Mapping evergreen forests in the Brazilian Amazon using MODIS and PALSAR 500-m mosaic imagery
نویسندگان
چکیده
0924-2716/$ see front matter 2012 International http://dx.doi.org/10.1016/j.isprsjprs.2012.07.003 ⇑ Corresponding author. Address: 3100 Monitor A Oklahoma, Norman, OK 73072, USA. Tel.: +1 405 325 E-mail address: [email protected] (S. Sheldon) In this study, we evaluate a methodology that uses dual-polarization L-band SAR 500-m mosaic PALSAR imagery to identify and map forests in the Brazilian Amazon and an algorithm that uses time-series MODIS imagery to map evergreen forest. IKONOS images were used to evaluate forest maps derived from PALSAR and MODIS imagery. A comparison between the PALSAR forest map and IKONOS forest maps shows that 91.4% of PALSAR-derived forest pixels had greater than 60% IKONOS-derived forest area. We also compared the PALSAR-derived forest map with the MODIS-derived evergreen forest map. Out of 1999 evergreen forest pixels in the MODIS evergreen forest map (the areas covered by the 11 IKONOS imagery), 1934 pixels were identified as forest by the PALSAR forest map, approximately 96.7% agreement. The results of this study highlight the potential of combining PALSAR and MODIS data for identifying and mapping evergreen forests in the Amazon. 2012 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.
منابع مشابه
Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010
Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phase...
متن کاملA Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia
The areal extent and spatial distribution of evergreen forests in the tropical zones are important for the study of climate, carbon cycle and biodiversity. However, frequent cloud cover in the tropical regions makes mapping evergreen forests a challenging task. In this study we developed a simple and novel mapping algorithm that is based on the temporal profile analysis of Land Surface Water In...
متن کاملPhenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery
Updated extent, area, and spatial distribution of tropical evergreen forests from inventory data provides valuable knowledge for research of the carbon cycle, biodiversity, and ecosystem services in tropical regions. However, acquiring these data in mountainous regions requires labor-intensive, often cost-prohibitive field protocols. Here, we report about validated methods to rapidly identify t...
متن کاملPALSAR 50 m Mosaic Data Based National Level Biomass Estimation in Cambodia for Implementation of REDD+ Mechanism
Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation mechanism related to Reducing Emissions from Deforestation and forest Degradation (REDD+). This study investigated the potential of Phased Array-type L-band Synthetic Aperture Radar Fine Beam Dual (PALSAR FBD) 50 m mosaic data to estimate Above Ground Biomass (AGB...
متن کاملDetecting leaf phenology of seasonally moist tropical forests in South America with multi-temporal MODIS images
Leaf phenology of tropical evergreen forests affects carbon and water fluxes. In an earlier study of a seasonally moist evergreen tropical forest site in the Amazon basin, time series data of Enhanced Vegetation Index (EVI) from the VEGETATION and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors showed an unexpected seasonal pattern, with higher EVI in the late dry season than in t...
متن کامل