G
G. Arturo Sánchez-Azofeifa
Researcher at University of Alberta
Publications - 91
Citations - 7816
G. Arturo Sánchez-Azofeifa is an academic researcher from University of Alberta. The author has contributed to research in topics: Tropical and subtropical dry broadleaf forests & Deforestation. The author has an hindex of 39, co-authored 80 publications receiving 7119 citations. Previous affiliations of G. Arturo Sánchez-Azofeifa include Smithsonian Tropical Research Institute.
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Satellite-based observations of the green depressing cropping system in a farming-pastoral ecotone of northern China
Xin Chen,Xin Chen,Xin Chen,Pingli An,Pingli An,Kati Laakso,G. Arturo Sánchez-Azofeifa,Fangtian Wang,Fangtian Wang,Guoliang Zhang,Guoliang Zhang,Li Jiang,Li Jiang,Yi Zhou,Yi Zhou,Fei Lun,Fei Lun,Lidong Zou,Lidong Zou,Rui Jiang,Zhihua Pan +20 more
TL;DR: In this article, the authors present a study that analyses green depressing cropping fields and their related farmland use patterns in Ulanqab, China, taking into consideration satellite imagery, ground truth data, phenological records, and other ancillary data from 2015 to 2019 at the Ulanqiab region.
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Tropical dry forest resilience and water use efficiency: an analysis of productivity under climate change
Kayla Stan,G. Arturo Sánchez-Azofeifa,Sandra M. Durán,Michael Hesketh,Kati Laakso,Carlos Portillo-Quintero,Cassidy Rankine,Sebastian Doetterl +7 more
TL;DR: In this paper, the authors evaluate the resilience of tropical dry forests to water stress and droughts by increasing their rain use efficiency in drier years and recovering to average RUE in the year following a drought.
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Using visible-near-infrared spectroscopy to classify lichens at a Neotropical Dry Forest
TL;DR: In this article, the authors explored the spectral properties of lichens and their host's bark and found that the lichen signatures tend to mask the spectral contributions from bark, however, there are some specific groups of species with high bark mixing probably due to their nature and the similarities between the spectral features of lichen and bark spectra.
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Improved collaborative representation model with multitask learning using spatial support for target detection in hyperspectral imagery
TL;DR: An improved collaborative representation model with multitask learning using spatial support (ICRTD-MTL) for target detection in hyperspectral imagery and the experimental results suggest that the proposed algorithm obtains an excellent performance.
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Can we increase the impacts from payments for ecosystem services? Impact rose over time in Costa Rica, yet spatial variation indicates more potential
TL;DR: In this paper, the authors examine shifts within Costa Rica's Pagos por Servicios Ambientales (PSA) program and study shifts in impact over time across early periods and whether further adjustments could raise contributions.