WO2017039431A1

WO2017039431A1 - Method and system for controlling natural fire

Info

Publication number: WO2017039431A1
Application number: PCT/NL2015/000028
Authority: WO
Inventors: Ester WILLEMSEN
Original assignee: Instituut Fysieke Veiligheid
Priority date: 2015-09-04
Filing date: 2015-09-04
Publication date: 2017-03-09

Abstract

The present invention is in the field of real time controlling natural fires and of a system for predicting development of a natural fire. It has been found difficult to control natural fires, or at least adequately control these fires. Many natural fires end up to be so called wildfires. Such is unwanted.

Description

Method and System for controlling Natural Fire

FIELD OF THE INVENTION

The present invention is in the field of real time controlling natural fires and of a system for predicting development of a natural fire.

BACKGROUND OF THE INVENTION

It has been found difficult to control natural fires, or at least adequately control these fires. Many natural fires end up to be so called wildfires.

A wildfire is considered an uncontrolled fire in an area having combustible vegetation. In most instances these fires occur in a countryside or a wilderness. The wildfires are (to some extent) also known under various/similar terms such as forest fire, desert fire, brush fire, bushfire, grass fire, hill fire, peat fire, and vegetation fire. A wildfire typically differs from other fires by its extensive size, the speed at which it can spread out from its original source, its potential to change direction unexpectedly, and its ability to jump gaps such as roads, rivers and fire breaks, in other words it is to a large extent unpredictable in its behavior. Wildfires are a common occurrence in a hot and dry climate, and they often occur in more moderate climate zones as well, especially during summer time. They pose a great risk to life and infrastructure; they burn vast areas of land (up to 1 million km²/year

worldwide) . Natural fires and especially uncontrolled wildfires cause extensive damage.

There are basic strategies of wildfire detection, prevention, and suppression, but these are often not

sophisticated enough. A very basic strategy, still used a lot, is an assumption that fire will develop in an angle of 45° from a starting point. A suppression technique considered is controlled burning, such as for stopping a fire; however such a technique is typically limited to scarcely populated areas. In other words the prior art strategies are considered at the most first order approaches of controlling fire, which are in many cases unsuited. Some prior art documents recite methods for controlling natural fire.

For instance DE 10 2007 007492 Al recites a method involving determining a simulation model of temporary fire process by considering extinguishing effects of different extinguishing techniques. The simulation model reverts to meteorological measuring data and maintained data by an area condition. The simulation results are provided to a central control room, and action force is delivered over an optimal input guide. The action force and supply forces are led over the control room with regard to predictive location of the fire. This method uses only wind speed and wind direction, and possibly landscape information, which is typically insufficient for controlling a natural fire. In addition the model uses coarse grids, which results in unreliable results and hence insufficient control. Such is especially relevant in densely populated areas.

WO2007/054630 Al recites a method of detecting a fire in a wooded area, characterized in that it comprises the following steps: providing some trees in the area with a fire sensor provided with a radiofrequency emitter able to emit information for identifying and/or locating each sensor, according to a grid of the area to be monitored; detecting at each fire sensor the fire absent or fire present state, and making a fire sensor emit an alert signal, if a fire is present in the vicinity of said sensor, containing information for identifying and/or a signal for locating the said sensor, to a monitoring post; - transmitting the alert signal from the monitoring post to the fire brigade by means of a long-range radiofrequency link.

US2009/128327 A2 recites a system for adjusting parameters of ambient condition detectors in a regional monitoring system is coupled to or includes fire modeling processing. Based on outputs from the processing, selected parameters of respective detectors can be adjusted to shorten detector time to alarm. As a fire condition develops, different detectors can be adjusted dynamically and in real-time. EP 1 561 493 A2 recites a system for the detection of forest fires, having an airborne infra-red detection system that passes infra-red data with geo references to the center for planning and coordinating the action. The center has a computer unit which can display the affected surface and compute firefighting plans. The center is in communication with airborne (and ground firefighting units. US 5,832,187 A recites a system and method for automatically detecting fires in select areas, and reacting thereto to put out the fires. A stationary, earth orbit satellite, pilotless drone aircrafts or piloted aircraft contains one or more infrared detectors and optical means for detecting small fires when they first occur in fields and wooded areas, preferably where man made campfires and trash dumping are prohibited. A computer in the satellite, drone or piloted aircraft and/or on the ground receives and analyzes image signals of the earth area or areas being monitored and, upon detecting infrared radiation of varying intensity and variable shape, indicative that a fire has started, generates coded signals which are (a) indicative of the coordinate locations of the fire, (b) the extent of the fire, (c) the shape of the area(s) burning, (d) the direction of movement of the fires (e) the speed (s) of the flame fronts, (f) smoke condition, (g) intensity of the fire, (h) fire ball location(s), etc. In one form, a conventional and/or infrared television camera (s) generates image or video signals which are digitized and recorded in memory and/or on tape or disc. Expert system logic, such as fuzzy logic, is used to prioritize dangerous areas to assist in directing

