• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    System of automatic valuation of damages produced by meteorological risks in crops and infrastructures, which includes: - an interface (10) for selecting geographical location (l) and meteorological risk (r); - an observation module (12) to obtain meteorological data (m) and cartographic information (c) of the geographical location (l) including type of crop or infrastructure; - a risk assessment module (14) to estimate, based on the meteorological data (m), the risk levels (nr) associated with the geographical location (l); - a damage assessment module (16) to estimate, according to the risk levels (nr) and the cartographic information (c), the damage assessment (d) in the crops and/or infrastructures of each selected location (l), classifying the damages in different levels; - a representation module (18) to represent the risk levels (nr) and damage assessment (d) in an associated cartographic database. The observation module allows the incorporation of data contributed by an unmanned aerial vehicle or by a meteorological observer. (Machine-translation by Google Translate, not legally binding)
    公开号:ES2572534A1
    申请号:ES201630037
    申请日:2016-01-15
    公开日:2016-06-01
    发明作者:Laura LÓPEZ CAMPANO；Andrés MERINO SUANCES；José Luis SÁNCHEZ GÓMEZ；Eduardo GARCÍA ORTEGA
    申请人:Universidad de Leon；
    IPC主号:
    专利说明:

    Field of the Invention The present invention falls within the sectors of meteorology, agrometeorological risks and risk prevention and insurance.
    Background of the invention At present, in the matter of meteorological observation and prediction, one of the applications most demanded by risk managers is to know in a quasi-real way where damage to crops or infrastructure caused by meteorological risks is occurring. The damage estimation or appraisal process is not carried out in a manner
    15 automatic, but it is necessary to evaluate them in situ so this system is slow and has a high cost. On the other hand, climate change is changing both the frequency and intensity patterns of some extreme weather events. The process of adaptation to climate change must include a system for detecting and monitoring meteorological risks that allows information and alerts to be displayed on
    20 real time.
    However, there is currently no method or system that allows the assessment of agrometeorological damages or infrastructures in real time and without the need for an appraiser to review damaged farms or infrastructures in situ. Similarly, there is no system
    25 that allows the phenological identification of the crops, except for the on-site examination. The present invention solves the aforementioned problems
    Description of the invention The invention relates to an automatic valuation system for damages caused by
    30 meteorological risks on crops and infrastructure. The system includes an interface configured to select a geographic location and a specific meteorological risk. The system also includes an observation module that allows to capture cartographic information of the selected geographical location (including data of the type of crop and / or of the existing infrastructure in said location
    35 geographical) and real-time meteorological data using a detection system

    remote, through a network of weather stations or through an unmanned aerial vehicle. The system also includes a risk assessment module configured to estimate the levels of risks associated with said geographic location according to the meteorological variables of the observation module. Additionally, the system includes a module for assessing damages for the automatic and remote valuation of agrometeorological damages (based on the phenological state of the crops and the danger of the recorded meteorological risk) and of damages in the infrastructures of the selected geographical location, classifying the damages in different levels. A representation module is responsible for representing the risk and damage assessment levels in an associated cartographic base. Finally, the system can provide recommendations on how to act before the different alerts.
    The observation module may be configured to obtain the meteorological data from an observation system external to the system. The external observation system may include a satellite, a meteorological radar, a meteorological station, an electric unloading station, an unmanned aerial vehicle equipped with a radiometer that compares data prior to the meteorological event with data subsequent to it, or a meteorological reporter .
    The observation module is preferably configured to obtain the cartographic information from a database. The risk assessment module can be configured to estimate the levels of risk associated with the selected location by comparing the meteorological data captured on that location with reference values.
    Cartographic information may also include the phenological state of the crops. The phenological status of the crops can be obtained from a weather station located at the selected location and provisioned of at least one video camera for monitoring the on-site phenology. Cartographic information may include the vulnerability of infrastructure for each type of meteorological risk.
    The meteorological hazards that are contemplated can include intense rainfall of rain, snow, freezing rain, extreme temperatures, frost, conditions of sliding ground due to weather, fog or low visibility conditions, freezing fog, storms, storms with hail, wind gust maximum
    The risk assessment module is preferably configured to evaluate the intensity and duration of a particular meteorological risk. The damage valuation module can perform automatic agrometeorological damage valuation based on the
    5 Phenological state of the crops and the danger of the recorded meteorological risk, including its intensity and duration.
