6 September 2017 Remote sensing techniques in monitoring areas affected by forest fire
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Proceedings Volume 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017); 104440Q (2017) https://doi.org/10.1117/12.2277700
Event: Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 2017, Paphos, Cyprus
Abstract
Forest fire is a part of nature playing a key role in shaping ecosystems. However, fire’s environmental impacts can be significant, affecting wildlife habitat and timber, human settlements, man-made technical constructions and various networks (road, power networks) and polluting the air with emissions harmful to human health. Furthermore, fire’s effect on the landscape may be long-lasting. Monitoring the development of a fire occurs as an important aspect at the management of natural hazards in general. Among the used methods for monitoring, satellite data and remote sensing techniques can be proven of particular importance. Satellite remote sensing offers a useful tool for forest fire detection, monitoring, management and damage assessment. Especially for fire scars detection and monitoring, satellite data derived from Landsat 8 can be a useful research tool. This paper includes critical considerations of the above and concerns in particular an example of the Greek area (Thasos Island). This specific area was hit by fires several times in the past and recently as well (September 2016). Landsat 8 satellite data are being used (pre and post fire imagery) and digital image processing techniques are applied (enhancement techniques, calculation of various indices) for fire scars detection. Visual interpretation of the example area affected by the fires is also being done, contributing to the overall study.
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Aikaterini Ch. Karagianni, Aikaterini Ch. Karagianni, Maria A. Lazaridou, Maria A. Lazaridou, } "Remote sensing techniques in monitoring areas affected by forest fire", Proc. SPIE 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 104440Q (6 September 2017); doi: 10.1117/12.2277700; https://doi.org/10.1117/12.2277700
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