Geoinformation system for prediction of forest fire

Geoinformation system for prediction of forest fire danger caused by solar radiation using remote sensing Nikolay V. Baranovskiy*, Elena P. Yankovich National Research Tomsk Polytechnic University, 30 Lenin av., Tomsk, Russia 634050 ABSTRACT This article reviews the project of subsystem that reflects the Earth remote sensing data from the space in order to monitor the forest fire danger, caused by the focused solar radiation effect. This subsystem is based on the use of sensing data from the MODIS instrument aboard the Terra satellite. We consider the Timiryazevsky Forestry of Tomsk region to be a typical territory of the boreal forest zone. To estimate the forest fire danger level, we use an original method to classify the forest areas according to their characteristics (the ground mensuration data) and the main meteorological parameters, namely, the cloud cover on this territory, obtained from the MODIS satellite data. Keywords: forest fire, danger, geoinformation system, solar radiation, cloud, MODIS

1. Introduction According to [1,2], the reasons why forest fires occur are quite various, but can be divided into natural and anthropogenic components. Anthropogenic factors include felony arson, careless usage of fire, the impact of railway lines and motor highways, and the presence of settlements or technological objects on the forested territories [1]. The igniting mechanisms can be the effects of the particles, heated up to high temperature, the radiative or convective heat flux, etc. [3]. The natural factors should include the fact that forest fuels can ignite due to the cloud to ground storm discharges [4]. However some reasons have a mixed character. They refer, for example, to the fact that forest fuels can ignite due to the focused solar radiation effect [5]. In theory [6] and experiments [7] we showed that the forest fuel layer can ignite when the solar energy concentrates on the level of 15-17 kW/m2. The energy concentrators can be the glass containers, their fragments and big resin blobs. In this case, the first ones fall to the natural reasons, and the second ones to the anthropogenic factors. We have developed a physically based method to estimate the forest fire danger during the focused solar radiation effect [8]. At present, we must develop the technology that will answer the forestry management needs. Its base should be this forest fire danger detection method. The purpose of the study is to develop a subsystem that reflects the Earth remote sensing data from the space in order to monitor the forest fire danger, caused by the focused solar radiation effect. There is growing awareness of the increases in frequency and intensity of wildfires across Siberia and their impact on the economy, human health 1,2 and climate change 3,4. The spread and evolution of Siberian wildfires over the recent decades have been revealed successfully by satellite observations. For example, Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on NASA’s Terra and Aqua satellites have provided a valuable fire-related product, which includes a rich data source about area burned, fire intensity and long-range plumes transport of Siberian wildfires 5. The recent intercontinental smoke transport from Siberian fires (summer 2012) to British Columbia (Canada) (Figure 1) illustrates the intensity of severe fires occurred in Siberia.

2. Computational Model At present, the scientists apply in practice the methods, developed with the use of large statistical data files (Nesterov V.G., Novozhenkova L.F., Viegas D.X., Van Wagner C.E., Stocks B.J., Alexander M.E., Garsia Diez E.L., Deeming I.E. etc.). These methods represent the formulas, algorithms, criteria, worked out from averaging the characteristics of ignition conditions on large samples both by areas and by the time [9-14]. Among them, the Canadian, American and European systems have become widely spread [1]. The Nesterov complex meteorological index is a state standard in the Russian Federation. *[email protected], phone +7-903-953-56-95, tpu.ru

Remote Sensing of Clouds and the Atmosphere XX, edited by Adolfo Comerón, Evgueni I. Kassianov, Klaus Schäfer, Richard H. Picard, Konradin Weber, Proc. of SPIE Vol. 9640, 96400Z 2015 SPIE · CCC code: 0277-786X/15/$18 · doi: 10.1117/12.2193864 Proc. of SPIE Vol. 9640 96400Z-1 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 11/06/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

