data structure of a region DB (database). It is a flowchart showing the operation of the information processing device.

[0011] 1 is a schematic diagram of an information processing system S according to this embodiment. The information processing system S includes an information processing device 1, a user terminal 2, and an artificial satellite 3, which are capable of communicating with each other via a network NW. The network NW includes, for example, a mobile communication network, a fixed communication network, or the Internet.

[0012] 1, for ease of explanation, one information processing device 1, one user terminal 2, and one artificial satellite 3 are illustrated. However, the respective numbers of information processing devices 1, user terminals 2, and artificial satellites 3 are not limited to this. For example, the processing executed by the information processing device 1 of this embodiment may be executed by a plurality of information processing devices 1 that are distributed.

[0013] The information processing device 1 is installed in a facility such as a data center, etc. The information processing device 1 is a computer such as a server that belongs to a cloud computing system or other computing system.

[0014] The internal configuration of the information processing device 1 will be described in detail with reference to FIG.

[0015] The information processing device 1 includes a control unit 11, a communication unit 12, and a storage unit 13. The components of the information processing device 1 are connected to each other so as to be able to communicate with each other.

[0016] The control unit 11 includes, for example, one or more general-purpose processors including a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). The control unit 11 may include one or more dedicated processors specialized for specific processing. Instead of including a processor, the control unit 11 may include one or more dedicated circuits. The dedicated circuits may be, for example, an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). The control unit 11 may include an ECU (Electronic Control Unit). The control unit 11 transmits and receives any information via the communication unit 12.

[0017] The communication unit 12 includes a communication module compatible with one or more wired or wireless LAN (Local Area Network) standards for connecting to the network NW. The communication unit 12 may include a module compatible with one or more mobile communication standards including LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation). The communication unit 12 may include a communication module compatible with one or more short-range communication standards or specifications including Bluetooth (registered trademark), AirDrop (registered trademark), IrDA, ZigBee (registered trademark), Felica (registered trademark), or RFID. The communication unit 12 transmits and receives any information via the network NW.

[0018] The memory unit 13 may include, but is not limited to, for example, a semiconductor memory, a magnetic memory, an optical memory, or a combination of at least two of these. The semiconductor memory may be, for example, a RAM or a ROM. The RAM may be, for example, an SRAM or a DRAM. The ROM may be, for example, an EEPROM. The memory unit 13 may function as, for example, a main memory device, an auxiliary memory device, or a cache memory. The memory unit 13 may store information resulting from analysis or processing by the control unit 11. The memory unit 13 may store various information related to the operation or control of the information processing device 1. The memory unit 13 may store system programs, application programs, embedded software, etc. The memory unit 13 may be provided outside the information processing device 1 and may be accessed by the information processing device 1. The memory unit 13 includes an area DB, which will be described later.

[0019] The user terminal 2 may be a mobile device such as a mobile phone, a smartphone, a wearable device, or a tablet. Alternatively, the user terminal 2 may be a general-purpose device such as a PC, or a dedicated device. "PC" is an abbreviation for personal computer.

[0020] The satellite 3 includes a synthetic aperture radar (SAR). The satellite 3 transmits or irradiates radio waves, such as microwaves, from the SAR antenna toward the geographical region R (see Figure 1) to be observed. The geographical region includes plantations such as rubber plantations. The satellite 3 receives electromagnetic energy scattered from the geographical region R using an antenna and measures time-series data of the backscatter coefficient. For example, the backscatter coefficient (dB) of Sentinel-1's C-band SAR (10-m resolution, 12-day period) is used. The backscatter coefficient is analyzed using Google Earth Engine (GEE), a remote sensing and GIS (geographic information system) analysis environment, or SNAP, ENVI, SARscape, ArcGIS, QGIS, or other tools. The SAR frequency of the satellite 3 is not limited to C-band, and X-band or L-band may also be used.

[0021] The artificial satellite 3 includes a synthetic aperture radar, so it can carry out observations day and night, and without being affected by weather such as clouds.

[0022] Four types of polarization can be used for the time-series data of the backscattering coefficient: VV (vertical wave transmission, vertical wave reception), VH (vertical wave transmission, horizontal wave reception), HH (horizontal wave transmission, horizontal wave reception), and HV (horizontal wave transmission, vertical wave reception). Here, the control unit 11 uses VH polarization.

[0023] Either of two types of orbit directions, ascending or descending, can be adopted for the orbit direction of the artificial satellite 3. Here, the control unit 11 uses data for the ascending orbit.