firefighting. Such information, or select portions thereof, is automatically transmitted to one or more earth bound and/or aircraft contained receivers where firefighting equipment such as helicopter and aircraft containing drainable water or other firefighting agents is available for immediate dispatch to the fire zone. And O2010/015742 Al recites a system for preventing fires, especially forest fires, comprising on the one hand a network of a plurality of geolocalized sensors forming a grid in the area of forest to be monitored, each sensor being able to detect locally an incipient fire and being provided with a radiofrequency transmitter connected by radio to a control terminal) , so that the detection of an incipient fire in the vicinity of a sensor is transmitted automatically to its control terminal) , which is able to generate an alert signal, the system being characterized in that it comprises a computer provided with simulation software capable of predicting in advance in terms of physical time, on the basis of a plurality of parameters, the movement of a flame front away from the position of an incipient fire. These documents are considered to relate to background art, identifying in general rough approaches .

The present invention therefore relates to a method and system for preventing and/or limiting damage of Natural Fire, which overcomes one or more of the above disadvantages, without jeopardizing functionality and advantages.

SUMMARY OF THE INVENTION

The present invention relates in a first aspect to a method for real time controlling a natural fire and in a second aspect to a system for predicting development of a natural fire .

The present method relies on determination of an actual situation. Characteristics of a location of a fire and its vicinity are found to determine development of a fire, such as extent of a fire at a certain point in (future) time, speed of a fire in a certain (or multitude) of direction (s) , intensity of a fire. The present model now has fine-tuned characteristics and has established the most important characteristics for development of a natural fire and provides predictions on development of a fire in a few minutes time or better.

It is noted that especially in densely populated areas insight in development of natural fires is of the utmost importance. It is for instance important to evacuate people in time, and/or to advise to seek shelter. Likewise, an evacuation plan can be tested/adapted based on novel insights of the present method. If a natural fire is developing, it is

important to establish opportunities to control the fire or even to extinguish the fire. The opportunities should clearly be worthwhile to pursue. It is also important to act quickly. In a few minutes time a first insight in a (most likely) scenario should be available. Such indicates that information of the actual location such be updated regularly. Contrary to less populated areas (or scarcely populated areas) one can not just let a fire continue for hours or days, before controlling it, typically at a costs of thousands of hectares natural land lost. With the present system appropriate measures can be taken.

It has been found that the weather is of great influence on the spread and development of natural fires. A step in making a prediction is providing the most significant weather parameters. Providing the (actual) weather parameters is a step in the process of making a prediction, and is done halfway through the process. This step is preferably performed after combining all landscape characteristics and therefore easily adjustable during usage of the present model system. Because this step is being done after combining all the landscape characteristics, which takes the longest time to load, it isn't necessary to redo the entire process just to adjust a couple of parameters, such as wind parameters. Changing (wind) parameters can be done in a matter of seconds, instead of redoing the entire process, which has to be done using prior art models. In other words the present system is capable of real time

predictions, based on parameters that have been entered in view of e.g. changes therein. This function helps making the present spread model a fast and easy to use model.

It is noted that the present system can be used during large scale fire events, for e.g. Dutch standards. In this respect it is observed that Dutch fire events typically last up to a couple of days maximum, which leaves no time to set up an extended command post. Therefore for instance no significant GIS unit is available on short notice during Dutch fire events. Therefore, the Dutch spread system is capable to operate on a much more mobile platform. The Dutch spread model runs on an average laptop computer, instead of heavy duty desktop

computers of prior art systems, yet giving reliable and adequate results. It can be used directly on the fire line if needed. Calculation by the Dutch spread model only takes minutes instead.

