32nd International Symposium on Remote Sensing of Environment
June 25 – 29, 2007
San Jose, Costa Rica
En este Simposio, el Dr. Germán Flores participó como ponente, presentando el tema “Spatial distribution of forest fuels based on classification and regression trees”. (La información compartida, está en inglés).
Abstract – Fire management planning require of a precise information of quantity and quality of many factors, such as forest fuels. Moreover, it is important to know fuels location and the spatial variation of fuel loads. Many direct and indirect techniques have been tested, some of the work with ancillary information, such as satellite imagery. In fact satellite imagery has become a practical alternative to classify land covers, with a acceptable level of accuracy, which is strongly related to forest fuels. We also count with spatial information of topography, climate, altitude, soil, etc, which can used to define spatial distribution of forest fuels. This paper illustrate the use a classification and regression trees (CART), to spatially model forest fuel distribution. The study area is located at the central part of Jalisco state. The results showed a good accuracy in the spatial estimation of fuels loading.
Abstract – Fire management planning require of a precise information of quantity and quality of many factors, such as forest fuels. Moreover, it is important to know fuels location and the spatial variation of fuel loads. Many direct and indirect techniques have been tested, some of the work with ancillary information, such as satellite imagery. In fact satellite imagery has become a practical alternative to classify land covers, with a acceptable level of accuracy, which is strongly related to forest fuels. We also count with spatial information of topography, climate, altitude, soil, etc, which can used to define spatial distribution of forest fuels. This paper illustrate the use a classification and regression trees (CART), to spatially model forest fuel distribution. The study area is located at the central part of Jalisco state. The results showed a good accuracy in the spatial estimation of fuels loading.
Autor (es): INIFAP.