Zobrazeno 1 - 10
of 6 879
pro vyhledávání: '"tree-species classification"'
Publikováno v:
Neurips 2024 - Climate Change Workshop
Tree species classification plays an important role in nature conservation, forest inventories, forest management, and the protection of endangered species. Over the past four decades, remote sensing technologies have been extensively utilized for tr
Externí odkaz:
http://arxiv.org/abs/2411.12897
Reliable large-scale data on the state of forests is crucial for monitoring ecosystem health, carbon stock, and the impact of climate change. Current knowledge of tree species distribution relies heavily on manual data collection in the field, which
Externí odkaz:
http://arxiv.org/abs/2412.04714
Autor:
Puliti, Stefano, Lines, Emily R., Müllerová, Jana, Frey, Julian, Schindler, Zoe, Straker, Adrian, Allen, Matthew J., Winiwarter, Lukas, Rehush, Nataliia, Hristova, Hristina, Murray, Brent, Calders, Kim, Terryn, Louise, Coops, Nicholas, Höfle, Bernhard, Junttila, Samuli, Krůček, Martin, Krok, Grzegorz, Král, Kamil, Levick, Shaun R., Luck, Linda, Missarov, Azim, Mokroš, Martin, Owen, Harry J. F., Stereńczak, Krzysztof, Pitkänen, Timo P., Puletti, Nicola, Saarinen, Ninni, Hopkinson, Chris, Torresan, Chiara, Tomelleri, Enrico, Weiser, Hannah, Astrup, Rasmus
Proximally-sensed laser scanning offers significant potential for automated forest data capture, but challenges remain in automatically identifying tree species without additional ground data. Deep learning (DL) shows promise for automation, yet prog
Externí odkaz:
http://arxiv.org/abs/2408.06507
Autor:
Huang, Yunmei1 (AUTHOR) huan1643@purdue.edu, Ou, Botong2 (AUTHOR) bou@purdue.edu, Meng, Kexin2 (AUTHOR) meng147@purdue.edu, Yang, Baijian2 (AUTHOR) byang@purdue.edu, Carpenter, Joshua3 (AUTHOR) jcarpene@purdue.edu, Jung, Jinha3 (AUTHOR) jinha@purdue.edu, Fei, Songlin1 (AUTHOR) sfei@purdue.edu
Publikováno v:
Remote Sensing. Oct2024, Vol. 16 Issue 20, p3836. 16p.
This paper investigates tree species classification using Sentinel-2 multispectral satellite image time-series. Despite their critical importance for many applications, such maps are often unavailable, outdated, or inaccurate for large areas. The int
Externí odkaz:
http://arxiv.org/abs/2408.08887
Autor:
Gaydon, Charles, Roche, Floryne
Knowledge of tree species distribution is fundamental to managing forests. New deep learning approaches promise significant accuracy gains for forest mapping, and are becoming a critical tool for mapping multiple tree species at scale. To advance the
Externí odkaz:
http://arxiv.org/abs/2404.12064
Autor:
Harmon, Ira1 (AUTHOR) daisyw@cise.ufl.edu, Weinstein, Ben2 (AUTHOR) ben.weinstein@weecology.org, Bohlman, Stephanie3 (AUTHOR) sbohlman@ufl.edu, White, Ethan2 (AUTHOR) ethanwhite@ufl.edu, Wang, Daisy Zhe1 (AUTHOR)
Publikováno v:
Remote Sensing. Dec2024, Vol. 16 Issue 23, p4365. 23p.
Publikováno v:
Forest Engineering. Nov2024, Vol. 40 Issue 6, p53-63. 11p.
Autor:
Avtar, Ram1,2,3 (AUTHOR) chen@eis.hokudai.ac.jp, Chen, Xinyu1 (AUTHOR) jinjinf@yeah.net, Fu, Jinjin1 (AUTHOR) hiteshsupe@eis.hokudai.ac.jp, Alsulamy, Saleh4 (AUTHOR), Supe, Hitesh1 (AUTHOR) albertusstephanus.louw.s4@elms.hokudai.ac.jp, Pulpadan, Yunus Ali5 (AUTHOR) yunusp@iisermohali.ac.in, Louw, Albertus Stephanus1 (AUTHOR), Tatsuro, Nakaji6 (AUTHOR)
Publikováno v:
Remote Sensing. Nov2024, Vol. 16 Issue 21, p4060. 16p.
Autor:
Ni-Meister, Wenge1,2 (AUTHOR) flingo@gradcenter.cuny.edu, Albanese, Anthony1 (AUTHOR), Lingo, Francesca2 (AUTHOR)
Publikováno v:
Remote Sensing. Sep2024, Vol. 16 Issue 17, p3313. 24p.