Publications

Daldegan, GA; Roberts, DA; Ribeiro, FDF (2019). Spectral mixture analysis in Google Earth Engine to model and delineate fire scars over a large extent and a long time-series in a rainforest-savanna transition zone. REMOTE SENSING OF ENVIRONMENT, 232, UNSP 111340.

Abstract
Fire is used worldwide to clear natural vegetation areas for economic activities and to manage the regeneration of already opened sites. In Brazil, fire has been traditionally used to convert natural vegetation areas to agricultural lands (slash and burn) and to manage pastures for livestock. We developed the Burned Area Spectral Mixture Analysis (BASMA) algorithm in Google Earth Engine, which is designed to process Landsat data to produce a multi-temporal fire scar database representing annual burned area for an extent of 362,000 km(2) in the transition zone between the Amazon forest and the Cerrado biome. This region is considered a conservation hotspot, given its high deforestation rates over the last four decades. We digitally processed a 32-year time-series (1985 to 2017) of Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper+, and Landsat 8 Operational Land Imager data to map fire scars based on sub-pixel char fraction, aiming to generate a consistent burned area product at a finer scale and covering a longer period than those currently available for the region. Manually interpreted reference burned area polygons for each annual mosaic was used to guide the definition of the best fire scar endmember and its fraction threshold. To assess our BASMA-delineated fire scar, they were compared to independent datasets of manually delineated burned area produced by visual analysis of finer spatial resolution imagery, returning an average Dice Coefficient value of 0.86. Accuracy was also measured against the 30-meter Burned Area product available at the 'Queimadas' data portal. A total of 11,106,258 ha was mapped as having been affected by fire during the annual dry season over the 32 years, which represents 30.7% of the study region. Results showed a decreasing trend in the annual amount of burned area over the time-series. It reflects a similar pattern shown in the deforestation rate for the Legal Amazon, measured by the Brazilian National Institute for Space Research - INPE. Moreover, the Cerrado biome subset of the study region consistently showed higher burned area when compared to the Amazon forest subset. Our findings provide robust evidence that our approach is a consistent method to identify and delineate fire scars for large areas over a long time-series in a very efficient fashion, given the digital processing power of Google Earth Engine, which reduces the time necessary to analyze such big amount of data.

DOI:
10.1016/j.rse.2019.111340

ISSN:
0034-4257