Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Fabien H. Wagner"'
Autor:
Griffin Carter, Fabien H. Wagner, Ricardo Dalagnol, Sophia Roberts, Alison L. Ritz, Sassan Saatchi
Publikováno v:
Frontiers in Remote Sensing, Vol 5 (2024)
California forests have recently experienced record breaking wildfires and tree mortality from droughts, However, there is inadequate monitoring, and limited data to inform policies and management strategies across the state. Although forest surveys
Externí odkaz:
https://doaj.org/article/d3eabc77a4c94f34b84024bcf720c24a
Autor:
Fabien H. Wagner, Samuel Favrichon, Ricardo Dalagnol, Mayumi C. M. Hirye, Adugna Mullissa, Sassan Saatchi
Publikováno v:
Remote Sensing, Vol 16, Iss 6, p 1056 (2024)
The Amazon, the world’s largest rainforest, faces a severe historic drought. The Rio Negro River, one of the major Amazon River tributaries, reached its lowest level in a century in October 2023. Here, we used a U-net deep learning model to map wat
Externí odkaz:
https://doaj.org/article/f6c0effdaef14f1288407c55361eed60
Autor:
Ricardo Dalagnol, Fabien H. Wagner, Thaise Emilio, Annia S. Streher, Lênio S. Galvão, Jean P. H. B. Ometto, Luiz E. O. C. Aragão
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 8, Iss 5, Pp 601-614 (2022)
Abstract The Amazon region in Brazil contains c. 5% of the palm species of the world. However, palm cover at macroecological scales has not yet been quantified in this biome. Here, we used high spatial resolution LiDAR data, acquired from 610 flightl
Externí odkaz:
https://doaj.org/article/08e4d7b23d7248eabadeb10e470ad2d8
Autor:
Guilherme Mataveli, Gabriel de Oliveira, Michel E. D. Chaves, Ricardo Dalagnol, Fabien H. Wagner, Alber H. S. Ipia, Celso H. L. Silva‐Junior, Luiz E. O. C. Aragão
Publikováno v:
Conservation Letters, Vol 15, Iss 6, Pp n/a-n/a (2022)
Abstract While Brazil publicly committed to reduce deforestation in Amazonia at the 26th Conference of the Parties (COP26), the Brazilian parliament is moving toward weakening environmental laws. Deforestation rates continue ascending, reaching in 20
Externí odkaz:
https://doaj.org/article/a1b7a32f764e406682aada190e536d67
Autor:
Fabien H. Wagner
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-20 (2021)
Abstract Mapping the spatial distribution of a plant is a current challenge in ecology. Here, a convolutional neural network (CNN) and 33,798 Sentinel-2 satellite images were used to detect and map forest stands dominated by trees of the genus Plerom
Externí odkaz:
https://doaj.org/article/c38db386a29c41e2b9fe2fa630fd3a41
Autor:
Fabien H. Wagner, Ricardo Dalagnol, Alber H. Sánchez, Mayumi C. M. Hirye, Samuel Favrichon, Jake H. Lee, Steffen Mauceri, Yan Yang, Sassan Saatchi
Publikováno v:
Frontiers in Environmental Science, Vol 10 (2022)
Deep learning self-supervised algorithms that can segment an image in a fixed number of hard clusters such as the k-means algorithm and with an end-to-end deep learning approach are still lacking. Here, we introduce the k-textures algorithm which pro
Externí odkaz:
https://doaj.org/article/ed0fedee47964307a9693c96ee1a8733
Autor:
Ricardo Dalagnol, Fabien H. Wagner, Lênio S. Galvão, Annia S. Streher, Oliver L. Phillips, Emanuel Gloor, Thomas A. M. Pugh, Jean P. H. B. Ometto, Luiz E. O. C. Aragão
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Abstract We report large-scale estimates of Amazonian gap dynamics using a novel approach with large datasets of airborne light detection and ranging (lidar), including five multi-temporal and 610 single-date lidar datasets. Specifically, we (1) comp
Externí odkaz:
https://doaj.org/article/d496adcb275d4fb1951dcf49cbda5c8f
Autor:
Fabien H. Wagner, Ricardo Dalagnol, Celso H. L. Silva-Junior, Griffin Carter, Alison L. Ritz, Mayumi C. M. Hirye, Jean P. H. B. Ometto, Sassan Saatchi
Publikováno v:
Remote Sensing, Vol 15, Iss 2, p 521 (2023)
Monitoring changes in tree cover for assessment of deforestation is a premise for policies to reduce carbon emission in the tropics. Here, a U-net deep learning model was used to map monthly tropical tree cover in the Brazilian state of Mato Grosso b
Externí odkaz:
https://doaj.org/article/e074eedc33c24270bb584a2906be6284
Autor:
Fabien H. Wagner, Alber Sanchez, Yuliya Tarabalka, Rodolfo G. Lotte, Matheus P. Ferreira, Marcos P. M. Aidar, Emanuel Gloor, Oliver L. Phillips, Luiz E. O. C. Aragão
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 5, Iss 4, Pp 360-375 (2019)
Abstract Mapping forest types and tree species at regional scales to provide information for ecologists and forest managers is a new challenge for the remote sensing community. Here, we assess the potential of a U‐net convolutional network, a recen
Externí odkaz:
https://doaj.org/article/687bf095f9e74e72a6ad4e0e2c69f23c
Autor:
Luiz E. O. C. Aragão, Liana O. Anderson, Marisa G. Fonseca, Thais M. Rosan, Laura B. Vedovato, Fabien H. Wagner, Camila V. J. Silva, Celso H. L. Silva Junior, Egidio Arai, Ana P. Aguiar, Jos Barlow, Erika Berenguer, Merritt N. Deeter, Lucas G. Domingues, Luciana Gatti, Manuel Gloor, Yadvinder Malhi, Jose A. Marengo, John B. Miller, Oliver L. Phillips, Sassan Saatchi
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-12 (2018)
Deforestation carbon emissions from the Brazilian Amazon have declined steeply, but how much drought-induced forest fire emissions add to this process is still unclear. Here the authors show that gross emissions from forest fires are more than half a
Externí odkaz:
https://doaj.org/article/6cec3cffb65b432eb2776761784f6d7f