| Who launched what, when and why; trends in global land-cover observation capacity from civilian earth observation satellites AS Belward, JO Skøien ISPRS Journal of Photogrammetry and Remote Sensing 103, 115-128, 2015 | 510 | 2015 |
| Top-kriging - geostatistics on stream networks JO Skøien, R Merz, G Blöschl Hydrology and Earth System Sciences 10 (2), 277-287, 2006 | 273 | 2006 |
| Characteristic space scales and timescales in hydrology JO Skøien, G Blöschl, AW Western Water Resources Research 39 (10), 1304, 2003 | 239 | 2003 |
| Characteristic space scales and timescales in hydrology JO Skøien, G Blöschl, AW Western Water Resources Research 39 (10), 2003 | 239 | 2003 |
| Spatiotemporal topological kriging of runoff time series JO Skøien, G Blöschl Water Resources Research 43 (9), W09419, 2007 | 130 | 2007 |
| Mapping ignorance: 300 years of collecting flowering plants in Africa J Stropp, RJ Ladle, AC M. Malhado, J Hortal, J Gaffuri, W H. Temperley, ... Global Ecology and Biogeography 25 (9), 1085-1096, 2016 | 106 | 2016 |
| INTAMAP: the design and implementation of an interoperable automated interpolation web service E Pebesma, D Cornford, G Dubois, G Heuvelink, D Hristopulos, J Pilz, ... Computers & Geosciences 37 (3), 343-352, 2011 | 103 | 2011 |
| Spatial prediction on river networks: comparison of top‐kriging with regional regression G Laaha, JO Skøien, G Blöschl Hydrological Processes 28 (2), 315-324, 2014 | 77 | 2014 |
| eHabitat, a multi-purpose Web Processing Service for ecological modeling G Dubois, M Schulz, J Skøien, L Bastin, S Peedell Environmental Modelling & Software 41, 123-133, 2013 | 75 | 2013 |
| Smooth regional estimation of low-flow indices: physiographical space based interpolation and top-kriging S Castiglioni, A Castellarin, A Montanari, JO Skøien, G Laaha, G Blöschl Hydrology and Earth System Sciences 15 (3), 715-727, 2011 | 70 | 2011 |
| Sciences Smooth regional estimation of low-flow indices: physiographical space based interpolation and top-kriging SC Hydrology, A Castellarin, A Montanari, JO Skøien, G Laaha | 70* | 2011 |
| Integrating field sampling, spatial statistics and remote sensing to map wetland vegetation in the Pantanal, Brazil J Arieira, DJ Karssenberg, SM De Jong, EA Addink, EG Couto, ... Biogeosciences 8, 667-686, 2011 | 69 | 2011 |
| rtop: An R package for interpolation of data with a variable spatial support, with an example from river networks JO Skøien, G Blöschl, G Laaha, E Pebesma, J Parajka, A Viglione Computers & Geosciences 67, 180-190, 2014 | 62 | 2014 |
| Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach? SA Archfield, A Pugliese, A Castellarin, JO Skøien, JE Kiang Hydrology and Earth System Sciences 17 (4), 1575-1588, 2013 | 57 | 2013 |
| Sampling scale effects in random fields and implications for environmental monitoring JO Skøien, G Blöschl Environmental Monitoring and Assessment 114 (1-3), 521-552, 2006 | 54 | 2006 |
| Catchments as space-time filters--a joint spatio-temporal geostatistical analysis of runoff and precipitation. JO Skøien, G Blöschl Hydrology & Earth System Sciences 10 (5), 2006 | 52 | 2006 |
| Catchments as space-time filters–a joint spatio-temporal geostatistical analysis of runoff and precipitation JO Skøien, G Blöschl Hydrol. Earth Syst. Sci 10, 645-662, 2006 | 52 | 2006 |
| Scale effects in estimating the variogram and implications for soil hydrology JO Skøien, G Blöschl Vadose Zone Journal 5 (1), 153-167, 2006 | 38 | 2006 |
| The role of station density for predicting daily runoff by top-kriging interpolation in Austria J Parajka, R Merz, JO Skøien, A Viglione Journal of Hydrology and Hydromechanics 63 (3), 228-234, 2015 | 34 | 2015 |
| The role of station density for predicting daily runoff by top-kriging interpolation in Austria J Parajka, R Merz, JO Skøien, A Viglione Journal of Hydrology and Hydromechanics 63 (3), 228-234, 2015 | 34 | 2015 |
