المؤلفون: Gengsheng Fang, Hao Xu, Sheng-I Yang, Xiongwei Lou, Luming Fang

المصدر: Ecological Indicators, Vol 151, Iss , Pp 110296- (2023)

مصطلحات موضوعية: Remote sensing, Forest variables, SAR, Satellite images, Sensors, Ecology, QH540-549.5

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1470160X23004387; https://doaj.org/toc/1470-160X

URL الوصول: https://doaj.org/article/bc53855f0b9748c2a94100c9b735c974

المؤلفون: Ferry, Björn, Rune, Håkan, Andersson, Ulf, Green, Martin

المصدر: Ornis Svecica BECC: Biodiversity and Ecosystem services in a Changing Climate. 30:13-30

مصطلحات موضوعية: Climate change, Community Temperature Index, Forest variables, Long-term censusing, Point counts, Naturvetenskap, Biologi, Zoologi, Natural Sciences, Biological Sciences, Zoology

URL الوصول: https://lup.lub.lu.se/record/9ec11433-95a6-4d7f-b379-9192037653b6
http://dx.doi.org/10.34080/os.v30.19633

المؤلفون: Zhihui Wang, Yi Bai, Jianfeng Hou, Fei Li, Xuqing Li, Rui Cao, Yuyue Deng, Huaibin Wang, Yurui Jiang, Wanqin Yang

المصدر: Forests, Vol 13, Iss 2, p 289 (2022)

مصطلحات موضوعية: bacterial community, forest succession, forest variables, fungal community, non-woody debris, soil biodiversity, Plant ecology, QK900-989

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1999-4907/13/2/289; https://doaj.org/toc/1999-4907

URL الوصول: https://doaj.org/article/25af65f6eb244c1a9879c3f296e5d870

المؤلفون: Heikki Astola, Lauri Seitsonen, Eelis Halme, Matthieu Molinier, Anne Lönnqvist

المصدر: Remote Sensing, Vol 13, Iss 12, p 2392 (2021)

مصطلحات موضوعية: deep learning, deep neural networks, transfer learning, sentinel-2, boreal forest, forest variables, Science

وصف الملف: electronic resource

Relation: https://www.mdpi.com/2072-4292/13/12/2392; https://doaj.org/toc/2072-4292

URL الوصول: https://doaj.org/article/b7a0a7d1f39546f2a130d67d8e6766fc

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.

المؤلفون: André Almeida, Fabio Gonçalves, Gilson Silva, Rodolfo Souza, Robert Treuhaft, Weslei Santos, Diego Loureiro, Márcia Fernandes

المصدر: Remote Sensing, Vol 12, Iss 21, p 3560 (2020)

مصطلحات موضوعية: REDD+, digital aerial photogrammetry (DAP), UAS, drone, structure from motion (SfM), plot-level forest variables, Science

وصف الملف: electronic resource

Relation: https://www.mdpi.com/2072-4292/12/21/3560; https://doaj.org/toc/2072-4292

URL الوصول: https://doaj.org/article/fe85a264dad042a7a055968cd47def1c

المؤلفون: Goldaraz Ugarte, Xabier

المساهمون: Escuela Técnica Superior de Ingeniería Agronómica y Biociencias, Nekazaritzako Ingeniaritzako eta Biozientzietako Goi Mailako Eskola Teknikoa, Álvarez Mozos, Jesús, Aranguren Erice, Itxaso

مصطلحات موضوعية: Random Forests, LiDAR, Variables forestales, Sentinel-1, Baso-aldagaiak, Sentinel-2, Forest variables

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=od______2347::e22a5faaf688ef72d415a6037f994c39
https://hdl.handle.net/2454/44769

المؤلفون: Matthieu Molinier, Lauri Seitsonen, Eelis Halme, Anne Lönnqvist, Heikki Astola

المصدر: Remote Sensing, Vol 13, Iss 2392, p 2392 (2021)
Astola, H, Seitsonen, L, Halme, E, Molinier, M & Lönnqvist, A 2021, ' Deep neural networks with transfer learning for forest variable estimation using sentinel-2 imagery in boreal forest ', Remote Sensing, vol. 13, no. 12, 2392 . https://doi.org/10.3390/rs13122392
Remote Sensing; Volume 13; Issue 12; Pages: 2392

مصطلحات موضوعية: 010504 meteorology & atmospheric sciences, Mean squared error, Science, 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, Deep neural networks, Boreal forest, Forest variables, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, Forest inventory, Pixel, business.industry, Deep learning, Sampling (statistics), 15. Life on land, Random forest, Transfer learning, Lidar, Feature (computer vision), deep learning, deep neural networks, transfer learning, sentinel-2, boreal forest, forest variables, stem volume, General Earth and Planetary Sciences, Environmental science, Artificial intelligence, Sentinel-2, business, Stem volume

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78b49984c9b89ce73d1188e91cb8f296
https://doi.org/10.3390/rs13122392

المؤلفون: Kalle Eerikäinen, Sahas M. Shrestha, Heikki Parikka, Yam P. Pokharel, Eero Muinonen

المصدر: Remote Sensing, Vol 4, Iss 12, Pp 3920-3947 (2012)

مصطلحات موضوعية: data imputation, GIS, k-nearest neighbors, mapping forest variables, nonlinear mixed-effects model, Open Source software, Landsat, MODIS, Science

وصف الملف: electronic resource

Relation: http://www.mdpi.com/2072-4292/4/12/3920; https://doaj.org/toc/2072-4292

URL الوصول: https://doaj.org/article/08546f29b3494a6a803a5f42f82930e3

المؤلفون: Dirkse, G. M., Daamen, W. P.

المصدر: Community Ecology, 2004 Jan 01. 5(1), 115-120.

URL الوصول: https://www.jstor.org/stable/90002571