Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry AS Woodget, PE Carbonneau, F Visser, IP Maddock Earth surface processes and landforms 40 (1), 47-64, 2015 | 455 | 2015 |
Drones and digital photogrammetry: from classifications to continuums for monitoring river habitat and hydromorphology AS Woodget, R Austrums, IP Maddock, E Habit Wiley Interdisciplinary Reviews: Water 4 (4), e1222, 2017 | 172 | 2017 |
Subaerial gravel size measurement using topographic data derived from a UAV‐SfM approach AS Woodget, R Austrums Earth Surface Processes and Landforms 42 (9), 1434-1443, 2017 | 108 | 2017 |
Adopting deep learning methods for airborne RGB fluvial scene classification PE Carbonneau, SJ Dugdale, TP Breckon, JT Dietrich, MA Fonstad, ... Remote Sensing of Environment 251, 112107, 2020 | 80 | 2020 |
From manned to unmanned aircraft: Adapting airborne particle size mapping methodologies to the characteristics of sUAS and SfM AS Woodget, C Fyffe, PE Carbonneau Earth Surface Processes and Landforms 43 (4), 857-870, 2018 | 63 | 2018 |
Processes at the margins of supraglacial debris cover: quantifying dirty ice ablation and debris redistribution C. Fyffe, A.S. Woodget et al. Earth Surface Processes and Landforms, 2020 | 44 | 2020 |
The accuracy and reliability of traditional surface flow type mapping: Is it time for a new method of characterizing physical river habitat? AS Woodget, F Visser, IP Maddock, PE Carbonneau River Research and Applications 32 (9), 1902-1914, 2016 | 40 | 2016 |
Quantifying below-water fluvial geomorphic change: The implications of refraction correction, water surface elevations, and spatially variable error AS Woodget, JT Dietrich, RT Wilson Remote Sensing 11 (20), 2415, 2019 | 31 | 2019 |
Unmanned Aerial Systems (UAS) for environmental applications special issue preface A Simic Milas, JJ Sousa, TA Warner, AC Teodoro, E Peres, JA Gonçalves, ... International Journal of Remote Sensing 39 (15-16), 4845-4851, 2018 | 28 | 2018 |
An evaluation of a low-cost pole aerial photography (PAP) and structure from motion (SfM) approach for topographic surveying of small rivers F Visser, A Woodget, A Skellern, J Forsey, J Warburton, R Johnson International Journal of Remote Sensing 40 (24), 9321-9351, 2019 | 20 | 2019 |
Quantifying physical river habitat parametres using hyperspatial resolution UAS imagery and SfM-photogrammetry A Woodget University of Worcester, 2015 | 13* | 2015 |
An assessment of airborne lidar for forest growth studies AS Woodget, DNM Donoghue, P Carbonneau Ekscentar, 47-52, 2007 | 11 | 2007 |
Quantifying fluvial substrate size using hyperspatial resolution UAS imagery and SfM-photogrammetry AS Woodget, F Visser, IP Maddock, P Carbonneau, R Austrums Extended Abstract, 11th International Symposium on Ecohydraulics, 2016 | 10 | 2016 |
Climate change impact on cliff instability and erosion R Moore, J Rogers, A Woodget, A Baptiste Environment Agency Annual Conference, 2010 | 8 | 2010 |
Climate change impact on cliff instability and erosion in the UK. FCRM> 10 R Moore, J Rogers, A Woodget, A Baptiste Proceedings of the Environment Agency Conference of River and Coastal …, 2010 | 7 | 2010 |
Spatial validation of submerged fluvial topographic models by mesohabitat units CA Puig-Mengual, AS Woodget, R Muñoz-Mas, F Martínez-Capel International Journal of Remote Sensing 42 (7), 2391-2416, 2021 | 6 | 2021 |
Generalised classification of hyperspatial resolution airborne imagery of fluvial scenes with deep convolutional neural networks. P Carbonneau, T Breckon, J Dietrich, S Dugdale, M Fonstad, H Miyamoto, ... Geophysical Research Abstracts 21, 2019 | 4 | 2019 |
Living England: Satellite-based habitat classification- Technical User Guide (NERR108) A Kilcoyne, M Clement, C Moore, G Picton Phillipps, R Keane, A Woodget, ... file:///C:/Users/m1003216/Downloads/Edition%201%20NERR108%20Living%20England …, 2022 | 3* | 2022 |
Unmanned aerial vehicles for riverine environments MR Casado, A Woodget, RB Gonzalez, I Maddock, P Leinster Unmanned aerial remote sensing, 55-75, 2020 | 3 | 2020 |
Quantifying Fluvial Topography Using UAS Imagery and SfM-Photogrammetry. A Woodget, P Carbonneau, F Visser, I Maddock, E Habit | 3 | 2014 |