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Authorship: ZHU, C.; LU, D.; VICTORIA, D. de C.; DUTRA, L. V. Mapping cropland distribution over large areas has attracted great attention in recent years, however, traditional pixel-based classification approaches produce high uncertainty in cropland area stati... ... |
Authorship: LU, D.; BATISTELLA, M.; LI, G.; MORAN, E.; HETRICK, S.; FREITAS, C. DA C.; SANT'ANNA, S. J. Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical... ... |
Authorship: LU, D.; CHEN, Q.; WANG, G.; MORAN, E.; BATISTELLA, M.; ZHANG, M.; LAURIN, G. V.; SAAH, D. Landsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, for... ... |
Authorship: LU, D.; LI, G.; BATISTELLA, M.; FREITAS, C. C. This research explored the integrated use of Landsat Thematic Mapper (TM) and radar (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) data for mapping impervious surface distribution to examine the rol... ... |
Authorship: LU, D.; BATISTELLA, M.; MORAN, E.; HETRICK, S.; ALVES, D.; BRONDIZIO, E.
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