| Where is positional uncertainty a problem for species distribution modelling? B Naimi, NAS Hamm, TA Groen, AK Skidmore, AG Toxopeus Ecography 37 (2), 191-203, 2014 | 1365 | 2014 |
| A machine learning method to estimate PM2. 5 concentrations across China with remote sensing, meteorological and land use information G Chen, S Li, LD Knibbs, NAS Hamm, W Cao, T Li, J Guo, H Ren, ... Science of the Total Environment 636, 52-60, 2018 | 479 | 2018 |
| Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling B Naimi, AK Skidmore, TA Groen, NAS Hamm Journal of biogeography 38 (8), 1497-1509, 2011 | 444 | 2011 |
| Statistics-based outlier detection for wireless sensor networks Y Zhang, NAS Hamm, N Meratnia, A Stein, M Van de Voort, PJM Havinga International Journal of Geographical Information Science 26 (8), 1373-1392, 2012 | 198 | 2012 |
| Estimating spatiotemporal distribution of PM1 concentrations in China with satellite remote sensing, meteorology, and land use information G Chen, LD Knibbs, W Zhang, S Li, W Cao, J Guo, H Ren, B Wang, ... Environmental Pollution 233, 1086-1094, 2018 | 183 | 2018 |
| Evaluating a thermal image sharpening model over a mixed agricultural landscape in India C Jeganathan, NAS Hamm, S Mukherjee, PM Atkinson, PLN Raju, ... International Journal of Applied Earth Observation and Geoinformation 13 (2 …, 2011 | 143 | 2011 |
| Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis A Datta, S Banerjee, AO Finley, NAS Hamm, M Schaap The Annals of Applied Statistics 10 (3), 1286-1316, 2016 | 127 | 2016 |
| The landscape epidemiology of echinococcoses AM Cadavid Restrepo, YR Yang, DP McManus, DJ Gray, P Giraudoux, ... Infectious Diseases of Poverty 5 (1), 1, 2016 | 120 | 2016 |
| Integrating remote sensing and geospatial big data for urban land use mapping: A review J Yin, J Dong, NAS Hamm, Z Li, J Wang, H Xing, P Fu International Journal of Applied Earth Observation and Geoinformation 103 …, 2021 | 103 | 2021 |
| Variance-based sensitivity analysis of the probability of hydrologically induced slope instability NAS Hamm, JW Hall, MG Anderson Computers & geosciences 32 (6), 803-817, 2006 | 67 | 2006 |
| Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases NAS Hamm, RJ Soares Magalhães, ACA Clements PLoS Neglected Tropical Diseases 9 (12), e0004164, 2015 | 62 | 2015 |
| A spatially varying coefficient model for mapping PM10 air quality at the European scale NAS Hamm, AO Finley, M Schaap, A Stein Atmospheric Environment 102, 393-405, 2015 | 57 | 2015 |
| Land cover change during a period of extensive landscape restoration in Ningxia Hui Autonomous Region, China AMC Restrepo, YR Yang, NAS Hamm, DJ Gray, TS Barnes, GM Williams, ... Science of the total environment 598, 669-679, 2017 | 49 | 2017 |
| Handling uncertainties in image mining for remote sensing studies A Stein, NAS Hamm, Q Ye International journal of remote sensing 30 (20), 5365-5382, 2009 | 47 | 2009 |
| Hydrological modelling of a drained grazing marsh under agricultural land use and the simulation of restoration management scenarios DHA Al-Khudhairy, JR Thompson, H Gavin, NAS Hamm Hydrological sciences journal 44 (6), 943-971, 1999 | 44 | 1999 |
| ELSA: Entropy-based local indicator of spatial association B Naimi, NAS Hamm, TA Groen, AK Skidmore, AG Toxopeus, ... Spatial statistics 29, 66-88, 2019 | 38 | 2019 |
| Geospatial mapping of soil organic carbon using regression kriging and remote sensing N Kumar, A Velmurugan, NAS Hamm, VK Dadhwal Journal of the Indian Society of Remote Sensing 46, 705-716, 2018 | 33 | 2018 |
| Exploring Spatiotemporal Phenological Patterns and Trajectories Using Self-Organizing Maps R Zurita-Milla, JAE van Gijsel, NAS Hamm, PWM Augustijn, A Vrieling IEEE Transactions on Geoscience and Remote Sensing 51 (4), 1914-1921, 2013 | 33 | 2013 |
| Variance-based sensitivity analysis of BIOME-BGC for gross and net primary production R Raj, NAS Hamm, C van der Tol, A Stein Ecological modelling 292, 26-36, 2014 | 31 | 2014 |
| A per-pixel, non-stationary mixed model for empirical line atmospheric correction in remote sensing NAS Hamm, PM Atkinson, EJ Milton Remote sensing of environment 124, 666-678, 2012 | 30 | 2012 |
Babak NaimiResearcher at University of Utrecht, The Netherlands在 uu.nl 的电子邮件经过验证
