13 documents found, page 1 of 2
Mapping Fractional Cropland Distribution in Mato Grosso, Brazil Using Time Seri...
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 statistics. This study proposes a new approach to map fractional cropland distribution in Mato Grosso, Brazil using time series MODIS enhanced vegetation index (EVI) and Landsat Thematic Mapper (TM) data. The major step...
Satellite estimation of aboveground biomass and impacts of forest stand structure.
LU, D.; BATISTELLA, M.; MORAN, E.Heterogeneous Amazonian landscapes and complex forest stand structure often make aboveground biomass (AGB) estimation difficult. In this study, spectral mixture analysis was used to convert a Landsat Thematic Mapper (TM) image into green vegetation, shade, and soil fraction images. Entropy was used to analyze the complexity of forest stand structure and to examine impacts of different stand structures on TM ref...
Mappig and monitoring land degradation risks in the western Brazilian Amazon us...
LU, D.; BATISTELLA, M.; MAUSEL, P.; MORAN, E.Mapping and monitoring land degradation in areas under human-induced stresses have urgent tasks in remote sensing whose importance has not yet been fully appreciated. In this study, a surface cover index (SCI) is developed to evaluate and map potential land degradation risks associated with deforestation and accompanying soil erosion in a Western Brazilian Amazon rural settlement study area. The relationships b...
Land-cover classification in the Brazilian Amazon with the integration of Lands...
LU, D.; BATISTELLA, M.; MORAN, E.Land-cover classification with remotely sensed data in moist tropical regions in a challenge due to the complex biophysical conditions. This paper explores techniques to improve land-cover classification accuracy through a comparative analysis of different combinations of spectral signatures and textures from Landsat Enhanced Thematic Mapper Plus (ETM +) and Radarsat data. A wavelet-merging technique was used t...
A comparative study of landsat TM and SPOT HRG images of vegetation classificat...
LU, D.; BATISTELLA, M.; MIRANDA, E. E. deComplex forest structure and abundant tree species in the moist tropical regions often couse difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, ...
Multitemporal spectral mixture analysis for Amazonian land-cover change detection.
LU, D.; BATISTELLA, M.; MORAN, E.The complex landscape and environmental conditions in the moist tropical region often result in poor land-cover change detection accuracy using traditional change detection methods. This paper explores linear spectral mixture analysis (LSMA) of multitemporal thematic mapper (TM) images to detect land-cover change in Rondônia, Brazilian Amazon basin. Three image endmembers (shade, green vegetation, and soil) wer...
A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for lan...
LI, G.; LU, D.; DUTRA, L.; BATISTELLA, M.This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Transformed divergence was used to identify potential textural images which were calculated with the gray-level co-occurrence matrix method. The standard deviation of selected textural images ...
The roles of textural images in improving land-cover classification in the Braz...
LU, D.; LI, G.; MORAN, E.; DUTRA, L.; BATISTELLA, M.Texture has long been recognized as valuable in improving land-cover classification, but how data from different sensors with varying spatial resolutions affect the selection of textural images is poorly understood. This research examines textural images from the Landsat Thematic Mapper (TM), ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar), the SPOT (Satellite...
Aboveground forest biomass estimation with Landsat and LiDAR data and uncertain...
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, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimatio...
Land use/cover classification in the Brazilian Amazon using satellite images.
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 regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Throu...