| Implementation of machine-learning classification in remote sensing: An applied review AE Maxwell, TA Warner, F Fang International journal of remote sensing 39 (9), 2784-2817, 2018 | 1851 | 2018 |
| Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America T Brandtberg, TA Warner, RE Landenberger, JB McGraw Remote sensing of Environment 85 (3), 290-303, 2003 | 615 | 2003 |
| A comparison of multispectral and multitemporal information in high spatial resolution imagery for classification of individual tree species in a temperate hardwood forest T Key, TA Warner, JB McGraw, MA Fajvan Remote Sensing of Environment 75 (1), 100-112, 2001 | 331 | 2001 |
| Evaluation of Sampling and Cross-Validation Tuning Strategies for Regional-Scale Machine Learning Classification AE Ramezan, C.A., Warner, T.A., and Maxwell Remote Sensing 11 (2), 185, 2019 | 301 | 2019 |
| Accuracy assessment in convolutional neural network-based deep learning remote sensing studies—Part 1: Literature review AE Maxwell, TA Warner, LA Guillén Remote Sensing 13 (13), 2450, 2021 | 259 | 2021 |
| Forest type mapping using object-specific texture measures from multispectral Ikonos imagery M Kim, M Madden, TA Warner Photogrammetric Engineering & Remote Sensing 75 (7), 819-829, 2009 | 235 | 2009 |
| Estimation of optimal image object size for the segmentation of forest stands with multispectral IKONOS imagery M Kim, M Madden, T Warner Object-based image analysis: spatial concepts for knowledge-driven remote …, 2008 | 228 | 2008 |
| Multi-scale GEOBIA with very high spatial resolution digital aerial imagery: scale, texture and image objects M Kim, TA Warner, M Madden, DS Atkinson International Journal of Remote Sensing 32 (10), 2825-2850, 2011 | 224 | 2011 |
| Kernel-based extreme learning machine for remote-sensing image classification M Pal, AE Maxwell, TA Warner Remote Sensing Letters 4 (9), 853-862, 2013 | 218 | 2013 |
| Effects of training set size on supervised machine-learning land-cover classification of large-area high-resolution remotely sensed data CA Ramezan, TA Warner, AE Maxwell, BS Price Remote Sensing 13 (3), 368, 2021 | 174 | 2021 |
| Apartheid representations in a digital landscape: GIS, remote sensing and local knowledge in Kiepersol, South Africa D Weiner, TA Warner, TM Harris, RM Levin Cartography and Geographic Information Systems 22 (1), 30-44, 1995 | 160 | 1995 |
| Integrating visible, near-infrared and short-wave infrared hyperspectral and multispectral thermal imagery for geological mapping at Cuprite, Nevada X Chen, TA Warner, DJ Campagna Remote Sensing of Environment 110 (3), 344-356, 2007 | 135 | 2007 |
| Change detection accuracy and image properties: a study using simulated data A Almutairi, TA Warner Remote Sensing 2 (6), 1508-1529, 2010 | 128 | 2010 |
| Multi-scale linkages between topographic attributes and vegetation indices in a mountainous landscape Y Deng, X Chen, E Chuvieco, T Warner, JP Wilson Remote Sensing of Environment 111 (1), 122-134, 2007 | 126 | 2007 |
| The SAGE Handbook of Remote Sensing TA Warner, GM Foody, MD Nellis The SAGE Handbook of Remote Sensing, 1-568, 2009 | 121 | 2009 |
| A time series of annual land use and land cover maps of China from 1982 to 2013 generated using AVHRR GIMMS NDVI3g data Y He, E Lee, TA Warner Remote Sensing of Environment 199, 201-217, 2017 | 118 | 2017 |
| Using Thematic Mapper data for change detection and sustainable use of cultivated land: a case study in the Yellow River delta, China GX Zhao, G Lin, T Warner International Journal of Remote Sensing 25 (13), 2509-2522, 2004 | 116 | 2004 |
| Assessing machine-learning algorithms and image-and lidar-derived variables for GEOBIA classification of mining and mine reclamation AE Maxwell, TA Warner, MP Strager, JF Conley, AL Sharp International Journal of Remote Sensing 36 (4), 954-978, 2015 | 98 | 2015 |
| Large-area, high spatial resolution land cover mapping using random forests, GEOBIA, and NAIP orthophotography: Findings and recommendations AE Maxwell, MP Strager, TA Warner, CA Ramezan, AN Morgan, ... Remote Sensing 11 (12), 1409, 2019 | 88 | 2019 |
| Accuracy assessment in convolutional neural network-based deep learning remote sensing studies—Part 2: Recommendations and best practices AE Maxwell, TA Warner, LA Guillén Remote Sensing 13 (13), 2591, 2021 | 86 | 2021 |
Aaron MaxwellWest Virginia University Department of Geology and GeographyVerified email at mail.wvu.edu