    BRIEF DESCRIPTION OF THE DRAWINGS A series of drawings that help to better understand the invention and that expressly relate to an embodiment of said invention that is presented as a non-limiting example thereof is described very briefly below.
    Figure 1 shows a schematic diagram of the system of the present invention.
    15 Figure 2 represents an example of an image with the probability of hail rainfall.
    Figure 3 represents an image with the appraisal of damages caused on cereal in the peninsula, taking into account the probability of hail precipitations of Figure 2.
    Figures 4 and 5 show two tables used to obtain the hail risk map of Figure 2.
    Figure 6A illustrates an example hail probability map for a specific day. 25 Figures 6B to 6F show different maps of damage caused on that day by hailstorms in different crops or infrastructures.
    Detailed Description of the Invention The present invention relates to a system that displays meteorological information in
    30 real time and also reports on the detection and monitoring of meteorological risks that affect crops and / or infrastructure. Additionally, the system allows to automatically assess the damages registered on the crops or the infrastructures allowing a rapid evaluation of the damages caused.
    35 System 1 comprises a series of interconnected modules, as shown in the

    schematic diagram of Figure 1. The system 1 comprises an interface 10 that allows a user to select one or more geographic locations (L) and at least one particular meteorological risk (R). The interface can be configured so that the user can enter information about the selected location, or to send and receive information from another user or from a risk manager.
    A real-time observation module 12 is responsible for managing and obtaining, for the selected geographical location (L), meteorological data (M) of different external observation systems 20, such as: satellite data, meteorological radars, stations meteorological, electric shock, observational data of unmanned aerial vehicles or meteorological reporter data. In addition, the observation module 12 obtains cartographic information (C) of the selected location, where said information includes at least data of the type of crop associated with the territory and / or of the existing infrastructures in the determined location.
    System 1 also comprises a risk assessment module 14 that estimates the level of each selected meteorological risk (NR) associated with each geographic location (L) according to the meteorological data (M) received from the observation module 12. The module of risk assessment 14 allows to obtain on a cartographic information system the interpolated observational data so that it is possible to know the weather conditions at any point.
    The risk assessment module 14 includes a data manager that allows to classify the levels of meteorological risk according to determined thresholds of danger. For example, risk assessment module 14 calculates the probability of hail from satellite images and classifies the risk of hail into "low" (values below 50% probability), "medium" (values between 50 and 70%) and "high" (values between 70% and 1100% probability). When these thresholds, established taking into account the climatic characteristics of the territory, are exceeded, a specific alert is issued for each meteorological risk considered.
    Therefore, the present invention provides a tool that allows knowing the weather conditions present in a given location as well as providing weather alerts to the end user. The system according to the present invention is

    Especially suitable for assessing the extent and duration of a particular meteorological risk.
    The meteorological hazards considered are, at least, heavy rainfall, snow or freezing rain, extreme temperatures, frost or sliding ground conditions due to weather, fog or low visibility conditions, freezing fog, storms, hail storms and streak maximum wind However, it is possible to introduce other meteorological risks later in the system.
    In a given study area, observational data from various monitoring systems can be available: data from a network of meteorological stations, radar data, data from an electric shock network and satellite data. In the system, it is possible to include observational data provided by an unmanned aerial vehicle (such as temperature or radiative values). The data provided by the various observational systems are integrated into a joint data network and the information is interpolated and pixelated for the entire territory.
    Figure 2 shows, by way of example, a risk map 30 (also called cartography or hazard map), which shows, in different shades of gray, the probabilities of hail rainfall estimated in the Spanish territory of the Peninsula Iberian, obtained from the risk assessment module 14.
    The development of the risk map 30 carried out by the risk assessment module 14 allows the transformation of the values of the meteorological parameters (M) into associated risk levels (NR). For the same location (L) selected, databases 22 are available with cartographic information (C) related to the characteristics of land uses, that is, information on the type of crop and / or type of infrastructure existing in the location .
