ERS INSAR data for remote sensing hilly forested areas

ERS INSAR data have proved to be of interest for forest applications. The interferometric coherence was found to be related to various land uses and forest types, while in some special cases (e.g., flat terrain) the interferometric phase has been linked to the forest height. This paper reports an investigation on the information content oft he interferometric coherence over a hilly terrain supporting various land use types and large pine plantations. The approach includes the rise of a Geographic Information System and multitemporal data to analyze the coherence behavior as a function of forest-type forest parameters and environmental factors such as meteorological and topographic effects. Coherence appears to be efficient to discriminate between forest types. However, topography and environmental conditions strongly affect the coherence and its estimation, pointing out the need for rejection of strong slopes areas (>15 degrees) and the sensitivity to local meteorological/seasonal effects. Based on these observations, forest classification results are presented. Forest/nonforest discrimination is very efficient (accuracy >90%) using one-clay interval acquisition. More detailed classification with discrimination between forest themes gives also good results. Then, we investigate the indirect link between coherence and forest parameters. The coherence is sensitive to the forest growth stage, making forest parameter retrieval possible using a simple straight-line model. Finally, the importance of wind upon temporal decorrelation is addressed and a semiempirical correction is proposed. (C) Elsevier Science Inc., 2000.