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There is a need to identify and extract the most useful information from spectral and temporal features, where usefulness is measured in terms of signal classification or target detection. For this reason, instead of using the entire spectral and temporal feature space, pertinent features are extracted to reduce dimensionality. The classification accuracy increases if the distributions of the classes...
The present paper presents an application of non- parametric statistical tests for the analysis of time series of remotely sensed data, acquired by different sensors of the same series. A set of points, extracted from the NOAA AVHRR GAC pathfinder dataset, which covers the period 1981-2001, was used as test dataset. Two tests, the Kruskal-Wallis and the Friedman test, have been used to address two...
Ecological and hydrological cycles play a key role in global climate dynamics. Remote sensing data are important in climate studies as they provide a global coverage of important hydrological variables at a variety of spatial and temporal scales. In this paper we study the long term relationships between NDVI derived from AVHRR and microwave brightness temperature from SSM/I sensor for different climate...
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