George P. Petropoulos
George P. Petropoulos
Department of Geography, Harokopio University, Athens, Greece
Verified email at - Homepage
Cited by
Cited by
Surface soil moisture retrievals from remote sensing: Current status, products & future trends
GP Petropoulos, G Ireland, B Barrett
Physics and Chemistry of the Earth, Parts a/b/c 83, 36-56, 2015
A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture
G Petropoulos, TN Carlson, MJ Wooster, S Islam
Progress in Physical Geography 33 (2), 224-250, 2009
Support vector machines and object-based classification for obtaining land-use/cover cartography from Hyperion hyperspectral imagery
GP Petropoulos, C Kalaitzidis, KP Vadrevu
Computers & Geosciences 41, 99-107, 2012
A new synergistic approach for monitoring wetlands using Sentinels-1 and 2 data with object-based machine learning algorithms
A Whyte, KP Ferentinos, GP Petropoulos
Environmental Modelling & Software 104, 40-54, 2018
The International Soil Moisture Network: serving Earth system science for over a decade
W Dorigo, I Himmelbauer, D Aberer, L Schremmer, I Petrakovic, L Zappa, ...
Hydrology and Earth System Sciences Discussions 2021, 1-83, 2021
Co-Orbital Sentinel 1 and 2 for LULC mapping with emphasis on wetlands in a mediterranean setting based on machine learning
A Chatziantoniou, GP Petropoulos, E Psomiadis
Remote Sensing 9 (12), 1259, 2017
Burnt area delineation from a uni-temporal perspective based on Landsat TM imagery classification using Support Vector Machines
GP Petropoulos, C Kontoes, I Keramitsoglou
International Journal of Applied Earth Observation and Geoinformation 13 (1 …, 2011
Hyperion hyperspectral imagery analysis combined with machine learning classifiers for land use/cover mapping
GP Petropoulos, K Arvanitis, N Sigrimis
Expert systems with Applications 39 (3), 3800-3809, 2012
Land use/land cover in view of earth observation: Data sources, input dimensions, and classifiers—A review of the state of the art
PC Pandey, N Koutsias, GP Petropoulos, PK Srivastava, E Ben Dor
Geocarto International 36 (9), 957-988, 2021
A comparison of spectral angle mapper and artificial neural network classifiers combined with Landsat TM imagery analysis for obtaining burnt area mapping
GP Petropoulos, KP Vadrevu, G Xanthopoulos, G Karantounias, ...
Sensors 10 (3), 1967-1985, 2010
Surface soil moisture retrievals over partially vegetated areas from the synergy of Sentinel-1 and Landsat 8 data using a modified water-cloud model
Y Bao, L Lin, S Wu, KAK Deng, GP Petropoulos
International journal of applied earth observation and geoinformation 72, 76-85, 2018
Actual evapotranspiration in drylands derived from in-situ and satellite data: Assessing biophysical constraints
M García, I Sandholt, P Ceccato, M Ridler, E Mougin, L Kergoat, L Morillas, ...
Remote Sensing of Environment 131, 103-118, 2013
Towards improved spatio-temporal resolution soil moisture retrievals from the synergy of SMOS and MSG SEVIRI spaceborne observations
M Piles, GP Petropoulos, N Sánchez, Á González-Zamora, G Ireland
Remote Sensing of Environment 180, 403-417, 2016
Exploring the relationships between post-fire vegetation regeneration dynamics, topography and burn severity: A case study from the Montane Cordillera Ecozones of Western Canada
G Ireland, GP Petropoulos
Applied Geography 56, 232-248, 2015
Hyperspectral remote sensing in precision agriculture: Present status, challenges, and future trends
P Singh, PC Pandey, GP Petropoulos, A Pavlides, PK Srivastava, ...
Hyperspectral remote sensing, 121-146, 2020
Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets
SK Singh, PK Srivastava, S Szabó, GP Petropoulos, M Gupta, T Islam
Geocarto international 32 (2), 113-127, 2017
Quantifying land use/land cover spatio-temporal landscape pattern dynamics from Hyperion using SVMs classifier and FRAGSTATS®
S Lamine, GP Petropoulos, SK Singh, S Szabó, NEI Bachari, ...
Geocarto international 33 (8), 862-878, 2018
Examining the capability of supervised machine learning classifiers in extracting flooded areas from Landsat TM imagery: a case study from a Mediterranean flood
G Ireland, M Volpi, GP Petropoulos
Remote sensing 7 (3), 3372-3399, 2015
Change detection of surface mining activity and reclamation based on a machine learning approach of multi-temporal Landsat TM imagery
GP Petropoulos, P Partsinevelos, Z Mitraka
Geocarto International 28 (4), 323-342, 2013
Determining the use of Sentinel-2A MSI for wildfire burning & severity detection
C Amos, GP Petropoulos, KP Ferentinos
International journal of remote sensing 40 (3), 905-930, 2019
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