optical remote sensing, image processing, Seasat-A scatterometer, advanced very high resolution radiometer, NDVI, enhanced resolution image reconstruction


A scientific effort is currently underway to assess tropical forest degradation and its potential impact on Earth's climate. Because of the large continental regions involved, Advanced Very High Resolution Radiometer (AVHRR) imagery and its derivative vegetation index products with resolutions between 1 and 12 km are typically used to inventory the Earth's equatorial vegetation. Archival AVHRR imagery is also used to obtain a temporal baseline of historical forest extent. Recently however, 50-km Seasat-A Scatterometer (SASS) Ku-band imagery (acquired in 1978) has been reconstructed to = 4-km resolution, making it a supplement to AVHRR imagery for historical vegetation assessment. In order to test the utility of reconstructed Ku-band scatterometer imagery for this purpose, seasonal AVHRR vegetation-index and SASS images of identical resolutions were constructed. Using the imagery, discrimination experiments involving 18 vegetation categories were conducted for a central South America study area. The results of these experiments indicate that AVHRR vegetation-index images are slightly superior to reconstructed SASS images for differentiating between equatorial vegetation classes when used alone. However, combining the scatterometer imagery with the vegetation-index images provides discrimination superior to any other combination of the data sets. Using the two data sets together, 90.3% of the test data could be correctly classified into broad classes of equatorial forest, degraded woodland/forest, woodland/savanna, and caatinga.

Original Publication Citation

Hardin, Perry J., Long, David G. "Integrating reconstructed scatterometer and advanced very high resolution radiometer data for tropical forest inventory." Optical Engineering 34.11 (1995): 3146-3153

Document Type

Peer-Reviewed Article

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Ira A. Fulton College of Engineering and Technology


Electrical and Computer Engineering