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Temilola Fatoyinbo
Temilola Fatoyinbo
NASA Goddard Space Flight Center
Bestätigte E-Mail-Adresse bei nasa.gov
Titel
Zitiert von
Zitiert von
Jahr
The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography
R Dubayah, JB Blair, S Goetz, L Fatoyinbo, M Hansen, S Healey, ...
Science of remote sensing 1, 100002, 2020
6372020
Global maps of twenty-first century forest carbon fluxes
NL Harris, DA Gibbs, A Baccini, RA Birdsey, S De Bruin, M Farina, ...
Nature Climate Change 11 (3), 234-240, 2021
6292021
Global declines in human‐driven mangrove loss
L Goldberg, D Lagomasino, N Thomas, T Fatoyinbo
Global change biology 26 (10), 5844-5855, 2020
5692020
Mangrove canopy height globally related to precipitation, temperature and cyclone frequency
M Simard, L Fatoyinbo, C Smetanka, VH Rivera-Monroy, ...
Nature Geoscience 12 (1), 40-45, 2019
3612019
Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions
N Pettorelli, M Wegmann, A Skidmore, S Mücher, TP Dawson, ...
Remote sensing in ecology and conservation 2 (3), 122-131, 2016
3132016
Flood extent mapping for Namibia using change detection and thresholding with SAR
S Long, TE Fatoyinbo, F Policelli
Environmental Research Letters 9 (3), 035002, 2014
2472014
Height and biomass of mangroves in Africa from ICESat/GLAS and SRTM
TE Fatoyinbo, M Simard
International Journal of Remote Sensing 34 (2), 668-681, 2013
2262013
Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California
L Duncanson, A Neuenschwander, S Hancock, N Thomas, T Fatoyinbo, ...
Remote Sensing of Environment 242, 111779, 2020
1972020
Landscape‐scale extent, height, biomass, and carbon estimation of Mozambique's mangrove forests with Landsat ETM+ and Shuttle Radar Topography Mission elevation data
TE Fatoyinbo, M Simard, RA Washington‐Allen, HH Shugart
Journal of Geophysical Research: Biogeosciences 113 (G2), 2008
1842008
Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission
L Duncanson, JR Kellner, J Armston, R Dubayah, DM Minor, S Hancock, ...
Remote Sensing of Environment 270, 112845, 2022
1412022
Future carbon emissions from global mangrove forest loss
MF Adame, RM Connolly, MP Turschwell, CE Lovelock, T Fatoyinbo, ...
Global Change Biology 27 (12), 2856-2866, 2021
1322021
Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping
CA Silva, L Duncanson, S Hancock, A Neuenschwander, N Thomas, ...
Remote Sensing of Environment 253, 112234, 2021
1162021
Advanced land observing satellite phased array type L-Band SAR (ALOS PALSAR) to inform the conservation of mangroves: Sundarbans as a case study
WA Cornforth, TE Fatoyinbo, TP Freemantle, N Pettorelli
Remote sensing 5 (1), 224-237, 2013
1122013
Integrating remote sensing with ecology and evolution to advance biodiversity conservation
J Cavender-Bares, FD Schneider, MJ Santos, A Armstrong, A Carnaval, ...
Nature Ecology & Evolution 6 (5), 506-519, 2022
1062022
Mapping mangrove extent and change: A globally applicable approach
N Thomas, P Bunting, R Lucas, A Hardy, A Rosenqvist, T Fatoyinbo
Remote Sensing 10 (9), 1466, 2018
1012018
Harnessing big data to support the conservation and rehabilitation of mangrove forests globally
TA Worthington, DA Andradi-Brown, R Bhargava, C Buelow, P Bunting, ...
One Earth 2 (5), 429-443, 2020
922020
The global ecosystem dynamics investigation
R Dubayah, SJ Goetz, JB Blair, TE Fatoyinbo, M Hansen, SP Healey, ...
AGU Fall Meeting Abstracts 2014, U14A-07, 2014
862014
GEDI launches a new era of biomass inference from space
R Dubayah, J Armston, SP Healey, JM Bruening, PL Patterson, JR Kellner, ...
Environmental Research Letters 17 (9), 095001, 2022
812022
Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta
T Fatoyinbo, EA Feliciano, D Lagomasino, SK Lee, C Trettin
Environmental Research Letters 13 (2), 025012, 2018
752018
Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data
R Lucas, R Van De Kerchove, V Otero, D Lagomasino, L Fatoyinbo, ...
Remote Sensing of Environment 237, 111543, 2020
742020
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