M
Mateus Batistella
Researcher at Empresa Brasileira de Pesquisa Agropecuária
Publications - 120
Citations - 4852
Mateus Batistella is an academic researcher from Empresa Brasileira de Pesquisa Agropecuária. The author has contributed to research in topics: Land use & Thematic Mapper. The author has an hindex of 33, co-authored 115 publications receiving 4007 citations. Previous affiliations of Mateus Batistella include State University of Campinas & Indiana University.
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Journal ArticleDOI
Framing Sustainability in a Telecoupled World
Jianguo Liu,Vanessa Hull,Mateus Batistella,Ruth DeFries,Thomas Dietz,Feng Fu,Thomas W. Hertel,R. Cesar Izaurralde,Eric F. Lambin,Shuxin Li,Luiz Antonio Martinelli,William J. McConnell,Emilio F. Moran,Rosamond L. Naylor,Zhiyun Ouyang,Karen R. Polenske,Anette Reenberg,Gilberto de Miranda Rocha,Cynthia S. Simmons,Peter H. Verburg,Peter M. Vitousek,Fusuo Zhang,Chunquan Zhu +22 more
TL;DR: In this article, an integrated framework based on telecoupling, an umbrella concept that refers to socioeconomic and environmental interactions over distances, is proposed to understand and integrate various distant interactions better.
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Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using RUSLE, remote sensing and GIS
TL;DR: In this paper, the authors applied the Revised Universal Soil Loss Equation (RUSLE), remote sensing, and geographical information system (GIS) to the maping of soil erosion risk in Brazilian Amazonia.
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Linear mixture model applied to Amazonian vegetation classification
TL;DR: In this paper, a linear mixture model (LMM) approach was applied to classify successional and mature forests using Thematic Mapper (TM) imagery in the Rondonia region of the Brazilian Amazon.
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Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates
Dengsheng Lu,Qi Chen,Guangxing Wang,Emilio F. Moran,Mateus Batistella,Maozhen Zhang,Gaia Vaglio Laurin,David Saah +7 more
TL;DR: Li et al. as mentioned in this paper provided a brief overview of current forest biomass estimation methods using both Landsat Thematic mapper (TM) image and LiDAR data, and demonstrated that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems.
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Land‐cover binary change detection methods for use in the moist tropical region of the Amazon: a comparative study
TL;DR: In this paper, 10 binary change detection methods were implemented and compared with respect to their capability to detect land-cover change and no change conditions in moist tropical regions in Amazon tropical regions.