In view of the present system it is noted that Dutch regional fire departments are using newly developed Command and Control systems to run operations on a natural/wildfire event. These systems are considered high tech and are a major

improvement on the way fire departments can handle operations like a large scale wildfire event. These systems use, for determining wildfire spread, a basic rule of thumb, which indicates that every meter/second wind speeds results in a 100 meter/hour fire spread. This rule of thumb is projected on a map, using a 45 degrees angle, and is considered to determine the fire spread off the coming hours. As indicated, such a system is in most cases insufficient. It is noted that with the present system it is not even necessary to use the above rule of thumb as a first indication; the present system can already be used at a start of the fire, due to its efficient and sophisticated design and prediction capacity. The present system can be operated by a person who is for instance the first one at a location of the fire, in a control room, etc. As such it now becomes possible to use the system in a preparative sense, such as by predicting a size of the fire on arrival (of fire fighting forces) .

The present system takes all relevant parameters into a count, including spots of bare ground, which makes a projected fire spread much more detailed. Where prior art methods project a fire front of multiple hundreds of meters across e.g. a heather field, the present system might project a much smaller fire front, burning between a couple of spots of bare ground, which will only leave 30 or 40 meter fire front. To recognize operational chances to control a wildfire the spread model can be used looking at the more specific data, compared to the method that is being used at this moment.

It has been found that, compared to prior art systems, the calculations/predictions of the present system are much more detailed. The present system makes a calculation based on detailed vegetation data, specific weather parameters of the upcoming hours and detailed terrain configuration, for the next hours. Such is considered a huge difference in the amount of details presented in a calculation.

It has been found that with determination of a relatively small number of parameters a good prediction of development of a fire can be made. Therein a minimum temperature may have a relative weight of 5-15%, such as 10%, a maximum temperature may have a relative weight of 5-15%, such as 10%, a minimum relative humidity may have a relative weight of 5-20%, such as 15%, a maximum relative humidity may have a relative weight of 2-15%, such as 8%, a wind speed may have a relative weight of 20-50%, such as 35%, a cloud coverage may have a relative weight of 5-15%, such as 10%, and an energy source may have a relative weight of 10-60%, such as 20-40%%. Other parameters mentioned, such as sunshine, may have a relative weight of 1- 10%, such as 2-5%. With the present set of parameters it has been found that a correlation of predicted development of a fire and actual development is in the order of 80-90%. In this respect it is noted that a large part of the deviation from 100% is caused by actual measures taken by the fire fighters, such as extinguishing of fire.

For instance local wind speed (± 5 m/s) and direction {± 5°) need to be determined in order to determine direction and speed of a fire. The relative humidity (RH ± 5%) is of some importance. The amount of energy source is very important as well as the nature of the source (in kg dry C/ha ± 5%) . The amount of water (± 2 wt . % relative to a total weight) being present and attributed to the energy source, such as in the form of frost, hoarfrost, condense, etc. as well as in the form of water content is a further important factor. Than the landscape, such as a height map comprising mountains, and hills, water bodies, such as ditches, human elements, such as infrastructure, dikes, pathways, pavements, etc. is found to be of relevance. It is noted that for instance in prior art models a bicycle track would be a sufficient barrier for a fire to stop, whereas in reality such a track would be of almost no significance. As such for instance the human elements need to be given a relatively low energy source value, indicating some delay in development. The present method also immediately identifies potential locations at risk, and at what point in time these locations could be at risk.

It has been found that a rough estimation of the above parameters is insufficient for a correct prediction of development of a fire. As such, as can very often be seen when battling natural fires unfortunately, wrong/insufficient measures are taken, at a wrong location, fire fighters get caught in the fire, etc. The present grid used for

determination is at least <100*100 m². For some not too much varying landscapes, as a polder landscape, such a grid may be sufficient. If more variation is present preferably a grid of < 50*50 m² is used. For even more variation preferably a grid of < 25*25 m² is used. For large parts of a landscape (and

determination of parameters) an even finer grid is used, such as < 10*10 m² , even up to < 2*2 m². Also combinations of grids may be used. It is noted that for taking correct measures in order to fight fires a smaller grid is better, because than measures can be taken at (almost an exact) relevant location or locations.

The present system can predict development of fires over a large area, even up to 100 km². Also development of small fires, having an area of 1 km² or less can be predicted

accurately.

