Multi-Temporal Crop Classification with HLS Imagery across CONUS

This dataset contains temporal Harmonized Landsat-Sentinel (HLS) imagery of diverse crop type and land cover classes across the Contiguous United States (CONUS) for the year 2022. The target labels are derived from USDA's Crop Data Layer (CDL). It's primary purpose is for training segmentation geospatial machine learning models. It includes 3,854 chips of 224 x 224 pixel area at 30m spatial resolution.

Data and Resources

Additional Info

Field Value
ID
GCS Poster
Filebin Poster
Version
Is live dataset
License https://creativecommons.org/licenses/by-sa/4.0/
Structured data license
Date created
Date published August 10, 2023
Date modified August 21, 2025
Languages
Same as
  1. https://source.coop//clarkcga/multi-temporal-crop-classification
Cite as
Creators
Creator 1
Type
Organization
ID
clarkcga
Identifier
Name
Clark Center for Geospatial Analytics
Email
URL
https://source.coop/clarkcga
Publishers
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