Brian Brisco
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View article: Multi-decadal floodplain classification and trend analysis in the Upper Columbia River valley, British Columbia
Multi-decadal floodplain classification and trend analysis in the Upper Columbia River valley, British Columbia Open
Floodplain wetland ecosystems experience significant seasonal water fluctuation over the year, resulting in a dynamic hydroperiod, with a range of vegetation community responses. This paper assesses trends and changes in land cover and hyd…
View article: Comment on hess-2023-211
Comment on hess-2023-211 Open
Abstract. Floodplain wetland ecosystems experience significant seasonal water fluctuation over the year, resulting in a dynamic hydroperiod, with a range of vegetation community responses. This paper assesses trends and changes in landcove…
View article: Comment on hess-2023-211
Comment on hess-2023-211 Open
Abstract. Floodplain wetland ecosystems experience significant seasonal water fluctuation over the year, resulting in a dynamic hydroperiod, with a range of vegetation community responses. This paper assesses trends and changes in landcove…
View article: Leveraging google earth engine cloud computing for large-scale arctic wetland mapping
Leveraging google earth engine cloud computing for large-scale arctic wetland mapping Open
Climate-driven permafrost degradation and an intensification of the hydrological cycle are rapidly altering the intricate ecohydrological processes of Arctic wetlands, threatening their long-term carbon sequestration capabilities. Addressi…
View article: Supplementary material to "Multi-decadal Floodplain Classification and Trend Analysis in the Upper Columbia River Valley, British Columbia"
Supplementary material to "Multi-decadal Floodplain Classification and Trend Analysis in the Upper Columbia River Valley, British Columbia" Open
The followings are detailed descriptions of wetland-related datasets.(i) The Historical Global Land Cover (created by the Hermosilla et al., 2022) is a high spatial resolution (30m) land cover maps for Canada's ecosystems (Overall accuracy…
View article: Multi-decadal Floodplain Classification and Trend Analysis in the Upper Columbia River Valley, British Columbia
Multi-decadal Floodplain Classification and Trend Analysis in the Upper Columbia River Valley, British Columbia Open
Floodplain wetland ecosystems experience significant seasonal water fluctuation over the year, resulting in a dynamic hydroperiod, with a range of vegetation community responses. This paper assesses trends and changes in landcover and hydr…
View article: Dual-Branch Fusion of Convolutional Neural Network and Graph Convolutional Network for PolSAR Image Classification
Dual-Branch Fusion of Convolutional Neural Network and Graph Convolutional Network for PolSAR Image Classification Open
Polarimetric synthetic aperture radar (PolSAR) images contain useful information, which can lead to extensive land cover interpretation and a variety of output products. In contrast to optical imagery, there are several challenges in extra…
View article: Remote Sensing and Machine Learning Tools to Support Wetland Monitoring: A Meta-Analysis of Three Decades of Research
Remote Sensing and Machine Learning Tools to Support Wetland Monitoring: A Meta-Analysis of Three Decades of Research Open
Despite their importance to ecosystem services, wetlands are threatened by pollution and development. Over the last few decades, a growing number of wetland studies employed remote sensing (RS) to scientifically monitor the status of wetla…
View article: Correction: Moghimi et al. Automatic Relative Radiometric Normalization of Bi-Temporal Satellite Images Using a Coarse-to-Fine Pseudo-Invariant Features Selection and Fuzzy Integral Fusion Strategies. Remote Sens. 2022, 14, 1777
Correction: Moghimi et al. Automatic Relative Radiometric Normalization of Bi-Temporal Satellite Images Using a Coarse-to-Fine Pseudo-Invariant Features Selection and Fuzzy Integral Fusion Strategies. Remote Sens. 2022, 14, 1777 Open
There was an error in the original publication [...]