[0024] The processing performed by the information processing system S of this embodiment will be described in detail below.

[0025] The control unit 11 of the information processing device 1 calculates backscattering coefficients from data measured by the synthetic aperture radar of the artificial satellite 3, and acquires time-series data of the backscattering coefficients via the network NW.

[0026] Additionally or alternatively, the control unit 11 may store location information of the geographical area and time series data in the storage unit 13 in association with the geographical area to which the radio waves are transmitted, as shown in FIG. 4 .

[0027] The control unit 11 determines the occurrence of defoliation of plants (here, rubber trees) based on time-series data. A method for determining the occurrence of defoliation will be described with reference to FIGS. 3A and 3B . FIG. 3A is a graph showing canopy coverage based on panoramic photography taken with a fisheye lens. The horizontal axis represents time. The vertical axis represents the percentage of the sky covered by rubber tree leaves when viewed directly upward from the forest floor. FIG. 3B is a graph showing time-series data of backscattering coefficient. The horizontal axis represents time. The vertical axis represents the backscattering coefficient (dB) of Sentinel-1 SAR. In FIG. 3B , the polarization is VH and the observation orbit is ascending. FIGS. 3A and 3B show graphs for the same period. As shown in FIGS. 3A and 3B , periods 31 to 34 when canopy coverage is low (i.e., periods when defoliation occurs) roughly coincide with periods 35 to 38 when the backscattering coefficient increases. Here, even within the same month, the canopy coverage is measured on any one day of the month and displayed on the graph as the value for the first day of the month, while the backscattering coefficient is displayed based on data measured from the beginning to the end of the month. Therefore, please note that periods 31 to 34 may differ from periods 35 to 38. Based on the above, the control unit 11 determines that the period of increase in the backscattering coefficient in the acquired time-series data is the period of defoliation. The defoliation may be either seasonal defoliation or abnormal defoliation due to disease. In this way, the control unit 11 can accurately determine the state of defoliation regardless of the weather or other factors in the geographical area being observed.

[0028] Additionally or alternatively, the occurrence of defoliation may be determined using time series data for one or more other geographical regions of the observed geographical region. Specifically, the control unit 11 may determine that defoliation has occurred in the observed geographical region when it detects that the backscattering coefficient of the observed geographical region has increased compared to the backscattering coefficient of the other one or more geographical regions at a particular time.

[0029] Additionally or alternatively, the occurrence of defoliation may be determined using historical time series data for the observed geographic region. For example, the control unit 11 may determine that defoliation has occurred in the observed geographic region when it detects that the current backscattering coefficient is higher than the backscattering coefficient for the same period in a previous year.

[0030] Additionally or alternatively, the control unit 11 may correct the time series data according to the topography or slope of the geographical area. For example, the control unit 11 may correct the time series data taking into account the influence that the closer the slope to the vertical with respect to the radar irradiation angle, the stronger the reflection, and the closer the slope to the horizontal, the weaker the reflection. Furthermore, the control unit 11 may correct the reflection intensity based on information such as the variety (clone) or age, height, planting spacing, or orientation of the rubber trees planted. Alternatively, the control unit 11 may reduce the geographical evaluation area to reduce the discrepancy between time and location, or may create a location-specific evaluation criterion or model to perform the evaluation.

[0031] Additionally or alternatively, the control unit 11 may determine whether the leaf fall is seasonal or abnormal. Specifically, the control unit 11 may determine the occurrence of abnormal leaf fall based on the deviation rate between reference time series data (i.e., time series data when there is no abnormal leaf fall) and the acquired time series data. Alternatively, the control unit 11 may determine the period of seasonal leaf fall from the reference time series data, and determine leaf fall outside the determined period as abnormal leaf fall.

[0032] As an additional example, the control unit 11 may determine the occurrence of leaf fall using an optical sensor on an artificial satellite in addition to the synthetic aperture radar.

[0033] As an additional example, the control unit 11 may perform machine learning such as deep learning using time series data and the presence or absence of abnormal leaf fall as training data, and determine the leaf fall occurrence status using the constructed learning model.

[0034] As an additional example, the control unit 11 may determine and output the degree of leaf fall based on time-series data.

[0035] As shown in FIG. 4, the control unit 11 stores in the storage unit 13 whether or not leaf fall has occurred in association with the geographical region of the observation target.

[0036] The control unit 11 outputs information regarding the state of leaf fall to the user terminal 2. The information regarding the state of leaf fall may include information indicating whether leaf fall has occurred or not and location information of the location where leaf fall has occurred.