To visualize the spatial information, it is logical to use the geographical information systems [15]. Geoinformation systems can be of various types. For example, in Ukraine, the scientists are developing the web-based GIS-system ForestGIS to estimate the forest fire danger [16]. This system allows to process the user queries in the web-server and to subsequently visualize the predictive and estimative information via the Internet. Moreover, we are actively developing the data computing system that forecasts and estimates the forest fires danger. It is based on interactive communication of GIS-system that layer by layer reflects the information about probable fires, and has the parallel software system that processes the input data and generates the forecasting information fields [17]. At present, the most famous GIS-systems are as follows: 1. The Information System of Forest Fire Remote Monitoring of the Federal Forestry Agency (ISDM-Rosleskhoz) (Russia) [18]. It estimates the current fire danger relying on the Nesterov index without any physical basis. A separate meteorological station is responsible for the minimal territory. Thanks to the scientists from the National Research Tomsk Polytechnic University, this system acquired the probability criterion to estimate the forest fire danger with regard to the thunderstorm activity and human factor. It disregards the forest fires caused by a focused solar radiation effect. It uses the remote sensing data. 2. The Canadian Forest Fire Danger Rating System CFFDRS (Canada) and the National Fire Danger Rating System NFDRS (USA) [9,11]. It estimates the forest fire danger relying on the statistical analysis of large data files about the large forested territories. It considers the anthropogenic impact and thunderstorm activity as the reasons for forest fires to occur. It disregards the factor of the focused solar radiation effect. It uses the remote sensing data. 3. The European Forest Fire Information System EFFIS (Europa) [19]. The most progressive component of this system repeats the subsystem of the Canadian Forest Fire Danger Rating System. It has the same characteristics and uses the remote sensing data. 4. GIS of the National Research Tomsk State University (Russia) [20]. It considers a mathematical model of drying the forest fuel layer. It disregards the ignition processes. The minimal territory is a stratum. It regards the factor of the focused solar radiation effect on the level of statistical estimates (but the forestry management lacks such statistics). It fails to use the remote sensing data. 5. The Virtual Fire System (Greece) [21]. It uses the web-services that reflect the information. It estimates the forest fire danger relying on meteorological data analysis. No data are available about the minimal territory. It disregards the factor of the focused solar radiation effect. It is possible to forecast the forest fire spread process. It fails to use the remote sensing data. 6. The Fire Station (Portugal) [22]. It disregards the reasons for the forest fire to occur. It is possible to forecast the forest fire spread process. It fails to use the remote sensing data.

3. Formulation of Problem and Methods of Its Solution We can define the following problem, which requires solving. It is necessary to detect the forest fire danger under the focused solar radiation effect. The software implementation of this method depends on how operatively we get the estimates of the forest fire danger level [23]. We have developed the method to classify the forest enclosures according to the theoretical and experimental results of modeling the forest fuel ignition processes by the focused solar radiation effect [8]. We have chosen the Timiryazevsky Forestry of Tomsk region as a pilot territory. The Timiryazevsky Mechanized Forestry of the Tomsk Forest Administration is located in the interfluve between two big rivers, the Ob River and the Tom River, on the territory of three administrative districts of Tomsk region – Tomsky, Shegarsky and Kozhevnikovsky districts. The length of the forestry territory from the North to the South is 50 km. The Timiryazevsky forestry was founded in 1966 based on the order of the Ministry of Forestry Management of the Russian Soviet Federated Socialistic Republic dated 08.07-1966 No. 261. The forestry forests are represented mainly by the uniform forest area, except for the isolated cedar forests near Zorkoltsevo, Nizhne Sechenovo and Gubino settlements. By forest and vegetation regionalization of the Western Siberia, the territory of the Timiryazevsky Forestry falls into the Southern Taiga zone (of the Obsko-Tomsky cedar and pine forest district). The forestry territory refers to the mild-humid region according to the agroclimatological zoning of Tomsk region, accepted by the Tomsk Department of the Siberian Institute for the Design of Metallurgical Factories (Sibgipromez). The duration of vegetation period is 120 days. On the forestry territory, the most spread soils are: podzolic and derno-podzolic soils (58%). Sandy and sandy loam soils prevail (99%) by the mechanical composition. Derno-podzolic soils are 37,3%. The wetlands occupy almost 20% of the forestry territory. The prevailing species is pine which occupies 39,6%; aspen is 26,2% and birch is 21,2%; cedar, larch, spruce and silver fir are 13%.

