Product details
- ASIN : B00086E97G
- Publisher : Louisiana State University (January 1, 1938)
- Language : English

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UK ed. Edition
by Eduards Gomez (Author, Editor), Kristina Alvarez (Editor)
A forest fire is any uncontrolled, non-structure fire that occurs in the wilderness. Wildlife behavior is often complex and variably dependent on factors such as fuel type, moisture content in the fuel, humidity, wind speed, topology, geographic location and ambient temperature. Weather patterns, such as heat waves droughts can also have a dramatic impact on the onset and outcome of wildfires. Fire is sometimes essential for forest regeneration, however, it often destroys forests and has dire social and economic consequences. This book looks at the underlying causes of forest fires, their ecological effects and preventive strategies.Hardcover – April 1, 2002
by John Suiter (Author)
Based on unpublished letters, journalists, and interviews, this new look at the Beats focuses on the Western experiences of these seminal American writers. 25,000 first printingHardcover – January 1, 2004
Spanish Edition by J. Y OTROS ARNALDOS VIGER (Author)
Paperback – July 8, 2011
by Tawanda Manyangadze (Author)
Remote sensing has been widely used in active forest fire detection; however there are some limitations in the operational contextual algorithms. These algorithms are greatly affected by clouds and different land cover types such as land and water with inherent temperatures. This book, therefore, provides a new multi-temporal threshold algorithm for near real-time forest fire detection using geostationary satellites, supplemental to the existing algorithms. This algorithm is based on temperature in IR3.9 channel and the difference between IR3.9 and IR10.8 channels. The multi-temporal threshold algorithm proved to have higher fire detection rate (50%) as compared to MSG FIR-G (3.7%) when ground data from Portugal was used for validation. This superiority was also confirmed over Southern Africa when MODIS fire product was used for validation. This analysis shows the possibility of manipulating the temporal domain of geostationary satellites in monitoring highly temporal environmental phenomenon. This algorithm could be especially useful to professionals in forest fire management, or anyone else who may be interested in applying geostationary satellites in environmental monitoring.
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