| A review of assessing the accuracy of classifications of remotely sensed data RG Congalton Remote sensing of environment 37 (1), 35-46, 1991 | 8853 | 1991 |
| Assessing the accuracy of remotely sensed data: principles and practices RG Congalton, K Green CRC press, 2019 | 7792 | 2019 |
| Accuracy assessment: a user’s perspective M Story, RG Congalton Photogrammetric Engineering and remote sensing 52 (3), 397-399, 1986 | 1824 | 1986 |
| Assessing Landsat classification accuracy using discrete multivariate analysis statistical techniques RG Congalton, RG Oderwald, RA Mead Photogrammetric engineering and remote sensing 49 (12), 1671-1678, 1983 | 1064 | 1983 |
| A quantitative method to test for consistency and correctness in photointerpretation RG Congalton, RA Mead Photogrammetric Engineering and Remote Sensing 49 (1), 69-74, 1983 | 763 | 1983 |
| A quantitative comparison of change-detection algorithms for monitoring eelgrass from remotely sensed data RD Macleod, RG Congalton Photogrammetric engineering and remote sensing 64 (3), 207-216, 1998 | 672 | 1998 |
| Application of remote sensing and geographic information systems to forest fire hazard mapping E Chuvieco, RG Congalton Remote sensing of Environment 29 (2), 147-159, 1989 | 648 | 1989 |
| Remote sensing and geographic information system data integration: error sources and RG Congalton Photogrammetric Engineering & Remote Sensing 57 (6), 677-687, 1991 | 514 | 1991 |
| Determining forest species composition using high spectral resolution remote sensing data ME Martin, SD Newman, JD Aber, RG Congalton Remote sensing of environment 65 (3), 249-254, 1998 | 484 | 1998 |
| A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data RG Congalton Photogrammetric Engineering and Remote Sensing, 1988 | 470 | 1988 |
| Accuracy assessment and validation of remotely sensed and other spatial information RG Congalton International Journal of Wildland Fire 10 (4), 321-328, 2001 | 422 | 2001 |
| A comparison of urban mapping methods using high-resolution digital imagery N Thomas, C Hendrix, RG Congalton Photogrammetric Engineering & Remote Sensing 69 (9), 963-972, 2003 | 392 | 2003 |
| Automated cropland mapping of continental Africa using Google Earth Engine cloud computing J Xiong, PS Thenkabail, MK Gumma, P Teluguntla, J Poehnelt, ... ISPRS Journal of Photogrammetry and Remote Sensing 126, 225-244, 2017 | 349 | 2017 |
| Evaluating the potential for measuring river discharge from space DM Bjerklie, SL Dingman, CJ Vorosmarty, CH Bolster, RG Congalton Journal of hydrology 278 (1-4), 17-38, 2003 | 335 | 2003 |
| A practical look at the sources of confusion in error matrix generation RG Congalton, K Green Photogrammetric engineering and remote sensing 59 (5), 641-644, 1993 | 306 | 1993 |
| Global land cover mapping: A review and uncertainty analysis RG Congalton, J Gu, K Yadav, P Thenkabail, M Ozdogan Remote Sensing 6 (12), 12070-12093, 2014 | 292 | 2014 |
| Using spatial autocorrelation analysis to explore the errors in maps generated from remotely sensed data RG Congalton Photogrammetric engineering and remote sensing, 1988 | 285 | 1988 |
| Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 data on Google Earth Engine J Xiong, PS Thenkabail, JC Tilton, MK Gumma, P Teluguntla, A Oliphant, ... Remote Sensing 9 (10), 1065, 2017 | 284 | 2017 |
| A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform P Teluguntla, PS Thenkabail, A Oliphant, J Xiong, MK Gumma, ... ISPRS Journal of Photogrammetry and Remote Sensing 144, 325-340, 2018 | 245 | 2018 |
| Effects of landscape characteristics on amphibian distribution in a forest-dominated landscape HL Herrmann, KJ Babbitt, MJ Baber, RG Congalton Biological Conservation 123 (2), 139-149, 2005 | 226 | 2005 |
Murali Krishna GummaCluster Leader – Geospatial Sciences and Big Data at ICRISAT (IRRI, IWMI, JNTU)Verified email at cgiar.org
