Abstract: A smoke detection method is proposed in single-frame video sequence images for forest fire detection in large space and complex scenes. A new superpixel merging algorithm is further studied to improve the existing ho- rizon detection algorithm. This method performs Simple Linear Iterative Clustering (SLIC) superpixel segmentation on the image, and the over-segmentation problem is solved with a new superpixel merging algorithm. The improved sky horizon line segmentation algorithm is used to eliminate the interference of clouds in the sky for smoke detec- tion. According to the spectral features, the superpixel blocks are classified by support vector machine (SVM). The experimental results show that the superpixel merging algorithm is efficient and simple, and easy to program. The smoke detection technology based on image segmentation can eliminate the interference of noise such as clouds and fog on smoke detection. The accuracy of smoke detection is 77% in a forest scene, it can be used as an auxiliary means of monitoringforestfires. A new attempt is given for forest fire warning and automatic detection.
forests [National Geographic, 2001]. For example, tropical rain forests in their natural state, don’t usually burn. Fuel loads are usually low and not highly flammable, and humidity is high even during drought years. In certain parts of Indonesia, heavy logging and slash-and-burn agriculture has been responsible for weakening these rain forest ecosystems. This has been evidenced by the fact that most of Indonesia’s severe forestfires have occurred shortly after long periods of drought [National Geographic, 2001]. A global system for monitoringforestfires could also greatly enhance law enforcement. In certain regions of Brazil, constant aircraft surveillance is used to monitor illegal burning of vegetation. Farmers caught burning open land or stubble after harvest face strict fines or other forms of prosecution. With regards to climate change studies, estimates of trace gas emissions from biomass burning are seriously constrained by the lack of reliable statistics. Little or no data exists on fire distribution and frequency, accurate estimates of area burned, fuel load and fuel content. On a local scale, remote sensing from aircraft offers a cost effective solution for persistent monitoring of wildfire events. However, on a global scale, satellites can readily fulfill the requirement for providing early detection and location of fire; including repetitive coverage, and synoptic data on fire distribution, burned area, vegetation state, and estimates of fire temperature. Regional ecological studies would benefit from accurate multiyear records of the distribution, timing, and frequency of fires. Models of global and regional atmospheric chemistry would be enhanced by reliable information on the source, location and volume of emissions from wild land fires.
Currently there are technologies which allow analyz- ing and characterizing the terrain. GIS technology allows integrating tools for analyzing data for the prevention, planning and management of forestfires . One of these applications is the analysis of visual basins. Several authors have recognized that the modern scientific tech- nologies and procedures facilitate the development of techniques for detecting and monitoringforestfires, characterized by a combination of geographic informa- tion systems and spatial data on forestfires [4,5]. Ac- cording to  various geographical conditions must be evaluated, as the positions that maximize visual coverage, taking into account that the areas of high-altitude should be included.
In this work a mathematical approach based path planning of actor which uses equation of a straight line passing through two points is proposed to extinguish forestfires. Forest domain is considered as a square area and is tessellated into n x n cells (small squares) of desired size. The Actor which performs actions similar to the actions performed by a robot is assumed to be available at one cell which is considered as one point and the cell in which fire occurs is considered as the second point. The equation of straight line is found out using these two points. Then using the straight line equation the sequence of intermediate cells between the cell where the Actor is available and the cell where the fire is occurred is computed and stored in memory. Then a check is made for presence of obstacle in the intermediate cells. If there are obstacles present then a cell without obstacle and also nearer to obstacle cell is found out and replaced in the memory. Integrity check is performed to make sure that successive points are incremental points. i.e. whether the next point can be reached in one move. Then the sequence of points stored in the memory is used by the Actor to move to the cell where fire is occurred and after reaching that cell the actor will start to extinguish fire. Computer simulation results shows that the algorithm works well in all aspects for environment with and without obstacles and it computes the path for the actor to extinguish Forest fire without collision with obstacles.
Forestfires of natural origin are most commonly caused by lightning and electrical storms, particularly when they are unaccompanied by rain. However, they can also be as a result of anthropogenic causes; i.e., fires due to human activities in the mountains and forests, arising either from failure to take necessary precautions or from accidents. Misuse of the forests has caused thousands of hectares to be razed in forestfires. Human action, without a doubt, causes the majority of forestfires in Puerto Rico. These fires are generated by carelessness or negligence in handling heat sources in the presence of combustible vegetation. The majority of forestfires on the island of Puerto Rico occur primarily in three months of the year as a result of various types of human inter- ventions, some of which are even criminal.
