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Benoit Parmentier
Researcher at University of Maine
Publications - 21
Citations - 655
Benoit Parmentier is an academic researcher from University of Maine. The author has contributed to research in topics: Land cover & Land use, land-use change and forestry. The author has an hindex of 9, co-authored 21 publications receiving 423 citations. Previous affiliations of Benoit Parmentier include University of Maryland, College Park & University of California, Santa Barbara.
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Journal ArticleDOI
A suite of global, cross-scale topographic variables for environmental and biodiversity modeling
Giuseppe Amatulli,Sami Domisch,Mao-Ning Tuanmu,Mao-Ning Tuanmu,Benoit Parmentier,Ajay Ranipeta,Jeremy Malczyk,Walter Jetz,Walter Jetz +8 more
TL;DR: While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains.
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Recommendations for using the relative operating characteristic (ROC)
TL;DR: In this article, the authors suggest four improvements in the use and interpretation of the ROC curve and its AUC by highlighting important threshold points, interpreting the shape of the curve, defining lower and upper bounds for the AUC, and mapping the density of the presence within each bin of the RC curve.
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Systematic land cover bias in Collection 5 MODIS cloud mask and derived products — A global overview
TL;DR: In this paper, the authors calculated global mean cloud frequency for both products, for 2009, and found that inflated proportions of observations were flagged as cloudy in the Collection 5 MOD35 product, which resulted in significantly decreased and spatially biased data availability for Collection 5-derived composite MODIS land products such as land surface temperature (MOD11) and net primary productivity (MOD17).
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Spatio-temporal data on the air pollutant nitrogen dioxide derived from Sentinel satellite for France
TL;DR: A new spatio-temporal dataset collected and processed from the Sentinel 5P remote sensing platform is presented, of value for policy-makers and health assessment.
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Using multi‐timescale methods and satellite‐derived land surface temperature for the interpolation of daily maximum air temperature in Oregon
Benoit Parmentier,Benoit Parmentier,Benoit Parmentier,Brian J. McGill,Adam M. Wilson,James Regetz,Walter Jetz,Robert P. Guralnick,Mao-Ning Tuanmu,Mark Schildhauer +9 more
TL;DR: In this paper, the authors provide a comprehensive evaluation of three interpolation methods and rigorous evaluation of multi-timescale procedures that do and do not include additional environmental covariates including land cover and land surface temperatures.