Yrjö Rauste

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The Global Rain Forest Mapping Project (GRFM) is an international collaborative effort initiated and managed by the National Space Development Agency of Japan (NASDA). The main goal of the project is to produce a high resolution wall-to-wall map of the entire tropical rain forest domain in four continents using the L-band SAR onboard the JERS-1 spacecraft.(More)
In this study, we extended the potential of a ContentBased Image Retrieval (CBIR) system based on Self-Organizing Maps (SOMs), for the analysis of remote sensing data. A database was artificially created by splitting each image to be analyzed into small images (or imagelets). Content-based image retrieval was applied to fully polarimetric airborne SAR data,(More)
Boreal ecosystems play an essential role in global climate regulation. Forests constitute pools of terrestrial carbon and are generally considered as global sinks of atmospheric CO2, contributing to attenuating the greenhouse effect. Large amounts of carbon are also stored in boreal lakes, bogs and wetlands, partially released as CH4 and other trace gases(More)
Methods for terrain correction of polarimetric SAR data were studied and developed. Ortho-rectification resampling and amplitude correction utilized Stokes matrix data. The Stokes matrix of thermal noise was subtracted before amplitude normalization. Application of an azimuth-slope correction algorithm resulted in slightly narrower distribution of(More)
In the context of the Global Boreal Forest Mapping project (GBFM), an initiative of the Japan Aerospace Exploration Agency (JAXA), a continental scale radar mosaic of the Eurasian Taiga was compiled. The mosaic is composed of some 520 strip-images (typically covering 80 km by 2500 km each) acquired in 1997-98 by the L-band SAR aboard the JERS-1 spacecraft.(More)
This paper evaluates performance of fully polarimetric SAR (PolSAR) data in several land cover mapping studies in the boreal forest environment, taking advantage of the high canopy penetration capability at L-band. The studies included multiclass land cover mapping, forest–nonforest delineation, and classification of soil type under vegetation. PolSAR data(More)
This letter describes an algorithm development for the production of a large-scale fully polarimetric synthetic aperture radar (SAR) (PolSAR) mosaic using multitemporal Advanced Land Observing Satellite Phased Array type L-band SAR acquisitions. The PolSAR data were collected during the snow-melting season in 2007 over Finnish Lapland, resulting in(More)
This article aims at providing a comparison of polarimetric change detection indices from a practical point of view. Six polarimetric change detection indices were tested on L band EMISAR data over Norway. Tests included quantitative evaluation of change maps compared to a ground truth of changes, and qualitative evaluation by visual inspection. Contrast(More)