    The system 1 also comprises, as shown in Figure 1, a damage assessment module 16 that performs the automatic assessment of damage to crops and / or structures. For the estimation of crop damage, the damage assessment module 16 combines the risk map 30 obtained by the risk assessment module 14 together with the type of crop (cereal, vine, olive, fruit, etc.) and the phenological state of the plant, obtained from the cartographic information (C). The damage assessment module 16 allows to finally obtain the damage assessment (D) in the crops by classifying this damage at different levels. The data of the phenological state of the plant can be obtained, for example, from a weather station located in the selected location and provisioned of a video camera that allows precise monitoring of the on-site phenology.
    Figure 3 represents an example of an image showing the damage assessment map 40 caused on cereal in the peninsula taking into account the probabilities of hail rainfall of Figure 2.
    For the assessment of infrastructure damage, the damage assessment module 16 estimates the damage considering the risk map 30 and an infrastructure vulnerability map for each type of meteorological risk (R).
    The system 1 also includes a representation module (18), which represents on the screen the risk map 30 (Figure 2) and the damage assessment map 40 (Figure 3) associated respectively with the risk levels (NR) and the damage assessment (D).
    The following explains in detail, and by way of example, the obtaining of the risk map 30 of Figure 2 from an experimental design that allows hail rainfall to be identified. The experimental design involves a total of five internal processes to determine hail rainfall with high temporal and spatial resolution:
    one. Receiving radiometer images: Images are received from an external radiometric information medium. These images may belong to different radiometric bands (ie, at different wavelengths depending on the radiometric resolution) of the instrument. This radiometric medium can be found on a satellite, on an unmanned aircraft or on any other observation platform.
    2. Transformation to .NAT format: The received images are transformed to a .NAT format.
    3. Transformation to .NetCDF format: Images in .NAT format are transformed to a NetCDF format.
    4. Obtaining the probability of convection: On each of the values
    Numeric (pixels) of the image is NetCDF type formula (1) is applied to obtain the probability of convection (Pocovection), a value for each of the pixels of the image that varies between O and 1:
    exp (Zl) pcollvecciOtl (1)
    l + exp (Zl)
    where Z, = 1492.636+ 1.188'X, -5.186'X, + 2.226'X, -1.659 ') ("-0.884'X, -7.62rX, 0.009810 * X7 + 0.026309 * X8 + 0.007047 * X9. The correspondence between the values of X and the spectral bands are shown in the table of Figure 4. The values of X represent the
    10 center of different spectral bands (center of the channel in micrometers).
    5. Obtaining the hail probability: On each of the numerical values (pixels) where the probability of convection (Pocovection) is equal to or greater than 0.5, formula (2) is applied, through which the probability of Hail (Pgrani.l: O):
    p. = exp (z,) (2) gramzo 1 + exp (z,)
    where, Z l = 115.039 -0.624 * Y1 -2.18 * Y 2 + 0.118 * Y 3+ 0.010955 * Y 4. The correspondence between the values of Y and the spectral bands is shown in the table in Figure 5. The values of And they represent the center of different spectral bands (center of the channel in micrometers). Finally, a numerical value is obtained in each of the pixels that
    20 measures the probability of hail precipitation (as much as one), which can be represented in a different color or gray-scale image for different probability bands, such as the example shown in Figure 2.
    Continuing with the previous example, once the hail probability map is obtained
    25 (risk map 30 of Figure 2), and known the phenological state of the plant and the map with cartographic information (C) on the types of crops, the valuation of the damages of a hail on cereal can be calculated. In the following, the calculation of the cereal damage appraisal for obtaining the damage appraisal map 40 of Figure 3 is explained in detail, by way of example.
    If a pixel in which according to the database of crop types is cereal, the
    Hail probability is over 50% and is at a time between April 1 andon November 31 (vulnerable phenological state), the damage is considered to be "damagemoderate. "If in that pixel the probability of hail is maintained for more than onedetermined threshold (e.g. 15 minutes), the damage becomes "strong damage". If you don't get to5 odds of 50% on the cultivated area is considered "weak damage." If weWe found out of those dates the valuation is "no damage." The dates of the statesVulnerable phenological variables vary for each type of crop and are calculated according tolegal regulations and research articles, being accessible from a database, byexample the same database 22 with the cartographic information (C). All calculations
    10 are performed automatically using various scripts.
