SAR interferometric signatures of forest

The potential of SAR interferometry for forest mapping and monitoring is discussed. It is shown that forest can clearly be discriminated from other land categories. Furthermore it is possible to distinguish a number of forest types. The presented approach is based on the SAR interferometric correlation and the backscatter intensities using ERS-1 SAR repeat-pass data. Baseline, time interval, and seasonal dependences were analyzed, substantiating a wide applicability of the approach. Data over an Alaskan test site were used to extend the results found over temperate forest to boreal forest and to demonstrate the potential of the described technique over remote areas. In addition, repeat-pass SAR interferometry was found to be particularly sensitive to change. Examples for the recognition of freezing, mechanical cultivation of agricultural fields, and canopy growth are shown