Fire, a phenomenon occurs in most parts of the world and causes severe financial losses, even, irreparable damages. Many parameters are involved in the occurrence of a fire; some of which are constant over time (at least in a fire cycle), but the others are dynamic and vary over time. Unlike the earthquake, the disturbance of fire depends on a set of physical, chemical, and biological relations. Monitoring the changes to predict the occurrence of fire is efficient in forest management. Method: In this research, the Persian and English databases were structurally searched using the keywords of fire risk modeling, fire risk, fire risk prediction, remote sensing and the reviewed papers that predicted the fire risk in the field of remote sensing and geographic information system were retrieved. Then, the modeling and zoning data of fire risk prediction were extracted and analyzed in a descriptive manner. Accordingly, the study was conducted in 1995-2017. Findings: Fuzzy analytic hierarchy process (AHP) zoning method was more practical among the applied methods and the plant moisture stress measurement was the most efficient among the remote sensing indices. Discussion and Conclusion: The findings indicate that RS and GIS are effective tools in the study of fire risk prediction.

Every year, hundreds of fires occur in the forests and rangelands across the world and damage thousands hectare of trees, shrubs, and plants which cause environmental and economic damages. This study aims to establish a real time forest fire alert system for better forest management and monitoring in Golestan Province. In this study, in order to prepare fire hazard maps, the required layers were produced based on fire data in Golestan forests and MODIS sensor data. At first, the natural fire data was divided into two categories of training and test samples randomly. Then, the vegetation moisture stresses and greenness were considered using six indexes of NDVI, MSI, WDVI, OSAVI, GVMI and NDWI in natural fire area of training category on the day before fire occurrence and a long period of 15 years, and the risk threshold of the parameters was considered in addition to selecting the best spectral index of vegetation. Finally, the model output was validated for fire occurrences of the test category. The results showed the possibility of prediction of fire site before occurrence of fire with more than 80 percent accuracy.

The management of Mediterranean mountains need to know whether or not the flora is adapted to respond to fire and, if so, through what mechanisms. Serpentine outcrops constitute particular ecosystems in the Mediterranean Basin, and plants need to make an additional adaptive effort. The objective of this study is to know the response to fire of the main members of the group of serpentine plants, which habit the Spanish Mediterranean ultramafic mountain, to help in their management. For this purpose, monitoring plots were established on a burned ultramafic outcrop, which was affected by fire in August 2012.They were located in the Mediterranean south of the Iberian Peninsula, Andalusia region. The dominant vegetation of this serpentine ecosystem had been studied previously to fire; it was a shrubland composed of endemic serpentinophytes (small shrubs and perennial herbs) included in Digitali laciniatae-Halimietum atriplicifolii plant association (Cisto-Lavanduletea class) in an opened pine forest. The post-fire response of the plants was studied in the stablished burned plots by field works through permanent 200 x 10 m transect methods, consisting on checking whether they were resprouters, seeders, both of them or if they showed no survival response. Additional information about fire related functional traits is provided for the studied taxa from other studies. Of the total of plants studied (23 taxa), 74% acted as resprouters, 30% as seeders, some of which also had the capacity to resprout (13%), and only 9% of the plants did not show any survival strategy. The presence of a resprouting burl was not high (17%), although serpentine small shrubs such as Bupleurum acutifolium and the generalist Teucrium haenseleri had this kind of organ. The herbaceous taxa Sanguisorba verrucosa, Galium boissieranum and Linum carratracense were seen to be resprouters and seeders. The serpentine obligated Ni-accumulator, Alyssum serpyllifolium subsp. malacitanum, did not show any survival strategy in the face of fire and therefore their populations need monitoring after fires. In the studied ecosystems no species had traits that would protect the aerial part of the plant against fire, although most of the species are capable of post-fire generation by below ground buds. Our results show that the ecosystem studied, composed of taxa with a high degree of endemism and some of them threatened, is predominantly adapted to survival after a fire, although their response capacity may be decreased by environmental factors.

Fire is one of the most serious hazards, which causes many economic, social, ecological, and human damages every year in the world. Fire in forests and natural ecosystems destroys wood, regeneration, forest vegetation, as well as soil erosion and forest regeneration problems (due to the dryness of the weather and the weakness of the soil). Awareness of the extent of the zones that have been fired is important for forest management. On the other hand, the difficulty of fieldwork due to the high cost and inaccessible roads, etc. reveals the need for using remote sensing science to solve this problem. In this research, MODIS satellite images were used to detect and determine the fire extent of Golestan province forests in northern Iran. MID13q1 and MOD13q1 images were used to detect the normal conditions of the environment. The 15-year time series data were provided for the NDVI and NDMI indicators in 2000-2015. Then, the behavior of indicators in the fire zone was studied on the day after the fire. The burned zones by the fire were specified by determining the appropriate threshold and then, they were compared to long-term normals. In the NDMI and NDVI indicators, the mean of the numeric value threshold limit for determining the burnt pixels was respectively 1.865 and 0.743 of the reduction in their normal long-term period, which are selected as fire pixels. The results showed that the NDMI index could determine the extent of the burned zone with the accuracy of 95.15%.