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Estimating canopy height and its changes at meter resolution from satellite imagery is a significant challenge in computer vision with critical environmental applications.
Color enhancement of highly correlated images. ii. channel ratio and “chromaticity” transformation techniques
Alan R Gillespie, Anne B Kahle, and Richard E Walker · 1987
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Quantifying canopy height underestimation by laser pulse penetration in small-footprint airborne laser scanning data
David LA Gaveau and Ross A Hill · 2003
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Canopy damage and recovery after selective logging in Amazonia: Field and satellite studies
Gregory P Asner, Michael Keller, Rodrigo Pereira, Jr, Johan C Zweede, and Jose NM Silva · 2004
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Automatic detection of harvested trees and determination of forest growth using airborne laser scanning
Xiaowei Yu, Juha Hyyppä, Harri Kaartinen, and Matti Maltamo · 2004
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Change detection techniques for canopy height growth measurements using airborne laser scanner data
Xiaowei Yu, Juha Hyyppä, Antero Kukko, Matti Maltamo, and Harri Kaartinen · 2006
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Remote sensing support for national forest inventories
Ronald E McRoberts and Erkki O Tomppo · 2007
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Updated world map of the Köppen-Geiger climate classification
Murray C Peel, Brian L Finlayson, and Thomas A McMahon · 2007
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Forest cover change and illegal logging in the Ukrainian Carpathians in the transition period from 1988 to 2007
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Stephan Getzin, Kerstin Wiegand, and Ingo Schöning · 2012
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High-resolution global maps of 21st-century forest cover change
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Ortho-rectification of SPOT 6 satellite images based on RPC models
Guo Dong Yang and Xiang Zhu · 2013
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Rate of tree carbon accumulation increases continuously with tree size
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Adrian J Das and Nathan L Stephenson · 2015
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Rodney J Keenan · 2015
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Kenneth G MacDicken · 2015
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Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Importance of ground refuges for the biodiversity in agricultural hedgerows
Stéphane Lecq, Anne Loisel, Francois Brischoux, Stephen J Mullin, and Xavier Bonnet · 2017
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Gordon Christie, Neil Fendley, James Wilson, and Ryan Mukherjee · 2018
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Projecting Australia’s forest cover dynamics and exploring influential factors using deep learning
Long Ye, Lei Gao, Raymundo Marcos-Martinez, Dirk Mallants, and Brett A Bryan · 2019
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Forests growth monitoring based on tree canopy 3D reconstruction using UAV aerial photogrammetry
Yanchao Zhang, Hanxuan Wu, and Wen Yang · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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The global ecosystem dynamics investigation: High-resolution laser ranging of the Earth’s forests and topography
Ralph Dubayah, James Bryan Blair, Scott Goetz, Lola Fatoyinbo, Matthew Hansen, Sean Healey, Michelle Hofton, George Hurtt, James Kellner, Scott Luthcke, et al · 2020
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Remote sensing of selective logging in tropical forests: Current state and future directions
Colbert M Jackson and Elhadi Adam · 2020
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The PROFOUND database for evaluating vegetation models and simulating climate impacts on European forests
Christopher PO Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, et al · 2020
Scale-MAE: A scale-aware masked autoencoder for multiscale geospatial representation learning
Colorado J Reed, Ritwik Gupta, Shufan Li, Sarah Brockman, Christopher Funk, Brian Clipp, Kurt Keutzer, Salvatore Candido, Matt Uyttendaele, and Trevor Darrell · 2023
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Improving gedi footprint geolocation using a high resolution digital elevation model
Anouk Schleich, Sylvie Durrieu, and Cédric Vega · 2023
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Mapping forest height and biomass at high resolution in France with satellite remote sensing and deep learning
Martin Schwartz · 2023
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FORMS: Forest multiple source height, wood volume, and biomass maps in France at 10 to 30m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach
Martin Schwartz, Philippe Ciais, Aurélien De Truchis, Jérôme Chave, Catherine Ottlé, Cedric Vega, Jean-Pierre Wigneron, Manuel Nicolas, Sami Jouaber, Siyu Liu, Martin Brandt, and Ibrahim Fayad · 2023
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Evaluating and mitigating the impact of systematic geolocation error on canopy height measurement performance of GEDI
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Twins: Revisiting the design of spatial attention in vision transformers
Xiangxiang Chu, Zhi Tian, Yuqing Wang, Bo Zhang, Haibing Ren, Xiaolin Wei, Huaxia Xia, and Chunhua Shen · 2021
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Datasheets for datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé Iii, and Kate Crawford · 2021
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SWIN transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Mapping global forest canopy height through integration of GEDI and Landsat data
Peter Potapov, Xinyuan Li, Andres Hernandez-Serna, Alexandra Tyukavina, Matthew C Hansen, Anil Kommareddy, Amy Pickens, Svetlana Turubanova, Hao Tang, Carlos Edibaldo Silva, et al · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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ImageNet-21K pretraining for the masses
Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, and Lihi Zelnik-Manor · 2021
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Preventing illegal logging
Sara T Thompson and William B Magrath · 2021
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Hao Tang, Jason Stoker, Scott Luthcke, John Armston, Kyungtae Lee, Bryan Blair, and Michelle Hofton · 2023
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Tree canopy extent and height change in Europe, 2001–2021, quantified using Landsat data archive
Svetlana Turubanova, Peter Potapov, Matthew C Hansen, Xinyuan Li, Alexandra Tyukavina, Amy H Pickens, Andres Hernandez-Serna, Adrian Pascual Arranz, Juan Guerra-Hernandez, Cornelius Senf, et al · 2023
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https://inventaire-forestier.ign.fr/spip.php?article773
Fiches descriptives des grandes régions écologiques (GRECO) et des sylvoécorégions (SER) · 2024
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org/docs/stable/generated/torch.optim.lr_scheduler.ReduceLROnPlateau.html#torch.optim.lr_scheduler.ReduceLROnPlateau
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Forest practitioners’ requirements for remote sensing-based canopy height, wood-volume, tree species, and disturbance products
Fabian Ewald Fassnacht, Christoph Mager, Lars T Waser, Urša Kanjir, Jannika Schäfer, Ana Potočnik Buhvald, Elham Shafeian, Felix Schiefer, Liza Stančič, Markus Immitzer, et al · 2024
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Neon (national ecological observatory network). ecosystem structure (dp3.30015.001))
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Swisstopo orthophotos
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Jan Pauls, Max Zimmer, Una M Kelly, Martin Schwartz, Sassan Saatchi, Philippe Ciais, Sebastian Pokutta, Martin Brandt, and Fabian Gieseke · 2024
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Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial LiDAR
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Sub-meter tree height mapping of California using aerial images and LiDAR-informed U-Net model
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