Article

Using ALOS/PALSAR and RADARSAT-2 to Map Land Cover and Seasonal Inundation in the Brazilian Pantanal

Citation

Evans TL, Costa MPF, Telmer KH & Silva TSF (2010) Using ALOS/PALSAR and RADARSAT-2 to Map Land Cover and Seasonal Inundation in the Brazilian Pantanal. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3 (4), pp. 560-575. https://doi.org/10.1109/JSTARS.2010.2089042

Abstract
The Brazilian Pantanal is a large continuous tropical wetland with large biodiversity and many threatened habitats. The interplay between the distribution of vegetation, the hydrology, the climate and the geomorphology nourishes and sustains the large diversity of flora and fauna in this wetland, but it is poorly understood at the scale of the entire Pantanal. This study uses multi-temporal L-band ALOS/PALSAR and C-band RADARSAT-2 data to map ecosystems and create spatial-temporal maps of flood dynamics in the Brazilian Pantanal. First, an understanding of the backscattering characteristics of floodable and non-floodable habitats was developed. Second, a Level 1 object-based image analysis (OBIA) classification defining Forest, Savanna, Grasslands/Agriculture, Aquatic Vegetation and Open Water cover types was achieved with accuracy results of 81%. A Level 2 classification separating Flooded from Non-Flooded regions for five temporal periods over one year was also accomplished, showing the interannual variability among sub-regions in the Pantanal. Cross-sensor, multi-temporal SAR data was found to be useful in mapping both land cover and flood patterns in wetland areas. The generated maps will be a valuable asset for defining habitats required to conserve the Pantanal biodiversity and to mitigate the impacts of human development in the region.

Keywords
Rivers ; Vegetation mapping; Floods; Remote sensing; Spatial resolution; ALOS/PALSAR; Flooding dynamics; Habitat mapping; K&C initiative; Pantanal; RADARSAT-2 Optical sensors

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing: Volume 3, Issue 4

StatusPublished
Publication date15/12/2010
Publication date online09/11/2010
Date accepted by journal29/09/2010
URLhttp://ieeexplore.ieee.org/…arnumber=5623305
ISSN1939-1404