Published December 25, 2025 | Version v1
Dataset Open

WHiCH (Western Himalaya Canopy Height) Map 2020, Pakistan

Authors/Creators

  • 1. ROR icon Taylor Geospatial Institute
  • 2. EDMO icon Washington University in St. Louis
  • 3. ROR icon University of the Punjab
  • 4. ROR icon Vrije Universiteit Amsterdam
  • 5. ROR icon National University of Sciences and Technology
  • 6. Multidomain Vision Research, LLC

Description

The western Himalayas region is a key biodiversity hotspot and a habitat for several species. This region needs an accurate spatial assessment of tree canopy height for improved estimates of aboveground biomass, carbon sequestration, and related forest ecosystem services. In this work, we used a deep convolution neural networks model, U-Net, for estimating canopy heights using Global Ecosystem Dynamics Investigation Mission (GEDI) with multi-band Sentinel-2 datasets. We produced a 10 m canopy height map of the study region for 2020. Overall, we achieved a Root Mean Square Error (RMSE) of 7.52 m and a Mean Absolute Error (MAE) of 5.71 m on test set, outperforming existing global canopy height models in this topographically challenging region.

Citation:

Use of these data require citation of this dataset:

Ahmad, A., Sastry, S., Dhakal, A., Khanal, S., Levering, A., Gilani, H., & Jacobs, N. (2025). WHiCH (Western Himalaya Canopy Height) Map 2020, Pakistan [Data set]. In International Journal of Applied Earth Observation and Geoinformation. Zenodo. https://doi.org/10.5281/zenodo.18056032

Original research article:

Ahmad, A., Sastry, S., Dhakal, A., Khanal, S., Levering, A., Gilani, H. & Jacobs, N. (2025). Canopy Height Mapping in the Western Himalayas, Pakistan: A Deep Learning Approach using GEDI and Sentinel-2 Fusion. International Journal of Applied Earth Observation and Geoinformation. doi.org/10.1016/j.jag.2025.105030

Files

WHiCH_Map_2020_preview.jpg

Files (1.4 GB)

Name Size Download all
md5:b413ea099031d5f02bf701e8394f11a8
550.5 kB Preview Download
md5:cddcc01d8e4a303d5e67da7d5bbd6aa7
1.4 GB Preview Download