The book provides a systematic review of the different applications for remote sensing and geographical information system techniques in research and management of forest fires. The authors have been involved in this field of research for several years. The book also benefits from data generated within the Megafires project, founded under the DG-XII of the European Union. A clear integration of research and experience is provided. New data gathered from fires affecting European countries between 1991 and 1997 are included as well as satellite images and auxiliary cartographic information. Geographic Information System files have been included in the attached CD-ROM depicting land cover, elevation, Koeppen classification climates and NOAA-AVHRR data of all European Mediterranean Europe at 1 sq km resolution. All these files are in Idrisi format and can be easily accessed from any GIS program. An Idrisi viewer has also been included in the CD-ROM.

Table of Contents:
1 Introduction.- 2 The role of fire In European Mediterranean ecosystems.- 2.1 Introduction.- 2.2 Fire history.- 2.2.1 Statistics.- 2.2.2 Land-use changes.- 2.2.3 Climate change.- 2.3 Fire effects on soils.- 2.4 Post-fire regeneration of vegetation.- 2.4.1 Plant traits.- 2.4.2 Environmental conditions.- 2.4.3 Prediction of long-term effects.- 2.5 Concluding remarks.- 3Short-term fire risk: foliage moisture content estimation from satellite data.- 3.1 The role of foliage moisture content in the short-term estimation of fire danger.- 3.2 The estimation of foliage moisture content.- 3.3 The effect of moisture content on reflectance and temperature.- 3.4 The use of low resolution data for foliage moisture estimation.- 3.5 Application of NOAA-AVHRR to FMC estimation.- 3.5.1 Study areas.- 3.5.2 Satellite data processing.- 3.5.3 Results on Chalkidiki study area.- 3.5.4 Results on Cabaneros study area.- 3.5.5 Results on Les Maures study area.- 3.5.6 Results on ONF land plots.- 3.5.7 Discussion.- 3.5.8 Conclusion.- 3.6 Foliage moisture assessment using high resolution data.- 4 Meteorological fire danger indices and remote sensing.- 4.1 Introduction.- 4.2 Processes and components embodied in fire danger indices.- 4.3 Meteorological fire danger indices.- 4.4 Large fire danger rating with meteorological indices in the European Mediterranean Basin.- 4.4.1 Databases and danger indices.- 4.4.2 Climatic stratification.- 4.4.3 Logistic regression.- 4.4.4 Assessment of the logistic model.- 4.5 Satellite data and meteorological danger indices.- 4.5.1 Satellite data and the logistic model for large fire danger rating...- 4.5.2 Estimation of long-term fire danger indices from satellite data...- 5 Integrated fire risk mapping.- 5.1 Temporal and spatial scales in fire risk mapping.- 5.2 The use of GIS in fire risk assessment.- 5.2.1 Description of geographical variables of fire risk.- 5.2.2 Criteria to integrate forest fire danger variables.- 5.3 Analysis of long-term fire risk on a European level.- 5.3.1 Introduction.- 5.3.2 Selection of risk variables.- 5.3.3 Techniques to estimate large Fire occurrence.- 5.3.3.1 Logistic Regression.- 5.3.3.2 Linear Regression.- 5.3.3.3 Artificial Neural Networks.- 5.3.4 Conclusions.- 5.4 Examples of local-scale risk analysis.- 5.4.1 Proposal of a local-risk index.- 5.4.2 Application at local level.- 6 Fire detection and fire growth monitoring using satellite data.- 6.1 Introduction.- 6.2 Basis for fire detection from satellite data.- 6.3 General issues related to remote sensing of active fires.- 6.3.1 Temporal issues.- 6.3.2 Thermal sensitivity issues.- 6.3.3 Spatial issues.- 6.3.4 Other problems related with satellite fire observation and detection.- 6.4 Active fire detection with NOAA-AVHRR images.- 6.4.1 Channel 3 single threshold algorithms.- 6.4.2 Multi-channel threshold algorithms.- 6.4.3 Contextual algorithms.- 6.4.4 Sub-pixel fire detection algorithm.- 6.4.5 Additional issues.- 6.5 Fire growth monitoring using AVHRR images.- 6.6 Future systems.- 6.7 Conclusions.- 7 Spectral characterisation and discrimination of burnt areas.- 7.1 Introduction.- 7.2 Spectral properties of burnt areas.- 7.2.1 Visible (0.4 - 0.7 m).- 7.2.2 Near-infrared (0.7 - 1.3 m).- 7.2.3 Mid-infrared (1.3 - 8.0 m).- 7.2.4 Thermal infrared (8.0 - 14.0 m).- 7.2.5 Microwave (> 1 mm).- 7.2.6 An overview of the characteristics of burnt surfaces using Landsat 5 TM imagery.- 7.2.6.1 Spectral properties and colour composites.- 7.2.6.2 Fire-induced spectral changes and vegetation recovery...- 7.3 Conclusions.- 8 Regional-scale burnt area mapping in southern Europe using NOAA-AVHRR 1km data .- 8.1 Introduction .- 8.2 Methods for burnt land mapping.- 8.3 Mapping burnt areas in southe rn Europe from NOAA-AVHRR data.- 8.3.1 Data and methods.- 8.3.2 Results.- 8.4 Discussion and conclusions.- 9 Burnt land mapping at local scale.- 9.1 Introduction.- 9.2 Scale issues in burnt land mapping.- 9.3 Operational burnt land mapping in Mediterranean landscapes.- 9.3.1 Structure of the Mediterranean landscape.- 9.3.2 Methodological approaches for burnt land mapping.- 9.3.3 Advantages of using high resolution sensors.- 9.4 Techniques for burnt land mapping.- 9.4.1 Overview.- 9.4.2 Description of the techniques.- 9.4.2.1 Principal component analysis.- 9.4.2.2 Spectral mixture analysis.- 9.4.2.3 Logistic regression modeling.- 9.4.2.4 Intensity-Hue-Saturation transformation.- 9.4.2.5 Other techniques.- 9.5 Discrimination of damage intensities.- 9.5.1 Interest of discriminating damage intensities.- 9.5.2 Description of the techniques.- 9.5.2.1 Vegetation Indices thresholding.- 9.5.2.2 Unsupervised classification: segment-based classification.- 9.5.2.3 Supervised classification.- 9.6 Epilogue.- References.