Title :
Forest fire risk zone evaluation based on high spatial resolution RS image in Liangyungang Huaguo Mountain Scenic Spot
Author :
Gao, Xiangwei ; Fei, Xianyun ; Xie, Hongquan
Author_Institution :
Sch. of Geodesy & Geomatics Eng., HuaiHai Inst. of Technol., Lianyungang, China
fDate :
June 29 2011-July 1 2011
Abstract :
Forest fire forecast synthesizes the main weather factors, geography, and degree of wet fuel, fuel types and characteristics of fire source to analyze and predict the forest fuel risk. All fire risk factors were divided into two kinds including stable and changeable factors. In this paper, Huaguo Mountain Scenic Spot in Liangyungang is choosed as study region. Stable fire risk factors, including topography and fuel types were used for forest zone evaluation. Using 10cm Aerial images, based on Forestry Resources surveying, this paper obtained the forestry vegetation type location and their characteristics such as tree height, breast-height diameter, leaves height, and canopy density. In the same time, the digital DEM and various geography factors such as elevation, slope, slope aspect, slope position was obtained by GIS. Based on these geography and fuel types characteristics the study region fire risk zone were divided using clustering analysis. Each fire risk zone has relative conformity in the geography and fuel types and its fire risk rating changing with weather and characteristics of fire source were modelled by Fuzzy multi-level synthetic evaluation. By fire risk zone, short time fire (24 hours) and high spatial resolution forecast would be realized, through further study in the similar region.
Keywords :
digital elevation models; environmental factors; environmental science computing; fires; forestry; fuzzy logic; geographic information systems; remote sensing; risk management; China; GIS; Huaguo mountain scenic spot; Liangyungang; aerial images; breast height diameter; canopy density; changeable forest fire risk factors; digital DEM; elevation; fire source characteristics; forest fire forecast; forest fire prediction; forest fire risk analysis; forest fire risk zone evaluation; forest zone evaluation; forestry resources surveying; forestry vegetation type; fuel types; fuzzy multilevel synthetic evaluation; geography factors; high spatial resolution remote sensing image; leaves height; main weather factors; slope aspect; slope position; stable forest fire risk factors; tree height; wet fuel degree; Fires; Forestry; Fuels; Geographic Information Systems; Meteorology; Surfaces; Vegetation mapping; cluster analysis; fire risk; high spatial aerial images;
Conference_Titel :
Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on
Conference_Location :
Fuzhou
Print_ISBN :
978-1-4244-8352-5
DOI :
10.1109/ICSDM.2011.5969116