Based on the above parameters a prediction of development of the natural fire is made towards at least one future point in time. Typically a prediction is made for various points in time, typically at least more accurate than on an hourly basis. By making use of the prediction ( s ) it is also possible to calculate a possible effect of measures (to be) taken, such as stop lines, strategic choices, deployment of forces, etc. The choices can now be (further) substantiated.

Having predicted the development measures to control the fire are established.

Thereby the present invention provides a solution to one or more of the above mentioned problems, by providing an extended system, comprising various functionalities, wherein the functionalities are further optimized with respect to each other, thereby further improving functionality and user friendliness.

Advantages of the present description are detailed throughout the description.

DETAILED DESCRIPTION OF THE INVENTION The present invention relates in a first aspect to a method for real time controlling a natural fire comprising the steps of

determining at least one value of a set of parameters, the set comprising

wind speed and wind direction,

relative humidity,

an amount of energy source,

an amount of water attributed to the energy source, landscape, such as a height map comprising mountains, and hills, water bodies, and human elements, such as infrastructure, such as roads, paths,

electricity pylons, and dikes,

and

potential locations at risk,

wherein determination is performed using a grid of

<100*100 m², preferably a grid of < 50*50 m², more preferably a grid of < 25*25 m²,

predicting development of the natural fire at a given point in time, and

establishing measures, such as to limit the fire, to evacuate people, to start a counter fire.

In an example of the present method the energy source is one or more of wood, such as hardwood, softwood, heath, combined heath and grass, moorland, peat, dune, wetland, and grass. It has been found that the nature of the energy source is crucial for predicting an accurate development. For instance, a hardwood environment could indicate

spreading of fire over large distances per unit time, heath may continue burning underground and at edges of an area comprising heath, etc.

In an example of the present method the amount of energy source is determined based on a model and one or more of satellite data, such as IR-satellite data, wherein the

satellite data is up to date data, fresh data provided by a helicopter, fresh meteorological data, a mobile weather station, and a handheld wind speed and wind direction

measurement equipment. Obtaining fresh data supports real time prediction of development. It is noted that often local variations and actual nature of a fire is different from what is expected or even predicted, such as hot spots. Real time measurements further support adapting the method and improving prediction of development of a fire.

In an example of the present method an amount of water attributed to the energy source, cloud cover, sunshine, outside temperature, and an amount of water in contact with the energy source. It has been found that if these amounts have been determined accurately, on a local scale, a prediction of development of a fire improves. The outside temperature may relate to a minimum (day) temperature, a maximum day

temperature, and an average day temperature, and combinations thereof .

In an example of the present method an action scenario is established. For instance, counter fires can be established, evacuation can be executed, available resource for firefighting can be located at critical areas, etc.

In an example of the present method for one or more of limiting risk in advance, for management of natural area, for photo-guiding, for risk evaluation, for dynamic interaction when limiting the fire, for forensic research, and for control of crisis. Limiting risk in advance can relate to removing energy source, planning water bodies, cleaning an interface between nature and urbanization, prohibiting urbanization, keeping areas clean (of energy source) , managing natural area over a long period of time, etc. Photo guiding, during a fire, and otherwise, can help improve the quality of underlying data for the model, and establish an actual situation. Such can be done by remote sensing. At the same time photo guiding can help fire fighters take appropriate measures. It is preferred to dynamically interact and act upon information when limiting a fire, e.g. when authorities make decisions in this respect.

In an example of the present method prediction of development comprises predicting a size, an intensity, and a position of at least one boundary of the fire. The boundary of the fire may relate to a line up to which the fire has

developed. Preferably a whole circumference of the fire is predicted. Even more preferably the development of the

boundary, or circumference, of the fire is predicted in time, such as in steps of one hour, more preferably in steps of 30 minutes, even more preferably in steps of 15 minutes. Therewith appropriate measures can be taken.

In an example of the present method a fire is limited to less than <2000*2000 m², preferably to less than <1000*1000 m², more preferably to less than <500*500 m², such as less than <250*250 m². Therewith adequate control is provided in most situations being relevant for e.g. populated areas.

In an example of the present method hot spots are

identified. These hotspots are considered particularly relevant for controlling a fire. Thereto typically a vehicle or the like travels through a fire area, establishing these hotspots.

Likewise similar information may be obtained by a helicopter or airborne vehicle.