Forestfires are one of the most important threats for forests in the State of Mexico. Therefore, understanding their geographical patterns is a priority for the design of forest management strat- egies. We processed the records obtained with the MOD14A2 product (for thermal anomalies and fire) of MODIS sensor. Such scenes correspond to dry seasons (from March 15 to June 30) from 2000 to 2012 in the State of Mexico. We analyzed such records in a GIS environment to learn their spatial patterns and establish their geographical correlations as a first step to understand the causal agents of forestfires. As a result, forestfires in the State of Mexico showed a clustered spa- tial trend with a southwest tendency and a slight spatial relation with total winter precipitation and maximal temperature in summer.
Forestfires in Uttrakhand have been regular and historic feature. Every year forestfires in Uttrakhand causes great loss to the forest ecosystem, diversity of flora and fauna and economic wealth. Forest fire is one of the major disasters in the forests of Uttarakhand. High temperatures with no atmospheric moisture were one of the important reason for forestfires in Uttrakhand. Remote sensing and GIS technology that has been used to detect forestfires and recent technology can send an early warning to prevent forestfires. Remote sensing has also been effectively used in the study monitoring, detection of forest fire and future planning. Thus the main aim of this study is the causes and where the forest fire takes place by preparing fire events density map on the bases of using Remote Sensing real time forest fire data from EOSDIS NASA and GIS techniques. The various parameters are taken in to account land use from BHUVN, forest type map, relief and slope. Later on to analyze the causes these aspects were compared with fire density map. Topography, slope and types of vegetation play important role in the spread of forest fire. Outcome of the study demonstrate that the proximity to inhabited places, dry climatic conditions and dry Chir pine forest cover are mainly responsible forest fire in the state. These types of studies are helpful to suggest preventive measures in different risk areas of Uttrakhand.
The forest is considered to be the one of the most indispensable resources and the fatal threat to forests is forestfires. It is widely reported that a total of 77,534 wildfires burned 6,790,692 acres in USA during 2004 . Hence it is necessary to carry out research activities to detect and extinguish fires to preserve valuable resources and environment. The best method to detect h fires is by fire modeling because we can understand and predict possible fire behavior without getting burned . In olden days fire detection is carried out by visual inspection of large areas with coverage radius of up to 20 km and daily walk through predefined paths during fire season by fire department personnel . In the literature most of the forest fire detection mechanisms are based on satellite images .But the long scan period and low resolution of satellite images reduces the effectiveness of satellite based forest fire detection mechanisms. In order to overcome the difficulties associated with satellite image based detection mechanisms many works have been reported in the literature using wireless sensor networks [5, 6]. But most of the works are concerned only with detection mechanisms and message will be sent to sink / gateway/internet and actions will be taken separately. In  a cluster based
Wireless sensor network has great impact on industry and our daily life, and this paper designs a monitoring system for forestfires based on wireless sensor network and GPS network. Our system is able to fairly accurately distinguish different forest fire scenarios and accurately determine the direction of growth of fire. This system with the advantages of real-time, low power, high reliability, remote control and so on, has a broad application prospect in forest fire monitoring.
The number of fire occurrences per 100 km 2 (10 000 ha) of forested area was determined for each ecoregion section in the conterminous United States (Cleland and others 2007) and Alaska (Nowacki and Brock 1995) for 2010. This forest fire occurrence density measure was calculated after screening out wildland fires on non-forested pixels using a forest cover layer derived from MODIS imagery by the Forest Service Remote Sensing Applications Center (USDA Forest Service 2008). The total number of fire occurrences across the conterminous States and Alaska was also calculated. The same approach was used to calculate the mean number of annual fire occurrences, per 100 km 2 (10 000 ha) of forested area, by ecoregion section for the first 10 full years of MODIS Active Fire data collection (2001-10).
