Monitoring of forest health using spectral unmixing of multispectral satellite data

Forests play an important role in global carbon, hydrological and atmospheric cycles. Current environmental issues have a strong impact on forest health. Satellite remote sensing is widely used for forest state monitoring due to increasing availability of satellite data and high temporal resolution. However, a spatial resolution of satellite data is often insufficient to detect small areas of forest drying. For a clearer detection of affected forest areas, spectral unmixing is required.

The results of spectral unmixing of Belarusian spacecraft data (4 bands: blue, green, red, NIR; spatial resolution 10 meters) are performed. To detect affected forest areas that need to be specified, the vegetation index NDVI is calculated. Then, spectral mixture analysis is running for these areas. The library of endmembers (pure spectral signatures) was created by ground measurements using spectral instruments that were developed in the department of aerospace researches of Belarusian state university. Comparison of spectral unmixing results and airborne measurements shows high agreement. Airborne measurements of study forest area was carried out using Leica airborne digital sensor. Spatial resolution of airborne data is around 40 centimeters. The developed spectral unmixing approach can be used for other tasks, such as burned area mapping, crop monitoring, etc.