    An example of a daily hail probability map obtained for a specific day is shown in Figure 5A. Figures 58 to 6F represent the map of damages (classified as "no damage", "weak damage", "moderate damage" and "strong damage") caused by hailstorms in
    15 different crops or infrastructures on the same day of Figure 6A: -Damage to cereal crops (Figure 68). -Damage to fruit crops (Figure 6e). -Damage to vine crops (Figure 6D). -Damage to olive crops (Figure 6E). That day there was no damage on
    20 olive plantations. -Damage on infrastructure (Figure 6F). This type of representation allows to know where hailstorms have been registered on roads or populated areas.
    权利要求:
    Claims (9)
    [1]
    1. Automatic valuation system for damages caused by meteorological risks in crops and infrastructures, characterized in that it comprises: - an interface (10) to select at least one geographical location (L) and at least one meteorological risk (R);
    - an observation module (12) configured to obtain meteorological data (M) and cartographic information (C) of each geographic location (L) selected, where the cartographic information (C) includes at least data from the type of crop or existing infrastructure in the geographic location (L) determined;
    - a risk assessment module (14) configured to estimate, for each meteorological risk (R) selected and based on the meteorological data (M), the different levels of risk (NR) associated in each geographic location (L);
    - a damage assessment module (16) configured to estimate, according to the risk levels (NR) and cartographic information (C), the damage assessment (D) in the crops or infrastructures of each selected location (L) , classifying the damages in different levels;
    - a representation module (18) configured to represent risk levels (NR) and damage assessment (D) in an associated cartographic base.
    [2]
    2. System according to claim 1, characterized in that the observation module (12) is configured to obtain the meteorological data (M) from at least one external observation system (20).
    [3]
    3. System according to claim 2, characterized in that the at least one system of
    External observation (20) includes at least one of the following: - a satellite, - a weather radar, - a weather station, - an electric shock station, - an unmanned aerial vehicle equipped with a radiometer that compares data prior to the event weather report with data after it, -a weather reporter.
    [4]
    4. System according to any of the preceding claims, characterized in that the
    Observation module (12) is configured to obtain the cartographic information (C) from a database (22).
    5. System according to claim 1, wherein the risk assessment module (14) isconfigured to estimate the risk levels (NR) associated with the selected locationby means of a comparison of the meteorological data captured on said localitywith reference values.
    System according to any of the preceding claims, characterized in that the cartographic information (C) includes the phenological state of the crops.
    [7]
    7. System according to claim 6, characterized in that the phenological state of the crops is obtained from a weather station located at the location
    15 selected and provisioned of at least one video camera to monitor on-site phenology.
    [8]
    8. System according to any of the preceding claims, characterized in that the
    Cartographic information (C) includes the vulnerability of infrastructure for each type 20 of meteorological risk.
    [9]
    9. System according to any of the preceding claims, characterized in that the meteorological hazards comprise at least one of the following: - intense rainfall requirements,
    25 - snow, - freezing rain, - extreme temperatures, - frosts, - sliding floor conditions due to weather,
    30 - fog or low visibility conditions, - icy fog,
    -storms,-storms with hail,-Maximum wind gust.
    [10]
    10. System according to any of the preceding claims, characterized in that the risk assessment module (14) is configured to evaluate the intensity and duration of a particular meteorological risk.
    [11 ]
    eleven . System according to any of the preceding claims, characterized in that the damage assessment module (16) performs the automatic appraisal of agrometeorological damages based on the phenological state of the crops and the danger of the recorded meteorological risk, including the intensity and duration of the same.
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    同族专利:
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    ES2572534B1|2017-03-10|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US20050197774A1|2004-03-02|2005-09-08|Masashi Egi|Method, program, and system for estimating weather risk|
    WO2007103402A2|2006-03-08|2007-09-13|Guy Carpenter & Company, Inc.|Spatial database system for generation of weather event and risk reports|
    US20100085197A1|2008-10-06|2010-04-08|International Business Machines Corporation|System and method of damage prevention from weather occurrences|
    US9087312B1|2015-01-23|2015-07-21|Iteris, Inc.|Modeling of costs associated with in-field and fuel-based drying of an agricultural commodity requiring sufficiently low moisture levels for stable long-term crop storage using field-level analysis and forecasting of weatherconditions, grain dry-down model, facility metadata, and observations and user input of harvest condition states|
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