The simulated concentrations of particles less than 2.5 μm diameter (PM2.5), AOD, total and diffuse radiation, and gross primary productivity (GPP) were evaluated using observations across the Amazon. The PM2.5 measurements were made using gravimetric ﬁlter analysis at two ground stations in Brazil: Balbina (1.917°S, 59.487°W; October 1998 to May 2003), a remote forest site in central Amazonia, and Porto Velho (8.687°S, 63.866°W; September 2009 to December 2011), a heavily biomass burning impacted site in southwestern Amazonia. Measurements of AOD at 500 nm were made using Sun-sky scanning spectral radiometers at four stations in the Aerosol Robotic Network (AERONET): Rio Branco, Alta Floresta, and Cuiabá-Miranda in Brazil and Santa Cruz in Bolivia. These sites are strongly inﬂuenced by biomass burning emissions in the dry season [Hoelzemann et al., 2009]. We used Level 2 data available between 1998 and 2008, with all years of data available at Alta Floresta and Santa Cruz, ~7 years at Cuiabá-Miranda, and ~8 years at Rio Branco. At Caxiuana, Brazil (1.738°S, 51.453°W), total and diffuse radiation observations [Butt et al., 2010] have been collected every 2 min between March 2005 and August 2006, using a BF3 sunshine sensor [Wood et al., 2003] (Delta-T Devices, Cambridge, UK), located at a height of 50 m, about 20 m above the top of the forest canopy. At Tapajos, Brazil (2.857°S, 54.959°W), total and diffuse radiation were measured using a BF3 sunshine sensor (2004 – 2006), and C ﬂuxes were measured using a close-path eddy covariance (EC) system [Saleska et al., 2003; Restrepo-Coupe et al., 2013]. The high-frequency ﬂux data were averaged to hourly values for the January 2002 to January 2006 period. The EC sensor is placed at a height of 63 m over a height of 35 – 40 m evergreen forest canopy. At Guyaﬂux, French Guiana (5.280°N, 52.926°W), total and diffuse radiation were measured using a BF3 sunshine sensor and GPP data calculated using eddy ﬂux data [Bonal et al., 2008] collected every 30 min between January 2007 and December 2009, at a height of 57 m (approximately 22 m above the canopy height) from an undisturbed mature evergreen broadleaf tropical wet ecosystem (for the GPP observations, only measurements between 9 A.M. and 5 P.M. local time were used).
Nearly all of the HBS sites measured during our 2017 field surveys of the Tanana Area Fires had no live surface organic layers remaining. Intense fires during summer of 2015 consumed between 5 and 10 cm of the former live surface organic layer and left behind only a residual dead, charred moss and lichen cover about 3–5 cm deep that had little capacity to insulate the soil layers beneath. We observed that the blackened surface organic layer showed a tendency to be 2–4 °C warmer than the live moss layer under unburned spruce forest strata. These results are consistent with those of Jiang et al.  and Brown et al. , who reported that post-fire thickness of the soil organic layer and its impact on soil thermal conductivity was the most important factor determining post-fire soil temperatures and thaw depth.
Cleland, D.T.; Freeouf, J.A.; Keys, J.E., Jr. [and others]. 2007. Ecological subregions: sections and subsections for the conterminous United States. Sloan, A.M., tech. ed. Gen. Tech. Report WO-76. Washington, DC: U.S. Department of Agriculture Forest Service. Map, presentation scale 1:3,500,000; Albers equal area projection; colored. Also as a GIS coverage in ArcINFO format on CD-ROM or at http://fsgeodata.fs.fed.us/other_resources/ecosubregions. html. [Date accessed: March 18, 2011].
for forestfires by Ohlson and Tryterud (2000), and Acacia and Pinus species in 0.26 g of BC per Petri dish, an adequate amount considering the size of the Petri dishes. Initially, 10 ml of distilled water was added to the Petri dishes, with additional water being applied periodical- ly (at the same time as the determination of germination parameters) to keep the seeds moist (assuring that at least one-third of its surface was in contact with water). Germina- tion was counted every Monday, Wednesday, and Friday during the germination period of each species. A seed was considered to have germinated when its radicle had extended be- yond the teguments by at least 1 mm (Côme 1970). The experiments took place spanning a period of several years and some treatments were not applied to all species (Table 1). The data obtained were used to calculate the ger-
(SSPMNP), which supports the largest area of YPMC forest in Baja Califor- nia, to determine whether fire severity is rising over the last three decades in the same manner that it is rising in the Sierra Nevada of Alta California. We used LANDSAT data to identify 32 fires that burned 26 529 ha in the Sierra de San Pedro Mártir National Park in the period 1984 to 2010. Of this, 1993 ha burned in YPMC forest types in 17 fires. We found no temporal trends in forest burned area or in the proportion of high severity fire, but we did find that the mean size of high severity patches within fires is rising. In the SSPMNP, the overall proportion of fire area burned at high severity averaged 3 % in both yellow pine and mixed co- nifer forests. We found no significant autoregressive effects of year in any of our analyses, but the year with the most burned area occurred after dri- er-than-average periods. In the SSPMNP data, there was no correla- tion between burned area and propor- tion of high severity fire; we interpret- ed this to mean that differences in fuels in SSPMNP were more important to fire behavior than weather conditions. The SSPMNP continues to burn at very low severities, even after 30 years of effective suppression of lightning-ig- nited fires. This is in stark contrast to similar forests in Alta California, which are experiencing fires of sizes and severities that fall far outside the historical range of variation. Current fire severities in the SSPMNP are very similar to the levels of severity de- scribed for Alta California YPMC for- ests before Euro-American settlement. Nonetheless, fire suppression policies in Mexican national parks in northern Baja California are causing increases in forest fuels and may be the cause of
A simple approach to the assessment of the level of forest opening-up has been introduced from the aspect of terrain accessibility for the available mobile fire apparatus with the use of GIS and GNSS technologies. First, the forest road network was mapped using the GNSS technology, and then the information on the quality of particular roads was collected. These data were processed in the ArcGIS 9.3 environment and as a result the geodatabase was created. It was later used to process the opening-up analysis in IDRISI Taiga environment. The opening-up analysis was performed for the Hrabusice forest management district, located in the karst area of the Slovensky raj National Park and the available mobile fire apparatus – pumping appliance CAS 32 on Tatra 148 chassis and forest special UNIMOG on Mercedes chassis.
