| Normalization method for multi-sensor high spatial and temporal resolution satellite imagery with radiometric inconsistencies N Leach, NC Coops, N Obrknezev Computers and Electronics in Agriculture 164, 104893, 2019 | 80 | 2019 |
| Towards frequent flood mapping with the Capella SAR system. The 2021 Eastern Australia floods case N Yague-Martinez, NR Leach, A Dasgupta, E Tellman, JS Brown 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 6174 …, 2021 | 16 | 2021 |
| LOESS radiometric correction for contiguous scenes (LORACCS): Improving the consistency of radiometry in high-resolution satellite image mosaics SA Wegmueller, NR Leach, PA Townsend International Journal of Applied Earth Observation and Geoinformation 97, 102290, 2021 | 15 | 2021 |
| Towards analysis ready data of optical CubeSat images: Demonstrating a hierarchical normalization framework at a wetland site Z Li, D Scheffler, NC Coops, N Leach, T Sachs International Journal of Applied Earth Observation and Geoinformation 103 …, 2021 | 6 | 2021 |
| Leveraging convolutional neural networks for semantic segmentation of global floods with PlanetScope imagery NR Leach, P Popien, MC Goodman, B Tellman IGARSS 2022-2022 IEEE international geoscience and remote sensing symposium …, 2022 | 3 | 2022 |
| Memory to map: Improving radar flood maps with temporal context and semantic segmentation V Sunkara, N Leach, S Ganju AGU Fall Meeting Abstracts 2021, NH35F, 2021 | 3 | 2021 |
| Rapid inundation mapping using the US National Water Model, satellite observations, and a convolutional neural network JM Frame, T Nair, V Sunkara, P Popien, S Chakrabarti, T Anderson, ... Geophysical Research Letters 51 (17), e2024GL109424, 2024 | 1 | 2024 |
| Cost-effective global flood segmentation using convolutional neural networks, sentinel-1 and active learning P Popien, V Sunkara, N Leach, B Tellman AGU Fall Meeting Abstracts 2021, H51A-04, 2021 | 1 | 2021 |
| Processing and applying multisensor CubeSat data to map forest fire timing and patterns NR Leach University of British Columbia, 2020 | 1 | 2020 |
| Improving Digital Representations of Inundation with Deep Learning: from satellite data fusion in Bangladesh to the National Water Model-Satellite fusion in CONUS B Tellman, J Giezendanner, A Saunders, A Islam, AS Islam, S Chakrabarti, ... AGU23, 2024 | | 2024 |
| Daily Flood Mapping Using U-Nets for MODIS and VIIRS N Leach, V Sunkara, P Popien, C Doyle AGU Fall Meeting Abstracts 2022, H46D-04, 2022 | | 2022 |
| A Remote Sensing Approach to Bridging the Gaps in FEMA Flood Risk Maps A Lawal, B Tellman, JM Frame, N Leach, T Nair, T Anderson, V Sunkara AGU Fall Meeting Abstracts 2022, NH35C-0504, 2022 | | 2022 |
| Medium Resolution Data and Deep Learning Unlock Parametric Flood Insurance C Doyle, MC Goodman, B Tellman, N Leach, P Popien, V Sunkara, ... AGU Fall Meeting Abstracts 2022, GC15G-0533, 2022 | | 2022 |
| Demonstrating the Generation and Application of Analysis Ready Data of Optical CubeSat Images at a Rewetted Peatland Site Z Li, D Spengler, NC Coops, N Leach, M Weituschat, A Kalhori, C Wille, ... Living Planet Symposium, 2022 | | 2022 |
| 45 years of sub-daily inundation mapping with deep learning merging the US National Water Model, satellite observations, and USGS stream gauges across CONUS B Tellman, P Popien, T Nair, JM Frame, S Chakrabarti, C Doyle, N Leach, ... AGU24, 0 | | |
| Observations and Geoinformation SA Wegmueller, NR Leach, PA Townsend | | |
Nicholas C CoopsCanada Chair of Remote Sensing在 ubc.ca 的电子邮件经过验证
Nicholas C CoopsCanada Chair of Remote Sensing在 ubc.ca 的电子邮件经过验证