Results 211 to 220 of about 130,242 (295)

Wall‐to‐wall Amazon forest height mapping with Planet NICFI, Aerial LiDAR, and a U‐Net regression model

Remote Sensing in Ecology and Conservation, EarlyView.
Tree canopy height is a key indicator of forest biomass and structure, yet accurate mapping across the Amazon remains challenging. Here, we generated a canopy height map of the Amazon forest at ~4.8 m resolution using Planet NICFI imagery and a deep learning U‐Net model trained with airborne LiDAR data.
Fabien H. Wagner, Ricardo Dalagnol, Griffin Carter, Mayumi C. M. Hirye, Shivraj Gill, Le Bienfaiteur Sagang Takougoum, Samuel Favrichon, Michael Keller, Jean P. H. B. Ometto, Lorena Alves, Cynthia Creze, Stephanie P. George‐Chacon, Shuang Li, Zhihua Liu, Adugna Mullissa, Yan Yang, Erone G. Santos, Sarah R. Worden, Martin Brandt, Philippe Ciais, Stephen C. Hagen, Sassan Saatchi   +21 more
wiley   +1 more source

Remote sensing reveals that wild herbivores limit senescent vegetation accumulation on dryland conservation reserves. [PDF]

Ecol Appl
Smith MS, Fisher AG, Finlayson G, Letnic M.   +3 more
europepmc   +1 more source

WP2 First surveillance bulletin including data from all sentinel sites

The periodic bulletins will compile and summarise data from all sites (at least three bulletins during the duration of the project, frequency will depend on the phase of the epidemic). However, from the beginning of the project, weekly automatic reports (graphs, tables) will be available on the I-MOVE-COVID-19 website.
openaire   +1 more source

Sentinel site surveillance of nontuberculous mycobacteria pulmonary diseases in Zhejiang, China, 2011–2013

The Brazilian Journal of Infectious Diseases, 2015
Bi, Sheng, Xu, Kai-jin, Ji, Zhong-kang, Zheng, Bei-wen, Sheng, Ji-fang   +4 more
openaire   +4 more sources

Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs

Remote Sensing in Ecology and Conservation, EarlyView.
Accurately estimating forest age is key to understanding how forests recover and evaluating restoration success. We developed a two‐step deep learning approach using historical greyscale aerial photographs to map forest age at fine spatial scales. By combining a pre‐trained model with localized fine‐tuning, our U‐Net + ResNet50 architecture achieved ...
Ying Ki Law, Yi‐Fei Gu, Shuwen Liu, Guangqin Song, Aland H. Y. Chan, Cham Man Tse, Zhonghua Liu, Martha J. Ledger, Billy C. H. Hau, Sawaid Abbas, Jin Wu   +10 more
wiley   +1 more source

Multimodal parameters for the diagnosis of putative primaries of cancer of unknown primary. [PDF]

iScience
Pan S, Wang J, Liu J, He S, Liu X, Zhang X, Jiang S, Wang Y, Zhou X, Song S, Zhou L, Li H, Luo J, Luo Z, Hu S, Wang H, Wang Q, Hu X.   +17 more
europepmc   +1 more source

Using phenology to improve invasive plant detection in fine‐scale hyperspectral drone‐based images

Remote Sensing in Ecology and Conservation, EarlyView.
Using drone‐based hyperspectral images of mixed temperate successional forests collected over a growing season, detection algorithms were produced for three invasive species of interest, which are not only invasive in Virginia but also much of the U.S.: Ailanthus altissima (tree of heaven), Elaeagnus umbellata (autumn olive), and Rhamnus davurica ...
Kelsey S. Huelsman, Howard E. Epstein, Xi Yang, Roderick Walker   +3 more
wiley   +1 more source

WP2 Third surveillance bulletin including data from all sentinel sites

Third surveillance bulletin including data from all sentinel ...
openaire   +1 more source

Monitoring feral pigs (Sus scrofa): Complementarity between autonomous sensing methods increases detection probability

Remote Sensing in Ecology and Conservation, EarlyView.
Invasive alien species are a major threat for biodiversity worldwide and effective monitoring is paramount to inform management. In this study we used a multi‐season occupancy model to assess probability of detection between camera traps and passive acoustic recorders for feral pigs (Sus scrofa) during 1 year of data collection.
Marina D. A. Scarpelli, Stewart Macdonald, Maryam Golchin, Simon Linke, Jens G. Froese   +4 more
wiley   +1 more source

Nationwide monthly burned area monitoring in Indonesia using Sentinel-2. [PDF]

PLoS One
Gaveau DLA, Descals A, Salim MA.
europepmc   +1 more source