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Russell Congalton
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Cited by
Year
A review of assessing the accuracy of classifications of remotely sensed data
RG Congalton
Remote sensing of environment 37 (1), 35-46, 1991
103851991
Assessing the accuracy of remotely sensed data: principles and practices
RG Congalton, K Green
CRC press, 2019
91102019
Accuracy assessment: a user’s perspective
M Story, RG Congalton
Photogrammetric Engineering and remote sensing 52 (3), 397-399, 1986
22221986
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
11641983
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
8121983
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
7571989
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
7491998
Accuracy assessment and validation of remotely sensed and other spatial information
RG Congalton
International journal of wildland fire 10 (4), 321-328, 2001
5752001
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
5482017
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
5241998
A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data.
RG Congalton
5091988
Remote sensing and geographic information system data integration- Error sources and research issues
R Lunetta, R Congalton, L Fenstermaker, J Jensen, K Mcgwire, LR Tinney
Photogrammetric engineering and remote sensing 57 (6), 677-687, 1991
5051991
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
4892018
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
4302017
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
4212003
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
4102003
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
3792014
A practical look at the sources of confusion in error matrix generation.
RG Congalton, K Green
3411993
Using spatial autocorrelation analysis to explore the errors in maps generated from remotely sensed data.
RG Congalton
2961988
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
2472005
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