Target detection of mine-related flooded areas using AISA-eagle data

• Published in: 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) pp. 1 - 4
• Main Authors: Garcia Millan, Virginia E., Pakzad, Kian, Faude, Ulrike, Teuwsen, Sebastian, Muterthies, Andreas
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2014
• Subjects: Flooding; Hyperspectral; Mining; Risk Assessment; Vegetation
• ISSN: 2158-6276
• DOI: 10.1109/WHISPERS.2014.8077548

The present research is developed in the frame of the R&D project GMES4Mining, which aims to support particular tasks within the different phases of a mining life cycle [1]. During the exploitation and after the closure of the mine, environmental and civil impacts may happen, due to changes in the compacting properties of the soil related to mining activities. In this paper, we focus in the emergence of flooded areas, due to a subsidence of the ground surface. Above-ground vegetation is affected by changes in groundwater's dynamics; at first trees suffer defoliation and senescence, and after some time, they die. Several methods have been tested, to detect changes in spectral response of forests in a mine area, which are related to imminent flooding. ENVI's Target Detection Tool has been used to estimate the reflectance proportion at pixel level of four targets of interest in AISA-Eagle's data, which are present in flooded areas: water, dead trunks, senescent trees and green stands within water. Five target detection's methods have been tested: Constrained Energy Minimization (CEM), Adaptative Coherence Estimator (ACE), Spectral Angle Mapper (SAM), Target-Constrained Interference-Minimized Filter (TCIMF) and Mixture Tuned Matched Filtering (MTMF).