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        "author": "Carlo de Franchis",
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        "description": "# Time Series Downloader (TSD)\n[![Build Status](https://travis-ci.com/cmla/tsd.svg?branch=master)](https://travis-ci.com/cmla/tsd)\n\nAutomatic download of Sentinel, Landsat and Planet crops.\n\n[Carlo de Franchis](mailto:carlo.de-franchis@ens-cachan.fr),\nCMLA, ENS Cachan, Universit\u00e9 Paris-Saclay, 2016-19\n\nWith contributions from [Enric Meinhardt-Llopis](mailto:enric.meinhardt@cmla.ens-cachan.fr), [Axel Davy](mailto:axel.davy@ens.fr) and [Tristan Dagobert](mailto:tristan.dagobert@cmla.ens-cachan.fr).\n\n\nThe main source code repository for this software is https://github.com/cmla/tsd.\n\n# Installation and dependencies\n\n## GDAL\nThe main dependency is GDAL. All the others can be installed\nwith `pip` as shown in the [next section](#install-tsd-as-a-python-package).\n\n### On Ubuntu\n`gdal` can be installed with `apt-get`. In order to get a\nrecent version we recommend adding the PPA `ubuntugis-unstable` (first\ncommand below):\n\n    sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable\n    sudo apt-get update\n    sudo apt-get install libgdal-dev gdal-bin\n\n### On macOS\nThere are several ways of installing `gdal`. I recommend option 1 as it\ngives a version of gdal 2.3 that works with JP2 files.\n\n_Note_: a shell script installing all the needed stuff (`brew`, `python`,\n`gdal`...) on an empty macOS system is given in the file\n[macos_install_from_scratch.sh](macos_install_from_scratch.sh).\n\n#### Option 1: using the GDAL Complete Compatibility Framework.\n\n[Download](http://www.kyngchaos.com/files/software/frameworks/GDAL_Complete-2.3.dmg)\nand install the `.dmg` file. Update your `PATH` after the installation by\nrunning this command:\n\n    export PATH=\"/Library/Frameworks/GDAL.framework/Programs:$PATH\"\n\nCopy it in your `~/.profile`.\n\n#### Option 2: using brew\n\n    brew install gdal --with-complete\n\nNote that this version doesn't support JP2 files (hence it will fail to get\nSentinel-2 crops).\n\n## Install TSD as a python package\n\nOnce `gdal` is installed on your machine you can install `tsd` with `pip`:\n\n    git clone https://github.com/cmla/tsd\n    cd tsd\n    pip install numpy  # required by rasterio\n    pip install -e . --no-binary rasterio\n\nAlternatively `tsd` can also be installed without downloading a tarball or a git clone:\n\n    pip install --upgrade https://github.com/cmla/tsd/tarball/master --no-binary rasterio\n\n\n# Usage\n\nSearch and download is performed by `get_sentinel2.py`, `get_landsat.py`,\n`get_planet.py` and `get_sentinel1.py` (one file per satellite constellation).\nThey can be used both as command line scripts or as Python modules.\n\nThey use the Python modules `search_devseed.py`, `search_scihub.py`,\n`search_peps.py` and `search_planet.py` (one file per API provider).\n\n## From the command line\nTSD can be used from the command line through the Python scripts\n`get_*.py`. For instance, to download and process Sentinel-2 images of the\nJamnagar refinery, located at latitude 22.34806 and longitude 69.86889, run\n\n    python get_sentinel2.py --lat 22.34806 --lon 69.86889 -b B02 B03 B04 -o test\n\nThis downloads crops of size 5000 x 5000 meters from the bands 2, 3 and 4,\ncorresponding to the blue, green and red channels, and stores them in geotif\nfiles in the `test` directory.\n\nIt should print something like this on `stdout` (the number of images might vary):\n\n    Found 22 images\n    Elapsed time: 0:00:02.301129\n\n    Downloading 66 crops (22 images with 3 bands)... 66 / 66\n    Elapsed time: 0:00:57.620805\n\n    Reading 22 cloud masks... 22 / 22\n    6 cloudy images out of 22\n    Elapsed time: 0:00:15.066992\n\nImages with more than half of the pixels covered by clouds (according to the\ncloud polygons available in Sentinel-2 images metadata, or Landsat-8 images\nquality bands) are moved in the `test/cloudy` subfolder.\n\nTo specify the desired bands, use the `-b` or `--band` flag. The crop size can\nbe changed with the `--width` and `--height` flags. For instance\n\n    python get_sentinel2.py --lat 22.34806 --lon 69.86889 -b B11 B12 --width 8000 --height 6000\n\ndownloads crops of size 8000 x 6000 meters, only for the SWIR channels (bands 11\nand 12).\n\nAll the available options are listed with the `-h` or `--help` flag:\n\n    python get_sentinel2.py -h\n\nYou can also run any of the `search_*.py` scripts from the command line\nseparately. Run them with `-h` to get the list of available options.  For a\nnice output formatting, pipe their output to `jq` (`brew install jq`).\n\n    python search_devseed.py --lat 22.34806 --lon 69.86889 | jq\n\n\n## As Python modules\n\nThe Python modules can be imported to call their functions from Python. Refer\nto their docstrings to get usage information. Here are some examples.\n\n    # define an area of interest\n    import tsd\n    lat, lon = 42, 3\n    aoi = tsd.utils.geojson_geometry_object(lat, lon, 5000, 5000)\n\n    # search Landsat-8 images available on the AOI with Development Seed's API\n    x = tsd.search_devseed.search(aoi, satellite='Landsat-8')",
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