JRC scientists obtained remarkable results in correcting surface shapes of satellite imagery to study mountainous terrains, with a combination of topographic correction algorithms and statistical methods. The JRC presented its new method in a recently published article in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
Proper pre-processing of remote sensing imagery is required to limit possible discrepancies due to atmospheric, radiometric and topographic effects, such as confusion between clouds and bright soils. Whereas most of these factors have been studied and their correction methods established, topographically induced illumination differences, confusion between dark shadows and water bodies for example, are still being investigated and there is no universal technique widely accepted in the remote sensing community.
To fill this gap, the JRC tested two digital elevation models (3D representations of a terrain’s surface), a pre-classification/stratification approach to identify the strata according to the vegetation covers and several statistical correction methods, in study areas from 3 continents (Asia, Africa and South America) with different land covers.
For more information click here
Source: Joint Research Centre