Abstract: A study that was aimed to identify the impact of forestfires on the biological properties of soils was carried out at former forest fire areas in Samosir Regency of North Sumatera. Soil samples were collected from former forest fire areas of 2014, 2013, 2012, 2011, 2010. The composite soil samples were collected systematically using diagonal method as much as 5 points in each period of fire. The soil samples were taken at three plots measuring 20 x 20 m 0-20 cm depth. Soil biological properties observed were soil organic C content, total number of microbes, abundance of arbuscular mycorrhizal fungi, phosphate solubilizing microbes, and soil microbial activity. The results showed that organic C content ranged from 0.75 to 2.47% which included criteria for very low to moderate. Arbuscular mycorrhizal fungi spores were found belonging to the genus of Glomus and Acaulospora. Spore number increased with the fire period ranging from 45 spores (forest fire in 2014) to 152 spores (forest fire in 2010). The total number of microbes obtained ranged from 53.78 x 10 7 cfu/mL (forest fire in 2010) to 89.70 x10 7 cfu/mL (forest fire in 2013). It was found 29 isolates of phosphate solubilizing microbes that consisted of 14 bacterial isolates and 15 fungi isolates with densities ranging from 27.642 x10 5 cfu/mL (forestfires in 2014) to 97.776 x 10 5 cfu/ mL (forestfires in 2011). The isolates of phosphate solubilizing bacteria identified consisted of Pseudomonas, Flavobacterium, Staphylococcus, and Mycobacterium genus, whereas the isolates of phosphate solubilizing fungi obtained consisted of Aspergillus and Penicillium genus. Soil respiration ranged from 2.14 kg / day (forest fire in 2010) up to 3.71 kg / day (forest fire in 2013). The varied results were greatly influenced by the type or form of the fires and intensity of fires. In the study area the type or form of the fires were canopy fires with low intensity.
Although the mere use of the abundance of species, without their processing binary data (presence / absence) could lead to consistent results we share the idea that Christophe Coudun (2005), like many other authors think that to link the ecological behavior of forest species measured ecological factors, will increase our knowledge of the species autoecology (Schaffers and Sykora 2000, Wamelink et al., 2002) quoted by Christophe Coudun (2005). The ecological behavior of eight species in four regions along a gradient from central Europe to northern Europe was studied by Diekmann and Lawesson (1999); the results of their work has shown that some species could be of optimum ecological changes in different regions; So we believe that our work should be as interesting if we had made in several areas. However, it would be better to make a second work that can be carried by comparing examples of our search with the existing literature.
The first group of questions concerned the awareness of respondents about the phenomenon of forestfires in both environmental and social level and their sensitivity towards the environmental issues. In the question that asked for the meaning of the term environmental damage, the majority of respondents representing the 62 % stated that they did not know the answer while fully aware of the issue appeared to be only the 24% and partial knowledge of the issue had the remaining 14%. Although the percentages of respondents who appeared to have knowledge of the concept of environmental destruction driven low, the results relating to the theme of knowledge of respondents about forest destruction and environmental sensitivity in general could be considered high. Specifically, in the question that asked what was the impact of forestfires in the environment, the majority of respondents representing the 84% clearly stated that the fire constitutes a parameter that directly affects the environment and even heavily, followed by a rate of 14% who believes that forestfires significantly affect the natural environment. Only the 2% of respondents answered that the phenomenon of forestfires affect less the environment. In addition, the majority of respondents not only felt that wildfires significantly affect the environment, but also the 96% of them linked the phenomenon of forestfires with the environmental destruction when asked if there is a potential connection between the wildfires and the environmental damage. Just a very small percentage of around 4 % reported that they did not know the answer to this question (see Figure 1).