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Full catalog/Ecosystem_Map_SRD_PAD_1947
Ecosystem_Map_SRD_PAD_1947·v1·dataset

Wetland types in Canadian river deltas (2007 and 2017)

ABoVE: Wetland Type, Slave River and Peace-Athabasca Deltas, Canada, 2007 and 2017
biosphere NASA ORNL_CLOUD Level 3 multiple
In plain English

What it measures. Maps of wetland and ecosystem types across two large Canadian river deltas for around 2007 and around 2017, using an 18-category scheme covering wetlands, peatlands, and dry uplands at fine (12.5 m) detail.

How it's made. Created by a machine-learning classifier trained on multi-season optical and radar satellite images (from Landsat, ERS, ALOS, Sentinel-1 and others), field data, and terrain measures.

How & where you'd use it. Lets researchers compare how wetland landscapes changed over a decade and study the deltas' ecology and hydrology.

What's measured

BIOSPHERE › ECOSYSTEMS › TERRESTRIAL ECOSYSTEMS › WETLANDSLAND SURFACE › LAND USE/LAND COVER › LAND USE/LAND COVER CLASSIFICATION

Coverage & cadence

  • Time span2006-06-14 → 2019-05-28
  • Measured byALOS-2 (PALSAR-2) · LANDSAT-5 (IMAGING RADIOMETERS) · LANDSAT-8 (IMAGING RADIOMETERS) · Sentinel-1A (IMAGING RADIOMETERS) · ERS-2 (IMAGING RADIOMETERS) · ALOS (PALSAR)
  • Processing levelLevel 3
  • Spatial extent-115.291, 57.7746, -109.643, 61.7919
  • Formatsmultiple
  • StatusCOMPLETE

What you can do with it

  • Map vegetation, forests and biomass
  • Monitor ecosystem productivity and carbon
  • Support habitat and biodiversity studies
Official description

This dataset provides ecosystem-types for the Slave River Delta (SRD) and Peace-Athabasca Delta (PAD), Canada, for the time periods circa 2007 and circa 2017. The image resolution is 12.5 m with 0.2-hectare minimum mapping unit. Included are an 18-class modified Enhanced Wetland Classification (EWC) scheme for wetland, peatland, and upland areas. Classes were derived from a Random Forest classification trained on multi-seasonal moderate-resolution images and synthetic aperture radar (SAR) imagery sourced from aerial and satellite sensors, field data, and calculated indices. Indices included Height Above Nearest Drainage (HAND) and Topographic Position Index (TPI), both derived from a digital elevation model, to differentiate between land cover types. The c. 2007 remote sensing data were comprised of early and late growing season Landsat-5, ERS2, L-Band PALSAR from 2006 to 2010 and growing season Landsat thermal composites. The c. 2017 remote sensing data were comprised of early and late growing season Landsat-8 and L-Band PALSAR-2 from 2017 to 2019, Sentinel-1 June VV and VH mean and standard deviations, and growing season Landsat thermal composites. Elevation indices from multi-resolution TPI and HAND were created from the Japan Aerospace Exploration Agency Advanced Land Observing Satellite 30 m Global Spatial Data Model. Also included are the images used for classification and the classification error matrices for each map and time period. Data are provided in GeoTIFF and GeoPackage file formats.

Get the data

ecosystem_map_srd_pad_1947_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="Ecosystem_Map_SRD_PAD_1947",
    version="1",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from ORNL_CLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.