Time Series Downloader (TSD)

Automatic download of Sentinel, Landsat and Planet crops.

Carlo de Franchis, CMLA, ENS Cachan, Université Paris-Saclay, 2016-19

With contributions from Enric Meinhardt-Llopis, Axel Davy and Tristan Dagobert.

The main source code repository for this software is https://github.com/cmla/tsd.

Installation

tsd is easily installed from sources with pip:

git clone https://github.com/cmla/tsd
cd tsd
pip install -e .

Alternatively, tsd latest release can also be installed from PyPI:

pip install tsd

Usage

Search and download is performed by get_sentinel2.py, get_landsat.py, get_planet.py and get_sentinel1.py (one file per satellite constellation). They can be used both as command line scripts or as Python modules.

They use the Python modules search_stac.py, search_scihub.py, search_peps.py and search_planet.py (one file per API provider).

From the command line

TSD can be used from the command line through the Python scripts get_*.py. For instance, to download and process Sentinel-2 images of the Jamnagar refinery, located at latitude 22.34806 and longitude 69.86889, run

python get_sentinel2.py --lat 22.34806 --lon 69.86889 -b B02 B03 B04 -o test

This downloads crops of size 5000 x 5000 meters from the bands 2, 3 and 4, corresponding to the blue, green and red channels, and stores them in geotif files in the test directory.

It should print something like this on stdout (the number of images might vary):

Found 22 images
Elapsed time: 0:00:02.301129

Downloading 66 crops (22 images with 3 bands)... 66 / 66
Elapsed time: 0:00:57.620805

Reading 22 cloud masks... 22 / 22
6 cloudy images out of 22
Elapsed time: 0:00:15.066992

Images with more than half of the pixels covered by clouds (according to the cloud polygons available in Sentinel-2 images metadata, or Landsat-8 images quality bands) are moved in the test/cloudy subfolder.

To specify the desired bands, use the -b or --band flag. The crop size can be changed with the --width and --height flags. For instance

python get_sentinel2.py --lat 22.34806 --lon 69.86889 -b B11 B12 --width 8000 --height 6000

downloads crops of size 8000 x 6000 meters, only for the SWIR channels (bands 11 and 12).

All the available options are listed with the -h or --help flag:

python get_sentinel2.py -h

You can also run any of the search_*.py scripts from the command line separately. Run them with -h to get the list of available options. For a nice output formatting, pipe their output to jq (brew install jq).

python search_stac.py --lat 22.34806 --lon 69.86889 | jq

For example, this should print ready to use curl commands for downloading Sentinel-5P netCDF files:

python search_scihub.py --lon 2 --lat 48 -s 2020-3-1 --satellite Sentinel-5P --product-type L1B_RA_BD8 | jq -r '.[] | "curl --user s5pguest:s5pguest \"\(.links.alternative)\\$value\" > \(.title).nc"'

As Python modules

The Python modules can be imported to call their functions from Python. Refer to their docstrings to get usage information. Here are some examples.

# define an area of interest
import tsd
lat, lon = 42, 3
aoi = tsd.utils.geojson_geometry_object(lat, lon, 5000, 5000)

# search Landsat-8 images available on the AOI with a STAC API
x = tsd.search_stac.search(aoi, satellite='Landsat-8')

Common issues

Warning: A rasterio issue on Ubuntu causes the need for this environment variable (more info on rasterio's github):

export CURL_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt