Zobrazeno 1 - 10
of 718
pro vyhledávání: '"Saatchi, Sassan"'
Autor:
Mullissa, Adugna, Saatchi, Sassan
Tropical forests play an important role in regulating the global carbon cycle and are crucial for maintaining the tropical forest biodiversity. Therefore, there is an urgent need to map the extent of tropical forest ecosystems. Recently, deep learnin
Externí odkaz:
http://arxiv.org/abs/2408.00107
Autor:
Pauls, Jan, Zimmer, Max, Kelly, Una M., Schwartz, Martin, Saatchi, Sassan, Ciais, Philippe, Pokutta, Sebastian, Brandt, Martin, Gieseke, Fabian
We propose a framework for global-scale canopy height estimation based on satellite data. Our model leverages advanced data preprocessing techniques, resorts to a novel loss function designed to counter geolocation inaccuracies inherent in the ground
Externí odkaz:
http://arxiv.org/abs/2406.01076
Autor:
Wagner, Fabien H, Favrichon, Samuel, Dalagnol, Ricardo, Hirye, Mayumi CM, Mullissa, Adugna, Saatchi, Sassan
The Amazon, the world's largest rainforest, faces a severe historic drought. The Rio Negro River, one of the major Amazon River tributaries, reaches its lowest level in a century in October 2023. Here, we used a U-net deep learning model to map water
Externí odkaz:
http://arxiv.org/abs/2401.16393
Autor:
Mitchard, Edward T. A., Carstairs, Harry, Cosenza, Riccardo, Saatchi, Sassan S., Funk, Jason, Quintano, Paula Nieto, Brade, Thom, McNicol, Iain M., Meir, Patrick, Collins, Murray B., Nowak, Eric
Independent retrospective analyses of the effectiveness of reducing deforestation and forest degradation (REDD) projects are vital to ensure climate change benefits are being delivered. A recent study in Science by West et al. (1) appeared therefore
Externí odkaz:
http://arxiv.org/abs/2312.06793
Autor:
Wagner, Fabien H, Roberts, Sophia, Ritz, Alison L, Carter, Griffin, Dalagnol, Ricardo, Favrichon, Samuel, Hirye, Mayumi CM, Brandt, Martin, Ciais, Philipe, Saatchi, Sassan
Tree canopy height is one of the most important indicators of forest biomass, productivity, and species diversity, but it is challenging to measure accurately from the ground and from space. Here, we used a U-Net model adapted for regression to map t
Externí odkaz:
http://arxiv.org/abs/2306.01936
Autor:
Fayad, Ibrahim, Ciais, Philippe, Schwartz, Martin, Wigneron, Jean-Pierre, Baghdadi, Nicolas, de Truchis, Aurélien, d'Aspremont, Alexandre, Frappart, Frederic, Saatchi, Sassan, Pellissier-Tanon, Agnes, Bazzi, Hassan
Accurate and timely monitoring of forest canopy heights is critical for assessing forest dynamics, biodiversity, carbon sequestration as well as forest degradation and deforestation. Recent advances in deep learning techniques, coupled with the vast
Externí odkaz:
http://arxiv.org/abs/2304.11487
Autor:
Wagner, Fabien H, Dalagnol, Ricardo, Silva-Junior, Celso HL, Carter, Griffin, Ritz, Alison L, Hirye, Mayumi CM, Ometto, Jean PHB, Saatchi, Sassan
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 spati
Externí odkaz:
http://arxiv.org/abs/2211.09806
Autor:
Wagner, Fabien H., Dalagnol, Ricardo, Sánchez, Alber H., Hirye, Mayumi C. M., Favrichon, Samuel, Lee, Jake H., Mauceri, Steffen, Yang, Yan, Saatchi, Sassan
Deep learning self-supervised algorithms that can segment an image in a fixed number of hard labels such as the k-means algorithm and relying only on deep learning techniques are still lacking. Here, we introduce the k-textures algorithm which provid
Externí odkaz:
http://arxiv.org/abs/2205.08671
Autor:
Mullissa, Adugna1,2 (AUTHOR) amullissa@ctrees.org, Saatchi, Sassan1,2,3 (AUTHOR), Dalagnol, Ricardo1,2,3 (AUTHOR), Erickson, Tyler4 (AUTHOR) tyler@vorgeo.com, Provost, Naomi1 (AUTHOR), Osborn, Fiona1 (AUTHOR), Ashary, Aleena1 (AUTHOR), Moon, Violet1 (AUTHOR), Melling, Daniel1 (AUTHOR)
Publikováno v:
Remote Sensing. Jun2024, Vol. 16 Issue 12, p2151. 16p.
Autor:
Zhao, Zhe, Ciais, Philippe, Wigneron, Jean-Pierre, Santoro, Maurizio, Brandt, Martin, Kleinschroth, Fritz, Lewis, Simon L., Chave, Jerome, Fensholt, Rasmus, Laporte, Nadine, Sonwa, Denis Jean, Saatchi, Sassan S., Fan, Lei, Yang, Hui, Li, Xiaojun, Wang, Mengjia, Zhu, Lei, Xu, Yidi, He, Jiaying, Li, Wei
Publikováno v:
In One Earth 15 March 2024 7(3):506-519