View article: 3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer
3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer Open
Many ecosystems, particularly wetlands, are significantly degraded or lost as a result of climate change and anthropogenic activities. Simultaneously, developments in machine learning, particularly deep learning methods, have greatly impro…
View article: Forty Years of Wetland Status and Trends Analyses in the Great Lakes Using Landsat Archive Imagery and Google Earth Engine
Forty Years of Wetland Status and Trends Analyses in the Great Lakes Using Landsat Archive Imagery and Google Earth Engine Open
Wetlands provide many benefits, such as water storage, flood control, transformation and retention of chemicals, and habitat for many species of plants and animals. The ongoing degradation of wetlands in the Great Lakes basin has been caus…
View article: Wetland Hydroperiod Analysis in Alberta Using InSAR Coherence Data
Wetland Hydroperiod Analysis in Alberta Using InSAR Coherence Data Open
Wetlands are dynamic environments, the water and vegetation of which can change considerably over time. Thus, it is important to investigate the hydroperiod status of wetlands using advanced techniques such as remote sensing technology. We…
View article: Creating a Detailed Wetland Inventory with Sentinel-2 Time-Series Data and Google Earth Engine in the Prairie Pothole Region of Canada
Creating a Detailed Wetland Inventory with Sentinel-2 Time-Series Data and Google Earth Engine in the Prairie Pothole Region of Canada Open
Wetlands in the Prairie Pothole Region (PPR) of Canada and the United States represent a unique mapping challenge. They are dynamic both seasonally and year-to-year, are very small, and frequently altered by human activity. Many efforts ha…
View article: Automatic Relative Radiometric Normalization of Bi-Temporal Satellite Images Using a Coarse-to-Fine Pseudo-Invariant Features Selection and Fuzzy Integral Fusion Strategies
Automatic Relative Radiometric Normalization of Bi-Temporal Satellite Images Using a Coarse-to-Fine Pseudo-Invariant Features Selection and Fuzzy Integral Fusion Strategies Open
Relative radiometric normalization (RRN) is important for pre-processing and analyzing multitemporal remote sensing (RS) images. Multitemporal RS images usually include different land use/land cover (LULC) types; therefore, considering an …
View article: Applying Machine Learning and Time-Series Analysis on Sentinel-1A SAR/InSAR for Characterizing Arctic Tundra Hydro-Ecological Conditions
Applying Machine Learning and Time-Series Analysis on Sentinel-1A SAR/InSAR for Characterizing Arctic Tundra Hydro-Ecological Conditions Open
Synthetic aperture radar (SAR) is a widely used tool for Earth observation activities. It is particularly effective during times of persistent cloud cover, low light conditions, or where in situ measurements are challenging. The intensity …
View article: Status and Trends of Wetland Studies in Canada Using Remote Sensing Technology with a Focus on Wetland Classification: A Bibliographic Analysis
Status and Trends of Wetland Studies in Canada Using Remote Sensing Technology with a Focus on Wetland Classification: A Bibliographic Analysis Open
A large portion of Canada is covered by wetlands; mapping and monitoring them isof great importance for various applications. In this regard, Remote Sensing (RS) technology hasbeen widely employed for wetland studies in Canada over the pas…
View article: The RADARSAT Constellation Mission Core Applications: First Results
The RADARSAT Constellation Mission Core Applications: First Results Open
The Canadian RADARSAT Constellation Mission (RCM) has passed its early operation phase with the performance evaluation being currently active. This evaluation aims to confirm that the innovative design of the mission’s synthetic aperture r…
View article: 3-D Hybrid CNN Combined With 3-D Generative Adversarial Network for Wetland Classification With Limited Training Data
3-D Hybrid CNN Combined With 3-D Generative Adversarial Network for Wetland Classification With Limited Training Data Open
Recently, deep learning algorithms, specifically convolutional neural networks (CNNs), have played an important role in remote sensing image classification, including wetland mapping. However, one limitation of deep CNN for classification …
View article: A Synergic Use of Sentinel-1 and Sentinel-2 Imagery for Complex Wetland Classification Using Generative Adversarial Network (GAN) Scheme
A Synergic Use of Sentinel-1 and Sentinel-2 Imagery for Complex Wetland Classification Using Generative Adversarial Network (GAN) Scheme Open
Due to anthropogenic activities and climate change, many natural ecosystems, especially wetlands, are lost or changing at a rapid pace. For the last decade, there has been increasing attention towards developing new tools and methods for t…
