Files
CA/Datas/landscan-hd-china-v1-assets/lshd_china_v1-0.ris
Akiba So bc73351234 chore: configure git-lfs and migrate data to LFS
- Add .gitattributes with LFS tracking for binary/data files
- Migrate processed parquet/npy/npz files from regular git to LFS
- Add Datas/ raw data via LFS (DEM, weather, air quality, maps)
- Add outputs/ GIS analysis and street matching results
- Enable cross-machine development with full data portability
2026-06-07 06:28:30 +08:00

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1.
TY - DATA
AU - Moehl, Jessica
AU - Reith, Andrew
AU - McKee, Jacob
AU - Weber, Eric
AU - Laverdiere, Melanie
AU - Swan, Benjamin
AU - Yang, Hsiuhan
AU - Hauser, Taylor
AU - Rose, Amy
AU - Walters, Sarah
AU - Roddy, Darrell
AU - Pyle, Joe
AU - O'Shell, Mary Ann
AU - Urban, Marie
PY - 2023
TI - LandScan HD China v1.0
CY - Oak Ridge, TN
PB - Oak Ridge National Laboratory
SE - August 11, 2023
T3 - LandScan HD
ET - v1.0
RI - China
C1 - CY 2023
C3 - raster digital data
AB - LandScan HD is developed for individual countries around the world and provides gridded population estimates at 3 arc-second resolution. The LandScan HD model incorporates current land use and infrastructure data from a variety of sources, applies facility occupancy estimates from ORNL's Population Density Tables (PDT) project, and leverages novel image processing algorithms developed at ORNL to rapidly map building structures and neighborhood areas using high-performance computing environments. In this way, LandScan HD is developed using a 'bottom-up' approach where high resolution population estimates are not dependent on a recently conducted, high quality census. This approach is particularly useful for parts of the world that regularly experience large changes in population distribution due to rapid growth, natural hazards, or conflict.
UR - https://landscan.ornl.gov
DO - https://doi.org/10.48690/1524248
ER -