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This article will consider such a meteorological factor as the cloud cover. In physical terms [24] it is clear that, if the clouds shield the Earth’s surface, the amount of radiative solar energy that comes from the sun will be insufficient. In middle latitudes the value of radiative heat flux of natural solar radiation is about 1 kW/m2 [25]. Thus, the geoinformation system can involve the layer, containing the data on the cloud cover over the controlled forested territory, worked out by the Earth remote sensing [23]. The figure 1 shows a typical space image with the thermally anomalous spots using the SatView service interface of the Institute of Computational Technologies of the Siberian Branch of the Russian Academy of Sciences for the Tomsk region territory as of June 01, 2012, 05:36 UTC (Data of State Research Center “Planeta” (SRC “Planeta”). Figure 2 shows a typical space image with the cloud cover mask (June 01, 2012, 05:36 UTC). Terra MODIS 2012/06/0, last update 1327 UTC

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Figure 2. Typical raster with cloud mask


4. Results and Discussion To implement the program, we offer to use the technologies of geographic informational systems that reflect the spatial data. The system offers to use the structure, shown on figure 3. Forest taxation banks of information

RS Data

Program realization of algorithms

Solar concentrators banks Visualization subsystem with geopositioning

Layered visualization of geospatial data Figure 3. GIS Structure

The geographical information system planned to use the Earth remote sensing data from the space. The MхD14 product (Thermal Anomalies/Fire) is one of the real-time resources about the spots of possible thermal anomalies. It is obtained when processing the data from the MODIS sensor aboard the TERRA/AQUA satellites (the MOD14 and MYD14 products correspondingly). These products are made relying on the real-time data obtained in the ranges of 4 micrometers (the MODIS 21 and 22 channels) and 11 micrometers (the MODIS 31 channel). To mask the cloud cover, we use the 1 and 2 channels with resolution of 250 meters (ranges are 0.65 and 0.68 micrometers), as well as the 7 and 32 channels (the spatial resolution of the 7 channel is 500 meters, the range is 2.1 micrometers, the 32 channel has the spatial resolution of 1 km., the range is 12 micrometers). The product documentation [26] and a number of articles [27] describe the detection algorithm in detail. Besides, some fire products of the MODIS sensor have the products that inform about the fire location, the emitted energy, relation of ignition and smoldering, as well as some estimate of the outburned area. The clouds are detected by a method, based on the technology, used when obtaining the global fire product with the help of AVHRR during the International Geo-sphere Biosphere Program (IGBP) [23]. The work [28] used the high resolution data (18 ASTER scenes) for validating the MODIS Thermal Anomalies product over Southern Africa. The ASTER instrument is also located on the Terra satellite platform and allows making investigations, which coincide with MODIS investigations in space and in time. Combination of these data allowed checking the validity of investigation over the active fires. The investigation area was only the Southern Africa territory, but we continue the work to validate the MODIS Thermal Anomalies product on the global level [23]. With the MODIS products, we can have a probability estimate of the cloud cover parameters over the controlled territory. These four conditions specify the cloud cover: clear, may be clear, indefinitely and cloudy. In principle, it is enough to operatively monitor the forest fire danger under the focused solar radiation effect.


5. Conclusion Resulting from this research, we have developed the project of subsystem that reflects the Earth remote sensing data using the MODIS instrument from Terra/Aqua satellite. We offer the method to assess the forest fire danger with regard to the forest area characteristics and atmosphere parameters, in particular, the cloud cover over the controlled territory.

Acknowledgments We have performed the work with the partial financial support by grant from the Russian Foundation for Basic Research (grant 12-07-00545-а) and within the state contract of the Federal Targeted Programme “Researches and developments in priority directions of development of a scientifically-technological complex of Russia on 2007 – 2013”. The state contract No. 14.515.11.0106.

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