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A hierarchical, multi‐sensor framework for peatland sub‐class and vegetation mapping throughout the Canadian boreal forest.
- Published in:
- Remote Sensing in Ecology & Conservation, 2024, v. 10, n. 4, p. 500, doi. 10.1002/rse2.384
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- Publication type:
- Article
Investigating the Use of Sentinel-1 for Improved Mapping of Small Peatland Water Bodies: Towards Wildfire Susceptibility Monitoring in Canada's Boreal Forest.
- Published in:
- Hydrology (2306-5338), 2023, v. 10, n. 5, p. 102, doi. 10.3390/hydrology10050102
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- Publication type:
- Article
Loss of the world's smallest forests.
- Published in:
- Global Change Biology, 2022, v. 28, n. 24, p. 7164, doi. 10.1111/gcb.16449
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- Publication type:
- Article
Mapping Arctic Lake Ice Backscatter Anomalies Using Sentinel-1 Time Series on Google Earth Engine.
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- Remote Sensing, 2021, v. 13, n. 9, p. 1626, doi. 10.3390/rs13091626
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- Publication type:
- Article
Spatio-Temporal Changes of Vegetation Net Primary Productivity and Its Driving Factors on the Qinghai-Tibetan Plateau from 2001 to 2017.
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- Remote Sensing, 2021, v. 13, n. 8, p. 1566, doi. 10.3390/rs13081566
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- Publication type:
- Article
Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule.
- Published in:
- Remote Sensing, 2021, v. 13, n. 8, p. 1424, doi. 10.3390/rs13081424
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- Publication type:
- Article
Interannual and Seasonal Variations of Hydrological Connectivity in a Large Shallow Wetland of North China Estimated from Landsat 8 Images.
- Published in:
- Remote Sensing, 2021, v. 13, n. 6, p. 1214, doi. 10.3390/rs13061214
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- Publication type:
- Article
Google Earth Engine Sentinel-3 OLCI Level-1 Dataset Deviates from the Original Data: Causes and Consequences.
- Published in:
- Remote Sensing, 2021, v. 13, n. 6, p. 1098, doi. 10.3390/rs13061098
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- Publication type:
- Article
Assessment of Annual Composite Images Obtained by Google Earth Engine for Urban Areas Mapping Using Random Forest.
- Published in:
- Remote Sensing, 2021, v. 13, n. 4, p. 748, doi. 10.3390/rs13040748
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- Publication type:
- Article
Machine Learning Classification of Mediterranean Forest Habitats in Google Earth Engine Based on Seasonal Sentinel-2 Time-Series and Input Image Composition Optimisation.
- Published in:
- Remote Sensing, 2021, v. 13, n. 4, p. 586, doi. 10.3390/rs13040586
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- Publication type:
- Article
Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series.
- Published in:
- Remote Sensing, 2020, v. 12, n. 15, p. 2465, doi. 10.3390/rs12152465
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- Publication type:
- Article
Remote Sensing of Boreal Wetlands 1: Data Use for Policy and Management.
- Published in:
- Remote Sensing, 2020, v. 12, n. 8, p. 1320, doi. 10.3390/rs12081320
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- Publication type:
- Article
Soil Moisture Monitoring in a Temperate Peatland Using Multi-Sensor Remote Sensing and Linear Mixed Effects.
- Published in:
- Remote Sensing, 2018, v. 10, n. 6, p. 903, doi. 10.3390/rs10060903
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- Publication type:
- Article
Contributions of Actual and Simulated Satellite SAR Data for Substrate Type Differentiation and Shoreline Mapping in the Canadian Arctic.
- Published in:
- Remote Sensing, 2017, v. 9, n. 12, p. 1206, doi. 10.3390/rs9121206
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- Publication type:
- Article
Moving to the RADARSAT Constellation Mission: Comparing Synthesized Compact Polarimetry and Dual Polarimetry Data with Fully Polarimetric RADARSAT-2 Data for Image Classification of Peatlands.
- Published in:
- Remote Sensing, 2017, v. 9, n. 6, p. 573, doi. 10.3390/rs9060573
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- Publication type:
- Article
Assessing the Potential to Operationalize Shoreline Sensitivity Mapping: Classifying Multiple Wide Fine Quadrature Polarized RADARSAT-2 and Landsat 5 Scenes with a Single Random Forest Model.
- Published in:
- Remote Sensing, 2015, v. 7, n. 10, p. 13528, doi. 10.3390/rs71013528
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- Publication type:
- Article
On the Importance of Training Data Sample Selection in Random Forest Image Classification: A Case Study in Peatland Ecosystem Mapping.
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- 2015
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- Publication type:
- Case Study
Detection of a low-relief 18th-century British siege trench using LiDAR vegetation penetration capabilities at Fort Beauséjour-Fort Cumberland National Historic Site, Canada.
- Published in:
- Geoarchaeology, 2009, v. 24, n. 5, p. 576, doi. 10.1002/gea.20281
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- Publication type:
- Article
A map of global peatland extent created using machine learning (Peat-ML).
- Published in:
- Geoscientific Model Development, 2022, v. 15, n. 12, p. 4709, doi. 10.5194/gmd-15-4709-2022
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- Publication type:
- Article
A map of global peatland extent created using machine learning (Peat-ML).
- Published in:
- Geoscientific Model Development Discussions, 2022, p. 1, doi. 10.5194/gmd-2021-426
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- Publication type:
- Article