# Source: Multi-Temporal Cloud Gap Imputation With HLS Imagery Across CONUS
# Type: http
# Catalog: SourceCoopConnector
# Generated by: folia catalog import
# Generated at: 2026-02-09T06:07:32.202370+00:00
#
# Do not edit manually - will be overwritten on next import.

source:
  id: source-coop-clarkcga-hls-multi-temporal-cloud-gap-imputation
  name: Multi-Temporal Cloud Gap Imputation With HLS Imagery Across CONUS
  type: http
  url: https://source.coop/clarkcga/hls-multi-temporal-cloud-gap-imputation
  description: This dataset contains temporal Harmonized Landsat-Sentinel imagery
    of diverse land covers across the Contiguous United States for the year 2022 along
    with binary cloud masks for the same area and year. This dataset's primary purpose
    is to train machine learning models for cloud gap imputation. The dataset contains
    7,852 224x224x18 HLS scenes and 21,642 binary cloud masks of size 224x224.
  provider: Clark Center for Geospatial Analytics
  metadata:
    source_coop: true
    source_coop_account: clarkcga
    source_coop_repository: hls-multi-temporal-cloud-gap-imputation
    connector_id: source-coop
    bbox:
    - -180.0
    - -90.0
    - 180.0
    - 90.0
    tags:
    - hls
    - multitemporal
    - cloud
    - imputation
    dataset:
      tier: 1
      thematic_group: Land Cover & Land Use
      format: unknown
      crs: EPSG:4326
      quality:
        coverage: unknown
      cloud_native_uri: https://data.source.coop/clarkcga/hls-multi-temporal-cloud-gap-imputation
      homepage: https://source.coop/clarkcga/hls-multi-temporal-cloud-gap-imputation