View article: Status and Trends of Wetland Studies in Canada Using Remote Sensing Technology with a Focus on Wetland Classification: A Bibliographic Analysis
Status and Trends of Wetland Studies in Canada Using Remote Sensing Technology with a Focus on Wetland Classification: A Bibliographic Analysis Open
A large portion of Canada is covered by wetlands; mapping and monitoring them is of great importance for various applications. In this regard, Remote Sensing (RS) technology has been widely employed for wetland studies in Canada over the p…
View article: Remote Sensing of Wetlands in the Prairie Pothole Region of North America
Remote Sensing of Wetlands in the Prairie Pothole Region of North America Open
The Prairie Pothole Region (PPR) of North America is an extremely important habitat for a diverse range of wetland ecosystems that provide a wealth of socio-economic value. This paper describes the ecological characteristics and importance…
View article: Modelling, Characterizing, and Monitoring Boreal Forest Wetland Bird Habitat with RADARSAT-2 and Landsat-8 Data
Modelling, Characterizing, and Monitoring Boreal Forest Wetland Bird Habitat with RADARSAT-2 and Landsat-8 Data Open
Earth observation technologies have strong potential to help map and monitor wildlife habitats. Yellow Rail, a rare wetland obligate bird species, is a species of concern in Canada and provides an interesting case study for monitoring wetl…
View article: InSAR Coherence Analysis for Wetlands in Alberta, Canada Using Time-Series Sentinel-1 Data
InSAR Coherence Analysis for Wetlands in Alberta, Canada Using Time-Series Sentinel-1 Data Open
Wetlands are valuable natural resources which provide numerous services to the environment. Many studies have demonstrated the potential of various types of remote sensing datasets and techniques for wetland mapping and change analysis. Ho…
View article: Response of Multi-Incidence Angle Polarimetric RADARSAT-2 Data to Herbaceous Vegetation Features in the Lower Paraná River Floodplain, Argentina
Response of Multi-Incidence Angle Polarimetric RADARSAT-2 Data to Herbaceous Vegetation Features in the Lower Paraná River Floodplain, Argentina Open
Wetland ecosystems play a key role in hydrological and biogeochemical cycles. In emergent vegetation targets, the occurrence of double-bounce scatter is indicative of the presence of water and can be valuable for hydrological monitoring. D…
View article: Seasonal Surface Subsidence and Frost Heave Detected by C-Band DInSAR in a High Arctic Environment, Cape Bounty, Melville Island, Nunavut, Canada
Seasonal Surface Subsidence and Frost Heave Detected by C-Band DInSAR in a High Arctic Environment, Cape Bounty, Melville Island, Nunavut, Canada Open
Differential interferometry of synthetic aperture radar (DInSAR) can be used to generate high-precision surface displacement maps in continuous permafrost environments, capturing isotropic surface subsidence and uplift associated with the …
View article: Comparing Solo Versus Ensemble Convolutional Neural Networks for Wetland Classification Using Multi-Spectral Satellite Imagery
Comparing Solo Versus Ensemble Convolutional Neural Networks for Wetland Classification Using Multi-Spectral Satellite Imagery Open
Wetlands are important ecosystems that are linked to climate change mitigation. As 25% of global wetlands are located in Canada, accurate and up-to-date wetland classification is of high importance, nationally and internationally. The adve…
View article: Number and nest-site selection of breeding black-necked cranes over the past 40 years in the Longbao Wetland Nature Reserve, Qinghai, China
Number and nest-site selection of breeding black-necked cranes over the past 40 years in the Longbao Wetland Nature Reserve, Qinghai, China Open
Black-necked crane (Grus nigricollis, BNC), facing serious threats from human activities and habitat variations, is an endangered species classified as vulnerable under the revised IUCN Red List. In this article, we investigated and analyz…
View article: Number and Nest-Site Selection of Breeding Black-Necked Cranes Over the Past 40 Years in the Longbao Wetland Nature Reserve, Qinghai, China
Number and Nest-Site Selection of Breeding Black-Necked Cranes Over the Past 40 Years in the Longbao Wetland Nature Reserve, Qinghai, China Open
Black-necked crane ( Grus nigricollis , BNC) is an endangered species classified as vulnerable under the revised IUCN Red List, and it faces serious threats from human activities and habitat variations. We investigated and analyzed the pop…
View article: Multi-Source EO for Dynamic Wetland Mapping and Monitoring in the Great Lakes Basin
Multi-Source EO for Dynamic Wetland Mapping and Monitoring in the Great Lakes Basin Open
Wetland managers, citizens and government leaders are observing rapid changes in coastal wetlands and associated habitats around the Great Lakes Basin due to human activity and climate variability. SAR and optical satellite sensors offer c…