In a second aspect the present invention relates to a system for predicting development of a natural fire comprising a set of parameters, the set comprising wind speed and wind

direction, relative humidity, an amount of energy source, an amount of water attributed to the energy source, landscape, such as a height map comprising mountains, and hills, water bodies, and human elements, such as infrastructure, such as roads, paths, electricity pylons, and dikes, and potential locations at risk, wherein determination is performed using a grid of <100*100 m², preferably a grid of < 50*50 m², more preferably a grid of < 25*25 m².

In an example the present system further comprises one or more of a user interface, a graphic interface, a 3-D model, a geographical interface, a mobile weather station, an apparatus for maintaining wireless contact, such as a satellite vehicle, a photo guide, such as a mobile vehicle, and a tablet. The present system may be web-based and is preferably also a standalone system. The system is preferably updated on a daily basis, more preferably in times of fire on an hourly basis.

EXAMPLES

The invention is further detailed by the accompanying example, which is exemplary and explanatory of nature and are not limiting the scope of the invention. To the person skilled in the art it may be clear that many variants, being obvious or not, may be conceivable falling within the scope of protection, defined by the present claims.

SUMMARY OF FIGURES

Figures 1-8 show detailed maps and development of a simulated fire in an example of the present system.

Fig. 9 shows an area (Deelense Veld)

Fig. 10 shows a part of the area of fig. 9.

Fig. 11 shows an enlarged part of fig. 10 having a frame around it.

DETAILED DESCRIPTION OF THE FIGURES

It has been found that natural fire spread model need different parameters to determine the spread of a natural fire in different fuel types. These parameters consist of fuel type (or energy source) (vegetation), historical weather characteristics on previous seven days (determines the fuel drought or amount of water attributed to the fuel source) , future weather characteristics on coming 7 hours (determines the expected fire spread in the given fuel, linked to the historical weather characteristics). Which of these parameters has the greatest influence on the spread of a natural fire will be shown by using the spread model. Chance will be shown in difference in meters/hour in fire spread. The parameter with the most increase of fire spread in meters/hour is the parameter with the highest influence on fire spread.

Making a control calculation using basic parameters, using a fixed plot, will give the control calculation. The parameters that will be changed in a different calculation are marked with the color red. The other parameters, if changed, won't have a significant effect on the fire spread. The change will be done by a 20% change in each of the parameter. Except the cloud cover, that will be changed from 0% to 20%. On a scale between 0% and 100% a 20% increase will be 20%.

Calculation area:

The area that will be used, is an heather area in the northern region of the Veluwe area in The Netherlands (fig. 1) . It is noted that sophisticated data is used in order to establish differences. The wind has been situated in such a way, that the fire will spread across the heather field without any other vegetation type.

Control parameters :

Drought parameters

These parameters determine the state of drought. If this is linked with a fuel model, it will determine the drought of a vegetation/fuel type as well.

Table 1. Drought parameters.

Wind parameters

These parameters determine the fire spread, if linked to the drought parameters and linked to the fuel model.

Table 2. Wind parameters.

Control calculation, using the control parameters.

Using the control parameters the fire spreads with a speed of 397 m/h in the first hour. This calculation will be repeated, with the changed parameters (see fig. 2) .

Changed T min.

This calculation is done with a change in the Minimal

temperature. The minimal temperature is increased with 20%, which makes it 18 degrees Celcius instead of 15 (see fig. 3) . Using the changed minimal temperature parameters, the fire spreads with a speed of 431.1 m/h in the first hour.

Changed T Max.

This calculation is done with a change in the maximum

temperature. The maximum temperature is increased with 20%, which makes it 36 degrees Celsius instead of 30.

Using the changed maximum temperature parameters, the fire spreads with a speed of 439 m/h in the first hour (see fig. 4) . Changed RH min.

This calculation is done with a change in the minimal relative humidity. The minimal relative humidity is decreased with 20%, which makes it 40% RH, instead of 50.

Using the changed minimal relative humidity parameters, the fire spreads with a speed of 459,6 m/h in the first hour (see fig. 5) .

Changed RH max.

This calculation is done with a change in the maximum relative humidity. The minimal relative humidity is decreased with 20%, which makes it 80% RH, instead of 100.

Using the changed maximum relative humidity parameters, the fire spreads with a speed of 423,8 m/h in the first hour (see fig. 6) .

Changed wind speed.

This calculation is done with a change in the wind speed. The wind speed is increased with 20%, which makes it 3,96 m/s, instead of 3,3.

Using the changed wind speed, the fire spreads with a speed of 533 m/h in the first hour (see fig. 7) .

