A New Multi-Temporal Forest Cover Classification for the Xingu River Basin, Brazil

Margaret Kalacska, Oliver Lucanus, Leandro Sousa and J. Pablo Arroyo-Mora
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Margaret Kalacska: Applied Remote Sensing Laboratory, Department of Geography, McGill University, Montreal, QC H3A 0B9, Canada
Oliver Lucanus: Applied Remote Sensing Laboratory, Department of Geography, McGill University, Montreal, QC H3A 0B9, Canada
Leandro Sousa: Flight Research Lab, National Research Council of Canada, Ottawa ON K1A 0R6, Canada
J. Pablo Arroyo-Mora: Laboratório de Ictiologia de Altamira, Universidade Federal do Pará, Altamira PA 68372040, Brazil

Data, 2019, vol. 4, issue 3, 1-8

Abstract: We describe a new multi-temporal classification for forest/non-forest classes for a 1.3 million square kilometer area encompassing the Xingu River basin, Brazil. This region is well known for its exceptionally high biodiversity, especially in terms of the ichthyofauna, with approximately 600 known species, 10% of which are endemic to the river basin. Global and regional scale datasets do not adequately capture the rapidly changing land cover in this region. Accurate forest cover and forest cover change data are important for understanding the anthropogenic pressures on the aquatic ecosystems. We developed the new classifications with a minimum mapping unit of 0.8 ha from cloud free mosaics of Landsat TM5 and OLI 8 imagery in Google Earth Engine using a classification and regression tree (CART) aided by field photographs for the selection of training and validation points.

Keywords: Landsat imagery; land cover change; deforestation; biodiversity; conservation; Xingu river basin (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
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