Assessment of forest degradation using multitemporal and multisensor very high resolution satellite imagery

The reliable detection of vegetation disease and plant stress are challenges in forest ecosystems. To address this problem, remote sensing existing methods of detection mostly rely on vegetation indices, however, in dense forest, the spectral saturation must be considered to select the most appropriate index. In this work, after a revision of the state of the art, a total of 20 vegetation indices were preliminary selected to perform a thorough statistical analysis with the aim to identify the disease and devitalization phenomena in a complex laurel forest. Multisensor very high resolution imagery, from the same month, with a time difference of a decade have been used. A robust methodology has been implemented to generate accurate vigor maps and to identify the forest areas that have experienced a degradation in plant health after 10 years.