Annual sub-pixel Landsat surface water maps of the Hudson Bay Lowlands from 1985-2021

Annual sub-pixel Landsat surface water maps of the Hudson Bay Lowlands from 1985-2021 The Hudson Bay Lowlands (HBL) is the wettest ecozone in Canada with 80% of its area covered by wetlands. It forms the third largest wetland in the world and is composed almost entirely of permafrost and non-frozen subarctic peatlands that store more carbon in the first 2 m of soil than the total carbon stored in any other ecozone in Canada. The HBL is also home to large mammals including polar bears, caribou, moose, and provides important breeding habitat for migratory birds. Surface water dynamics in the HBL are both a consequence and a driver of climate change, impacting evapotranspiration, permafrost thaw and carbon budgets under wetting / drying conditions as well as wildlife habitat. Previously, dynamic surface water products were generated from historical Landsat data to inform surface water trends in the HBL based on binary classifications of land versus water at 30 m spatial resolution (Olthof and Rainville, 2022). However, the HBL contains many water features smaller than 30 m, including streams and patterned fens that require a sub-pixel mapping approach to depict these small features as the percent water fraction within each pixel footprint. The annual surface water products in this dataset were created by leveraging an existing binary dynamic surface water product (Olthof and Rainville, 2022) to implement adaptive physical linear spectral unmixing models. The result is a spatially and temporally comprehensive Landsat sub-30m surface water time-series over the HBL from 1985 to 2021 that can be used to help researchers and policymakers address issues around climate change and wildlife. Following the Government of Canada Open Data initiative, these original dynamic surface water maps are available to the public. More information on the creation of this dataset can be found in the associated research paper at https://www.sciencedirect.com/science/article/pii/S0034425723004467?ref=pdf_download&fr=RR-2&rr=84402791cff87154. 2024-04-11 Environment and Climate Change Canada enviroinfo@ec.gc.ca Nature and EnvironmentSurface waterRemote sensingGeographical mapsClimate changeEnvironmentInland watersHabitatswaterremote sensingwater masksLandsatimagerymappingdataHudson Bay LowlandsOntarioManitobaJames Bay Annual Hudson Bay Lowlands Surface Water Masks 1985 - 2021 DataTIFF https://data-donnees.az.ec.gc.ca/data/water/scientificknowledge/annual-hudson-bay-lowland-surface-water-masks-1985-2021-data/?lang=en Annual Hudson Bay Lowlands Surface Water Masks 1985 - 2021 DataTIFF https://data-donnees.az.ec.gc.ca/data/water/scientificknowledge/annual-hudson-bay-lowland-surface-water-masks-1985-2021-data/?lang=fr

The Hudson Bay Lowlands (HBL) is the wettest ecozone in Canada with 80% of its area covered by wetlands. It forms the third largest wetland in the world and is composed almost entirely of permafrost and non-frozen subarctic peatlands that store more carbon in the first 2 m of soil than the total carbon stored in any other ecozone in Canada. The HBL is also home to large mammals including polar bears, caribou, moose, and provides important breeding habitat for migratory birds. Surface water dynamics in the HBL are both a consequence and a driver of climate change, impacting evapotranspiration, permafrost thaw and carbon budgets under wetting / drying conditions as well as wildlife habitat.

Previously, dynamic surface water products were generated from historical Landsat data to inform surface water trends in the HBL based on binary classifications of land versus water at 30 m spatial resolution (Olthof and Rainville, 2022). However, the HBL contains many water features smaller than 30 m, including streams and patterned fens that require a sub-pixel mapping approach to depict these small features as the percent water fraction within each pixel footprint.

The annual surface water products in this dataset were created by leveraging an existing binary dynamic surface water product (Olthof and Rainville, 2022) to implement adaptive physical linear spectral unmixing models. The result is a spatially and temporally comprehensive Landsat sub-30m surface water time-series over the HBL from 1985 to 2021 that can be used to help researchers and policymakers address issues around climate change and wildlife.

Following the Government of Canada Open Data initiative, these original dynamic surface water maps are available to the public. More information on the creation of this dataset can be found in the associated research paper at https://www.sciencedirect.com/science/article/pii/S0034425723004467?ref=pdf_download&fr=RR-2&rr=84402791cff87154.

Data and Resources

Similar records