[0037] FIG. 5 illustrates a flowchart of an information processing method performed by the information processing device 1.

[0038] In S1, the control unit 11 acquires time-series data of the backscattering coefficient based on data measured by the synthetic aperture radar of the artificial satellite 3. In S2, the control unit 11 determines the state of leaf fall of plants based on the time-series data. In S3, the control unit 11 outputs information regarding the state of leaf fall.

[0039] In the above-described embodiment, the information processing device preferably further stores location information of the geographical area in association with the time-series data in the storage unit, and outputs location information of the location where defoliation has occurred to the user terminal. This configuration makes it possible to identify the area where defoliation has occurred, making it easier to deal with plant diseases, etc.

[0040] In the above-described embodiment, the occurrence of defoliation is preferably determined using time-series data of one or more other geographical areas, which can improve the accuracy of determining the occurrence of defoliation.

[0041] In the above-described embodiment, the occurrence of defoliation is preferably determined using past time-series data for the geographical area, which can improve the accuracy of determining the occurrence of defoliation.

[0042] In the above-described embodiment, the occurrence of leaf fall is preferably determined using VH polarization, which indicates vertical wave transmission and horizontal wave reception, or HV polarization, which indicates horizontal wave transmission and vertical wave reception. This configuration can improve the accuracy of determining the occurrence of leaf fall. The reason for this is that it is known that when an object with large unevenness, such as a plant, causes the wave reflection direction to become distorted, resulting in relatively strong VH and HV signals.

[0043] In the above-described embodiment, the information processing device preferably further corrects the time-series data in accordance with the topography or slope of the geographical area. This configuration can improve the accuracy of determining the occurrence of defoliation.

[0044] Although the present disclosure will be described based on various drawings and examples, it should be noted that those skilled in the art may make various modifications and alterations based on the present disclosure. Other modifications are possible within the scope of the present disclosure. For example, the functions included in each means or step may be rearranged so as not to cause logical inconsistencies, and multiple means or steps may be combined or divided into one.

[0045] For example, in the above-described embodiment, a program that executes all or part of the functions or processes of the information processing device 1 can be recorded on a computer-readable recording medium. Computer-readable recording media include non-transitory computer-readable media, such as magnetic recording devices, optical discs, magneto-optical recording media, or semiconductor memories. The program can be distributed, for example, by selling, transferring, or lending portable recording media, such as DVDs (Digital Versatile Discs) or CD-ROMs (Compact Disc Read Only Memory) on which the program is recorded. The program can also be distributed by storing the program in the storage of a server and transmitting the program from the server to another computer. The program can also be provided as a program product. The present disclosure can also be realized as a program executable by a processor.

[0046] According to the present disclosure, the state of leaf abscission of plants can be determined with high accuracy.

[0047] [Contribution to the United Nations-led Sustainable Development Goals (SDGs)] The SDGs have been proposed to realize a sustainable society. One embodiment of the present invention is thought to be a technology that can contribute to "No. 8 - Decent Work and Economic Growth" and other goals.

[0048] 1. Information processing device

Claims

1. An information processing device including a control unit, a communication unit, and a memory unit, wherein the control unit performs operations including: acquiring time series data of backscattering coefficient based on data measured by a synthetic aperture radar of a satellite that transmits radio waves to a geographical area; determining the occurrence of defoliation of plants based on the time series data; and outputting information relating to the occurrence status.

2. An information processing device according to claim 1, wherein the operation includes storing location information of the geographical area in association with the time series data in the memory unit, and outputting location information of a location where leaf fall has occurred.

3. An information processing device according to claim 1, wherein the occurrence of said defoliation is determined using time series data of one or more other geographical regions.

4. An information processing device according to claim 1, wherein the occurrence of defoliation is determined using past time-series data for the geographical area.

5. An information processing device according to claim 1, wherein the occurrence of fallen leaves is determined using a VH polarization indicating vertical wave transmission and horizontal wave reception, or an HV polarization indicating horizontal wave transmission and vertical wave reception.

6. An information processing device according to claim 1, wherein the operation includes correcting the time series data in accordance with a topography or a slope of the geographical area.

7. An information processing method by an information processing device including a control unit, a communication unit, and a memory unit, comprising: acquiring time series data of backscattering coefficient based on data measured by a synthetic aperture radar of an artificial satellite that transmits radio waves to a geographical area; determining the occurrence of defoliation of plants based on the time series data; and outputting information relating to the occurrence status.

8. A program for causing a computer to function as the information processing device according to claim 1.

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