Data Set Overview
|Data set||LBA-ECO CD-37 Secondary Forest Biomass and Age Class, Rondonia, Brazil|
|Project||Large Scale Biosphere-Atmosphere|
|Time Period||1975-06-19 to 2003-05-20|
This data set provides tree age, forest formation, and land cover classification maps, and estimates of landscape-level above-ground live woody biomass (AGLB) for secondary forests in Rondonia, Brazil. The Threshold Age Mapping Algorithm (TAMA) was applied to a densely spaced time series of Landsat images (1975 to 2003) to derive forest type and age classification maps. The AGLB of the secondary forest was estimated by combining the forest classification map with coincident biomass estimates from the Geoscience Laser Altimeter System (GLAS). There are five raster images and three comma-delimited data files with this data set.
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Large Scale Biosphere-Atmosphere : The Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) is an intensive scientific investigation of the tropical rainforest of Brazil and portions of adjacent countries. Like FIFE and BOREAS, this project uses intensive remote-sensing techniques and ground-based experiments to investigate the atmosphere-biosphere-hydrosphere dynamics of this large tropical region. The LBA Project encompasses several scientific disciplines, or components. The LBA-ECO component focuses on the question: "How do tropical forest conversion, regrowth, and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in Amazonia?"
Project data set list for Large Scale Biosphere-Atmosphere .
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|Data File (Granule)||File Size||Dates|
|GLAS_Secondary_Forest.csv||86.7 KB||1975-06-19 - 2003-05-20|
|TAMA_Model_Checkpoints.csv||2.9 KB||1975-06-19 - 2003-05-20|
|TAMA_thresholds.csv||588 B||1975-06-19 - 2003-05-20|
|forest_type_age_combined.zip||5.8 MB||1975-06-19 - 2003-05-20|
|sfage_all_auto1_filter_ar01msk_undisteq30.zip||3.2 MB||1975-06-19 - 2003-05-20|
Files related to this data set have been downloaded on 80 occasions since 2013-02-13, totaling 348 files.