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2 results on '"Silva-Junior, Celso HL"'

1. Mapping Tropical Forest Cover and Deforestation with Planet NICFI Satellite Images and Deep Learning in Mato Grosso State (Brazil) from 2015 to 2021

Author

Wagner, Fabien H, Dalagnol, Ricardo, Silva-Junior, Celso HL, Carter, Griffin, Ritz, Alison L, Hirye, Mayumi CM, Ometto, Jean PHB, and Saatchi, Sassan

Subjects
Astrophysics - Earth and Planetary Astrophysics, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Monitoring changes in tree cover for rapid assessment of deforestation is considered the critical component of any climate mitigation policy for reducing carbon. Here, we map tropical tree cover and deforestation between 2015 and 2022 using 5 m spatial resolution Planet NICFI satellite images over the state of Mato Grosso (MT) in Brazil and a U-net deep learning model. The tree cover for the state was 556510.8 km$^2$ in 2015 (58.1 % of the MT State) and was reduced to 141598.5 km$^2$ (14.8 % of total area) at the end of 2021. After reaching a minimum deforested area in December 2016 with 6632.05 km$^2$, the bi-annual deforestation area only showed a slight increase between December 2016 and December 2019. A year after, the areas of deforestation almost doubled from 9944.5 km$^2$ in December 2019 to 19817.8 km$^2$ in December 2021. The high-resolution data product showed relatively consistent agreement with the official deforestation map from Brazil (67.2%) but deviated significantly from year of forest cover loss estimates from the Global Forest change (GFC) product, mainly due to large area of fire degradation observed in the GFC data. High-resolution imagery from Planet NICFI associated with deep learning technics can significantly improve mapping deforestation extent in tropics., Comment: 18 pages, 10 figures, submitted to Remote Sensing MDPI, Special Issue "Remote Sensing of the Amazon Region"

Published
2022

2. Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses.

Author

Silva Junior, Celso HL, Aragão, Luiz EOC, Anderson, Liana O, Fonseca, Marisa G, Shimabukuro, Yosio E, Vancutsem, Christelle, Achard, Frédéric, Beuchle, René, Numata, Izaya, Silva, Carlos A, Maeda, Eduardo E, Longo, Marcos, and Saatchi, Sassan S

Abstract

Deforestation is the primary driver of carbon losses in tropical forests, but it does not operate alone. Forest fragmentation, a resulting feature of the deforestation process, promotes indirect carbon losses induced by edge effect. This process is not implicitly considered by policies for reducing carbon emissions in the tropics. Here, we used a remote sensing approach to estimate carbon losses driven by edge effect in Amazonia over the 2001 to 2015 period. We found that carbon losses associated with edge effect (947 Tg C) corresponded to one-third of losses from deforestation (2592 Tg C). Despite a notable negative trend of 7 Tg C year-1 in carbon losses from deforestation, the carbon losses from edge effect remained unchanged, with an average of 63 ± 8 Tg C year-1 Carbon losses caused by edge effect is thus an additional unquantified flux that can counteract carbon emissions avoided by reducing deforestation, compromising the Paris Agreement's bold targets.

Published
2020

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