Remotely sensed snow status analyzed for the paper titled "Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions"

This comma-delimited dataset provides values for the remotely sensed status of snow on/off analyzed for field study sites described in the paper, "Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions," by Sadinski et al. (submitted). These data provide an indication of snow presence at the spatial resolution of a 500-m square cell for each eight-day interval beginning in January and ending at the start July of each year from 2008-2012. The source for the data was the MOD10A2 snow product from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor. We extracted data for the cells associated with 35 field study sites for which we subsequently determined the timing of spring snow-free conditions. The data field labeled "BlockSite" links these values geospatially to a data field of the same name in an ESRI shapefile titled "Study_Block_Boundaries.shp" that delineates study blocks containing the field sites. Refer to the paper by Sadinski et al. (submitted) for details of the analyses performed.

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_@id https://ddi.doi.gov/usgs-data.json
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier http://datainventory.doi.gov/id/dataset/usgs-5ffca65ed34e52c3b3d9d91e
metadata_type geospatial
modified 2022-06-23T00:00:00Z
old-spatial -95.680000000002, 42.95, -89.54, 47.1
publisher U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash e19123923ce0b09ba9f21b9dc0b0ecabe87301b2c61a4b04608ca8e3391b9f39
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-95.680000000002, 42.95], [-95.680000000002, 47.1], [ -89.54, 47.1], [ -89.54, 42.95], [-95.680000000002, 42.95]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • land-surface
  • minnesota
  • snow
  • terrestrial-hydrosphere
  • usgs-5ffca65ed34e52c3b3d9d91e
  • wisconsin
isopen False
license_id notspecified
license_title License not specified
maintainer Alisa L Gallant
maintainer_email gallant@usgs.gov
metadata_created 2025-09-23T16:08:55.496880
metadata_modified 2025-09-23T16:08:55.496886
notes This comma-delimited dataset provides values for the remotely sensed status of snow on/off analyzed for field study sites described in the paper, "Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions," by Sadinski et al. (submitted). These data provide an indication of snow presence at the spatial resolution of a 500-m square cell for each eight-day interval beginning in January and ending at the start July of each year from 2008-2012. The source for the data was the MOD10A2 snow product from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor. We extracted data for the cells associated with 35 field study sites for which we subsequently determined the timing of spring snow-free conditions. The data field labeled "BlockSite" links these values geospatially to a data field of the same name in an ESRI shapefile titled "Study_Block_Boundaries.shp" that delineates study blocks containing the field sites. Refer to the paper by Sadinski et al. (submitted) for details of the analyses performed.
num_resources 2
num_tags 14
title Remotely sensed snow status analyzed for the paper titled "Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions"