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Rasmus Houborg
Rasmus Houborg
Planet Labs
Verified email at planet.com
Title
Cited by
Cited by
Year
A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales
MC Anderson, JM Norman, WP Kustas, R Houborg, PJ Starks, N Agam
Remote Sensing of Environment 112 (12), 4227-4241, 2008
4212008
Combining vegetation index and model inversion methods for the extraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data
R Houborg, H Soegaard, E Boegh
Remote Sensing of Environment 106 (1), 39-58, 2007
3582007
Drought indicators based on model‐assimilated Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage observations
R Houborg, M Rodell, B Li, R Reichle, BF Zaitchik
Water Resources Research 48 (7), 2012
3352012
The future of Earth observation in hydrology
MF McCabe, M Rodell, DE Alsdorf, DG Miralles, R Uijlenhoet, W Wagner, ...
Hydrology and earth system sciences 21 (7), 3879-3914, 2017
3212017
Mapping leaf chlorophyll and leaf area index using inverse and forward canopy reflectance modeling and SPOT reflectance data
R Houborg, E Boegh
Remote sensing of environment 112 (1), 186-202, 2008
2212008
Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at the field scale
R Houborg, M Anderson, C Daughtry
Remote Sensing of Environment 113 (1), 259-274, 2009
2032009
Response of Chlorophyll, Carotenoid and SPAD-502 Measurement to Salinity and Nutrient Stress in Wheat (Triticum aestivum L.)
SH Shah, R Houborg, MF McCabe
Agronomy 7 (3), 61, 2017
1782017
A cubesat enabled spatio-temporal enhancement method (CESTEM) utilizing Planet, Landsat and MODIS data
R Houborg, MF McCabe
Remote Sensing of Environment 209, 211-226, 2018
1672018
High-Resolution NDVI from planet’s constellation of earth observing nano-satellites: A new data source for precision agriculture
R Houborg, MF McCabe
Remote Sensing 8 (9), 768, 2016
1362016
Joint leaf chlorophyll content and leaf area index retrieval from Landsat data using a regularized model inversion system (REGFLEC)
R Houborg, M McCabe, A Cescatti, F Gao, M Schull, A Gitelson
Remote Sensing of Environment 159, 203-221, 2015
1292015
A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning
R Houborg, MF McCabe
ISPRS Journal of Photogrammetry and Remote Sensing 135, 173-188, 2018
1262018
Advances in remote sensing of vegetation function and traits
R Houborg, JB Fisher, AK Skidmore
International Journal of Applied Earth Observation and Geoinformation 43, 1-6, 2015
1252015
Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP
R Houborg, A Cescatti, M Migliavacca, WP Kustas
Agricultural and Forest Meteorology 177, 10-23, 2013
1182013
Daily Retrieval of NDVI and LAI at 3 m Resolution via the Fusion of CubeSat, Landsat, and MODIS Data
R Houborg, MF McCabe
Remote Sensing 10 (6), 890, 2018
972018
Regional simulation of ecosystem CO2 and water vapor exchange for agricultural land using NOAA AVHRR and Terra MODIS satellite data. Application to Zealand, Denmark
RM Houborg, H Soegaard
Remote Sensing of Environment 93 (1-2), 150-167, 2004
822004
CubeSats in hydrology: Ultrahigh‐resolution insights into vegetation dynamics and terrestrial evaporation
MF McCabe, B Aragon, R Houborg, J Mascaro
Water Resources Research 53 (12), 10017-10024, 2017
792017
A random forest machine learning approach for the retrieval of leaf chlorophyll content in wheat
SH Shah, Y Angel, R Houborg, S Ali, MF McCabe
Remote Sensing 11 (8), 920, 2019
672019
Using leaf chlorophyll to parameterize light-use-efficiency within a thermal-based carbon, water and energy exchange model
R Houborg, MC Anderson, CST Daughtry, WP Kustas, M Rodell
Remote Sensing of Environment 115 (7), 1694-1705, 2011
602011
Intercomparison of a ‘bottom-up’and ‘top-down’modeling paradigm for estimating carbon and energy fluxes over a variety of vegetative regimes across the US
R Houborg, MC Anderson, JM Norman, T Wilson, T Meyers
Agricultural and forest meteorology 149 (12), 2162-2182, 2009
602009
CubeSats enable high spatiotemporal retrievals of crop-water use for precision agriculture
B Aragon, R Houborg, K Tu, JB Fisher, M McCabe
Remote Sensing 10 (12), 1867, 2018
562018
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