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3082.jpg (37683 bytes)Satellite imagery provides an inexpensive, geographically accurate, and synoptic medium for many earth resource applications including geo-environmental analysis. Remotely sensed imagery is especially useful in areas that are difficult to access like the Orinoco Delta, where ground investigations are expensive and time-consuming. Hence a major effort within the Bureau's geo-environmental study involves developing accurate and comprehensive remotely sensed data in a geographic information system (GIS) format for the interpretation of Orinoco Delta natural environments and processes. These images are also the preliminary data set in the digital environmental atlas.

A remotely sensed image is a record of the backscattering effects of a defined range or set of ranges of wavelengths of the electromagnetic spectrum. Typically, the range of wavelengths used for remote sensing is from ultraviolet though the visible light spectrum to infrared and to radar. The Bureau investigated a variety of remote sensing image types that could be potentially useful for geo-environmental analysis of the Delta, and we chose Landsat (visible light and infrared range) and three different forms of radar imagery. Radar energy responds to fundamentally different characteristics of the ground and vegetation than Landsat or other optical systems. The Landsat instrument senses reflectance in the visible and infrared portion of the electromagnetic spectrum and hence is sensitive to the resonant modes of molecules in the surface layer of vegetation or soil (Ulaby and others, 1981). Radar systems use electromagnetic wavelengths that are three orders of magnitude longer than those used by Landsat. This means that radar energy is most sensitive to the geometric and bulk electrical properties of the ground and vegetation. Because radar and optical systems measure different characteristics of their target, combining them can significantly enhance environmental analysis.

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Please send comments, questions, or suggestions to Edgar Guevara.
Copyright 1998 Bureau of Economic Geology