Changed cloud cover.

This calculation is done with a change in the cloud cover. The cloud cover is increased with 20%, which makes it 20%, instead of 0%.

Using the changed cloud cover, the fire spreads with a speed of 434,5 m/h in the first hour (see fig. 8) .

Overall change

This is an overview of the results in change of the different spread parameters. Numbers are absolute and in percentages. Change Control Changed Absolute Percentage

T. Min 397 431,1 34,1 8,6%

T. Max 397 439 42 10,6%

RH. Min 397 459,6 62,6 15,8

RH. Max 397 423,8 26,8 6,8%

Wind speed 397 533 136 34,3%

Cloud Cover 397 434,5 37,5 9,4%

Table 3. Relative contributions of parameters.

Fig. 9 shows an area (Deelense Veld). Various landscape items, such as roads, and landscape conditions, such as heather, open field, wood, and so on are visible. In the central part a natural fire occurred.

Fig. 10 shows a part of the area of fig. 9. According to model predictions the fire would proceed along a certain trajectory. The fire started in the mid-upper left section of the figure and would have proceeded according to the lines indicated in the figure, each line representing a later stage of the fire. A few of these lines are indicated with an arrow.

Fig. 11 shows an enlarged part of fig. 10 having a frame around it. Due to accurate control of the natural fire and preventive measures the extension of the fire could be limited to the area indicated. Note that fig. 11 is already a sub-area of fig. 10, and in addition only about 50% of the area of fig. 11 would be hit by the fire. In conclusion the present method showed to be very effective in controlling a natural fire.

A further conclusion is that various structural and preventive measures can and should be taken to limit future fires. For instance young trees can be removed, stop lines can be introduced, road access when having a fire can be evaluated etc.

Claims

1. Method for real time controlling a natural fire

comprising the steps of

determining of a set of parameters at least one value of each parameter, the set comprising

wind speed and wind direction,

relative humidity,

an amount of energy source,

an amount of water attributed to the energy source, landscape, such as a height map comprising

mountains, and hills, water bodies, and human elements, such as infrastructure, such as roads, paths,

electricity pylons, and dikes,

and

potential locations at risk,

wherein determination is performed using a grid of

predicting development of the natural fire at a given point in time, and

2. Method according to claim 1, wherein the energy source is one or more of wood, such as hardwood, softwood, heath, combined heath and grass, moorland, peat, dune, wetland, and grass.

3. Method according to any of the preceding claims, wherein the amount of energy source is determined based on a model and one or more of satellite data, such as IR- satellite data, wherein the satellite data is up to date data, fresh data provided by a helicopter, fresh

meteorological data, a mobile weather station, and a handheld wind speed and wind direction measurement

equipment .

4. Method according to any of the preceding claims, wherein the set of parameters further comprises an amount of water attributed to the energy source, cloud cover, sunshine, outside temperature, and an amount of water in contact with the energy source.

5. Method according to any of the preceding claims, wherein an action scenario is established.

6. Method according to any of the preceding claims, for one or. more of limiting risk in advance, for management of natural area, for photo-guiding, for risk evaluation, for dynamic interaction when limiting the fire, for forensic research, and for control of crisis.

7. Method according to any of the preceding claims, wherein prediction of development comprises predicting a size, an intensity, and a position of at least one boundary of the fire.

8. Method according to any of the preceding claims, wherein a fire is limited to less than <2000*2000 m², preferably to less than <1000*1000 m², more preferably to less than <500*500 m², such as less than <250*250 m².

9. Method according to any of the preceding claims, wherein hot spots are identified.

10. System for predicting development of a natural fire comprising a set of parameters, the set comprising at least one value of

wind speed and wind direction,

relative humidity,

an amount of energy source,

an amount of water attributed to the energy source, landscape, such as a height map comprising mountains, and hills, water bodies, and human elements such as infrastructure, such as roads, paths,

electricity pylons, and dikes,

and

potential locations at risk,

wherein determination is performed using for each parameter a grid of <100*100 m², preferably a grid of < 50*5 m², more preferably a grid of < 25*25 m².

11. System according to claim 10, further comprising one or more of a user interface, a graphic interface, a 3-D model, a geographical interface, a mobile weather station, an apparatus for maintaining wireless contact, such as a satellite vehicle, a photo guide, such as a mobile vehicle, and a tablet.