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The need for quantitative and accurate information to characterize the state and evolution of vegetation types at a national scale is widely recognized. This type of information is crucial for the Democratic Republic of Congo, which contains the majority of the tropical forest cover of Central Africa and a large diversity of habitats. In spite of recent progress in earth observation capabilities,...
This research investigates the adequacy of a remote sensing instrument's spatial resolution for monitoring crop growth over agricultural landscapes with different spatial patterns. The approach is based on the postulate that time series of a subset of pixels can characterize crop growth over a small zone with similar agro-climatic growing conditions. The point spread function (PSF) is explicitly taken...
This research aims to develop a multispectral, object-oriented and statistically-based change detection method using SPOT-VEGETATION time series. The dataset consists in daily images spanning years 2000 to 2006 and covering Bornean forest ecosystems. Seasonal composites are processed and homogeneous objects are delineated through a multi-temporal segmentation procedure. Each object is defined by a...
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