Evaluation of a new satellite-based method for forest fire detection

Citation
V. Cuomo et al., Evaluation of a new satellite-based method for forest fire detection, INT J REMOT, 22(9), 2001, pp. 1799-1826
Citations number
42
Categorie Soggetti
Earth Sciences
Journal title
INTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN journal
01431161 → ACNP
Volume
22
Issue
9
Year of publication
2001
Pages
1799 - 1826
Database
ISI
SICI code
0143-1161(20010615)22:9<1799:EOANSM>2.0.ZU;2-6
Abstract
Advanced Very High Resolution Radiometer (AVHRR)-based fire detection metho ds are considered in this work in order to assess their effective usefulnes s in the framework of civil programmes for fire risk and damage mitigation. The discussion is divided into the evaluation of the most commonly used me thods and the description of a new fire detection procedure which is propos ed in this paper. Commonly used detection methods are based on using absolu te threshold values for decision tests. These values usually match only wit h very local, uniform (in space and time) situations, and are often inadequ ate when applied to heterogeneous, or simply different, geographical areas or seasons. A high number of false alarms, so high as to make the satellite -based product not operationally utilizable, is the main disadvantage of th e fixed-threshold approach. The new fire-detection procedure proposed here makes use only of historical AVHRR data in order to automatically produce l ocal(in space and time) threshold values, suitable for fire-event detection also in very critical situations. High fire discrimination capabilities wi th low false-alarm rates, simple unsupervised implementation and, above all , flexibility for automatic extension to completely different geographic ar eas and observation conditions, are the main advantages associated with thi s new technique. Results obtained for different Italian areas have been suc cessfully compared with ground observations made by the Italian Forestry Se rvice. Tests made over a long observation period show that, on cloud-free r egions, more than 75% of significant forest fires are detected with less th an 20% of false alarms.