ES2572534B1 - Automatic valuation system for damages caused by meteorological risks in crops and infrastructure - Google Patents

Abstract

Automatic valuation system for damages caused by meteorological risks in crops and infrastructure, comprising: # - an interface (10) to select geographic 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 (N {sub, R}) associated with geographic location (L); # - a damage assessment module (16) to estimate, according to risk levels (N {sub, R}) and information cartographic (C), the valuation of damages (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 ( N {sub, R}) and damage assessment (D) in a associated cartographic base # The observation module allows the incorporation of data provided by an unmanned aerial vehicle or by a meteorological observer.

Description

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 infrastructures caused by meteorological risks is occurring. The process of estimating damages or appraisal is not carried out automatically, 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 in 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. Likewise, there is no system 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 appraisal system for damages caused by 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 infrastructures in said geographical location) and real-time meteorological data by means of a remote detection system, 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 appraisal module can perform the automatic appraisal of agrometeorological damage based on the phenological state of the crops and the danger of the recorded meteorological risk, including the intensity and duration of the crop.

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.

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. Figures 68 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 real-time meteorological information 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.

System 1 comprises a series of interconnected modules, as shown in the schematic diagram of Figure 1. System 1 comprises an interface 10 that allows a user to select one or more geographic locations (L) and at least one risk meteorological (R) determined. The interface can be configured so that the user can enter information about the selected location, or to send and receive

5 information from another user or 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 radar,

10 weather stations, electric shocks, observational data of unmanned aerial vehicles or weather reporters 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.

15 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 risk assessment module 14 allows to obtain information system

20 cartographic 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 hail risk as "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 to

30 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 Iberian Peninsula, 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

damage assessment (D) on crops 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.

Four.

Obtaining the probability of convection: On each of the numerical values (pixels) of the image is NetCDF type, the formula (1) is applied to obtain the probability of convection (Pocovection), a value for each of the pixels of the image. 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, O.009810 * X7 + O.026309 * X8 + O.007047 * X9 The correspondence between the values of X and the spectral bands is shown in the table in 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,)

15 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 Y 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 measures the probability of hail precipitations (in both by one), which can be represented in an image in different colors or grayscale 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.

30 If a pixel in which according to the database of crop types is cereal, the probability of hail is greater than 50% and is at a time between April 1 and November 31 (vulnerable phenological state) , the damage is considered to be "moderate damage", if in that pixel the probability of hail is maintained for more than a certain threshold (e.9. 15 minutes), the damage becomes "strong damage", if it is not Arrives at 50% odds on the cultivated area is considered "weak damage." If we are outside those dates, the appraisal is "no damage." The dates of vulnerable phenological states vary for each type of crop and are calculated according to legal regulations and research articles, being accessible from a database, for example the same database 22 with cartographic information (C). All calculations are performed automatically using various scripts.

An example of a daily hail probability map obtained for a specific day is shown in Figure 6A. Figures 68 to 6F represent the damage map (classified as "no damage", "weak damage", "moderate damage" and "strong damage") caused by hailstorms in different crops or infrastructure on the same day as 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 to olive plantations. -Damage on infrastructure (Figure 6F). This type of representation allows to know where hailstorms have been registered on roads or populated areas.

Claims (11)

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.

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.

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.

Four.

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) is configured to estimate the risk levels (NR) associated with the selected location by comparing the meteorological data captured on said location with reference values.

6.

System according to any of the preceding claims, characterized in that the cartographic information (C) includes the phenological state of the cultures.

7.

System according to claim 6, characterized in that the phenological state of the crops is obtained from a weather station located in the selected location and provisioned of at least one video camera for monitoring the on-site phenology.

8.

System according to any of the preceding claims, characterized in that the cartographic information (C) includes the vulnerability of the infrastructures for each type of meteorological risk.

9.

System according to any of the preceding claims, characterized in that the

Meteorological hazards include at least one of the following: - heavy rainfall, snow, freezing rain, extreme temperatures, frost, sliding floor conditions due to weather, fog or low visibility conditions, fog freezing, -storms, -storms with hail, -wind maximum wind. 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. 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.