Glacier-in-SETP

Glacier change monitoring for the Southeastern Tibetan Plateau by using aster stereo image and icesat-2 and satellite images.

1. data preparation

- 1.1 download aster stereo images on the website: https://search.earthdata.nasa.gov/search.

- 1.2 download icesat1 data by using scripts/icesat_download.sh,

- 1.3 download icesat2 data by using scripts/download_icesat2.py.

- 1.4 download tandem data from the website: https://download.geoservice.dlr.de/TDM90/

- 1.5 download srtm dem data by using scripts/get_srtm.sh. the srtm dem data is used as base map in our paper.

2. Icesat data processing (including both icesat-1 and icesat-2 data)

- 2.1 icesat data read out and subset to tiles.

• Step1: raw data read in and write out to the specific region data, by using scripts/readout.sh.
• Step2: subset data to tiles by using scrpits/h5files/tiles.sh. the processing including:
• 1. Search the .h5 files fall in the range of tiles.
• 2. Merge the searched .h5 files.
• 3. Subset the merged .h5 file to given tile.

- 2.2 obtain tiles-based elevation difference value.

• 1. The elevation difference is calculated by using srtm dem data.
• 2. The statistic of elevation difference (mean and std, et al.) for each tile of each year is obtianed.

3. Cyrosat-2 data processing

- 3.1 cryosat-2 tempo_points data read out and subset to tiles.

• Step1: raw data read in and write out to the specific region data, by using scripts/readout.sh.
• Step2: subset data to tiles by using scrpits/h5files/tiles.sh. the processing including:
• 1. Search the .h5 files fall in the range of tiles.
• 2. Merge the searched .h5 files.
• 3. Subset the merged .h5 file to given tile.

- 3.1 xxx

4. Aster stereo image-based dem processing

4.1 Aster dem generation by using script/aster_dem_batch.sh

4.2. post-processing for the aster dem data

4.3. aster dem coregistration with the srtm data.

4.4. calculate the dems difference map with with the srtm data.

5. data evaluation

5.1 Aster dem evaluation by using the notebooks/dem_evaluate_atl06.ipynb and notebooks/dem_evaluate_galh14.ipynb.

To do

1. mask out the data/cryotempo-points/2021/cryotempo_points_merge.h5 by using data/rgi60/rgi60_setp_mask.tif