GNDC-HiGLASS-LS20: Gap-free 20 m 5-Day LAI/FAPAR over China, 2018–2023
type: Dataset
creator: Jianbo Qi
  type: Agent
  type: person
description: # GNDC-HiGLASS-LS20 GNDC-compressed version of **HiGLASS-LS20** — the first gap-free, 20 m, 5-day LAI / FAPAR product over China (2018–2024), derived from integrated Landsat-8/9 and Sentinel-2 Analysis Ready Data. Files are stored as `.gndc` (a neural data cube format; see GeoNDC reference below) instead of GeoTIFF to reduce size. **A decoder is required to read them.** ## Decode ```bash pip install pygndc ``` Documentation: https://github.com/jianboqi/pygndc/blob/main/TUTORIAL.md ### Minimal example ```python import pygndc # Decode a .gndc file. The output is already in PHYSICAL values # (no scale factor needs to be applied). data = pygndc.read("HiGLASS_LS20_n018e108_2020_v01_LAI.gndc") print(data.shape) # (73, rows, cols) — 73 five-day composites print(data[0]) # first composite (DOY 001), LAI in m² m⁻² ``` > Note: after decoding, values are already physical (LAI in m² m⁻², > FAPAR unitless). Do **not** multiply by the scale factors below — those > apply only to the raw uint8 GeoTIFF source and are listed for reference. ## File naming ``` GNDC-HiGLASS_LS20_[lat][lon]_[year]_v01_LAI.gndc GNDC-HiGLASS_LS20_[lat][lon]_[year]_v01_FAPAR.gndc ``` - Tiles are 1° × 1° (WGS84 / EPSG:4326), centred at integer degree + 0.5° (e.g. `n018e108` = 18.5°N, 108.5°E, covering ~18–19°N, 108–109°E). - 73 bands per file = 5-day composites: DOY 001, 006, 011, …, 361 (Jan 1, Jan 6, …, Dec 22). ## Physical values & ranges | Variable | Range | Unit | |----------|-------|------| | LAI | 0 – 10.0 | m² m⁻² | | FAPAR | 0 – 1.0 | unitless | (For reference, the original uint8 GeoTIFF used scale factors LAI ×0.1 and FAPAR ×0.004. pygndc returns decoded data already in the physical ranges above.) ## Extend to other regions (2019–2024) Open-source pipeline (Google Colab): https://colab.research.google.com/drive/1zGYbUkh4COoZqpWA2tfMLZHVfsGZ1nAo ## Citation **For the GNDC compression format / decoder:** Qi, J., M. Li, B. Jiang, Y. Chen, and Q. Wang (2026). "GeoNDC: A Queryable Neural Data Cube for P…
issued: 2026-06-15T17:54:23.887000+00:00
modified: 2026-06-15T17:58:33.450000+00:00

HiGLASS_LS20_n036e117_2018-2023_v01_LAI-FPAR.gndc
type: Distribution
format: GNDC
issued: 2026-06-18T14:07:35.275159
modified: 2026-06-18T14:07:35.272136
access URL: https://data.source.coop/jianbo/gndc-higlass-ls20/HiGLASS_LS20_n036e117_2018-2023_v01_LAI-FPAR.gndc
byte size: 381132536

HiGLASS_LS20_n036e091_2018-2023_v01_LAI-FPAR.gndc
type: Distribution
format: GNDC
issued: 2026-06-18T14:07:35.275155
modified: 2026-06-18T14:07:35.272047
access URL: https://data.source.coop/jianbo/gndc-higlass-ls20/HiGLASS_LS20_n036e091_2018-2023_v01_LAI-FPAR.gndc
byte size: 13107200

HiGLASS_LS20_n034e106_2018-2023_v01_LAI-FPAR.gndc
type: Distribution
format: GNDC
issued: 2026-06-18T14:07:35.275147
modified: 2026-06-18T14:07:35.271932
access URL: https://data.source.coop/jianbo/gndc-higlass-ls20/HiGLASS_LS20_n034e106_2018-2023_v01_LAI-FPAR.gndc
byte size: 326675800

Source Cooperative
type: Agent