| 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 | 1506 | 2018 |
| Kernel-based extreme learning machine for remote-sensing image classification M Pal, AE Maxwell, TA Warner Remote Sensing Letters 4 (9), 853-862, 2013 | 210 | 2013 |
| 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 | 155 | 2021 |
| 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 | 97 | 2021 |
| 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 | 84 | 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 | 78 | 2019 |
| Comparison of NAIP orthophotography and RapidEye satellite imagery for mapping of mining and mine reclamation AE Maxwell, MP Strager, TA Warner, NP Zégre, CB Yuill GIScience & Remote Sensing 51 (3), 301-320, 2014 | 66 | 2014 |
| Land cover classification and feature extraction from National Agriculture Imagery Program (NAIP) Orthoimagery: A review AE Maxwell, TA Warner, BC Vanderbilt, CA Ramezan Photogrammetric Engineering & Remote Sensing 83 (11), 737-747, 2017 | 64 | 2017 |
| Accuracy assessment in convolutional neural network-based deep learning remote sensing studies—Part 2: Recommendations and best practices AE Maxwell, TA Warner, LA Guillen Remote Sensing 13 (13), 2591, 2021 | 62 | 2021 |
| Mapping the topographic features of mining-related valley fills using mask R-CNN deep learning and digital elevation data AE Maxwell, P Pourmohammadi, JD Poyner Remote Sensing 12 (3), 547, 2020 | 62 | 2020 |
| Predicting palustrine wetland probability using random forest machine learning and digital elevation data-derived terrain variables AE Maxwell, TA Warner, MP Strager Photogrammetric Engineering & Remote Sensing 82 (6), 437-447, 2016 | 62 | 2016 |
| Discriminating tree species at different taxonomic levels using multi-temporal WorldView-3 imagery in Washington DC, USA F Fang, BE McNeil, TA Warner, AE Maxwell, GA Dahle, E Eutsler, J Li Remote Sensing of Environment 246, 111811, 2020 | 49 | 2020 |
| Combining RapidEye satellite imagery and Lidar for mapping of mining and mine reclamation AE Maxwell, TA Warner, MP Strager, M Pal Photogrammetric Engineering & Remote Sensing 80 (2), 179-189, 2014 | 49 | 2014 |
| Thematic classification accuracy assessment with inherently uncertain boundaries: An argument for center-weighted accuracy assessment metrics AE Maxwell, TA Warner Remote Sensing 12 (12), 1905, 2020 | 47 | 2020 |
| Semantic segmentation deep learning for extracting surface mine extents from historic topographic maps AE Maxwell, MS Bester, LA Guillen, CA Ramezan, DJ Carpinello, Y Fan, ... Remote Sensing 12 (24), 4145, 2020 | 41 | 2020 |
| Scenario analysis predicts context-dependent stream response to landuse change in a heavily mined central Appalachian watershed ER Merriam, JT Petty, MP Strager, AE Maxwell, PF Ziemkiewicz Freshwater Science 32 (4), 1246-1259, 2013 | 41 | 2013 |
| Differentiating mine-reclaimed grasslands from spectrally similar land cover using terrain variables and object-based machine learning classification AE Maxwell, TA Warner International Journal of Remote Sensing 36 (17), 4384-4410, 2015 | 38 | 2015 |
| Multiscale analysis of hydrology in a mountaintop mine‐impacted watershed NP Zegre, AJ Miller, A Maxwell, SJ Lamont JAWRA Journal of the American Water Resources Association 50 (5), 1257-1272, 2014 | 38 | 2014 |
| Slope failure prediction using random forest machine learning and LiDAR in an eroded folded mountain belt AE Maxwell, M Sharma, JS Kite, KA Donaldson, JA Thompson, ML Bell, ... Remote Sensing 12 (3), 486, 2020 | 34 | 2020 |
| Land-surface parameters for spatial predictive mapping and modeling AE Maxwell, CM Shobe Earth-Science Reviews 226, 103944, 2022 | 32 | 2022 |
