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Resources","sub_category":"Soil and Land","monthly_downloads":1601,"total_dependent_repos":40,"total_dependent_packages":1,"readme":"====\nismn\n====\n\n|ci| |cov| |pip| |doc|\n\n.. |ci| image:: https://github.com/TUW-GEO/ismn/actions/workflows/build.yml/badge.svg?branch=master\n   :target: https://github.com/TUW-GEO/ismn/actions\n\n.. |cov| image:: https://coveralls.io/repos/TUW-GEO/ismn/badge.png?branch=master\n  :target: https://coveralls.io/r/TUW-GEO/ismn?branch=master\n\n.. |pip| image:: https://badge.fury.io/py/ismn.svg\n    :target: http://badge.fury.io/py/ismn\n\n.. |doc| image:: https://readthedocs.org/projects/ismn/badge/?version=latest\n   :target: http://ismn.readthedocs.org/\n\nReaders for data from the International Soil Moisture Network (ISMN) https://ismn.earth.\n\nThis package is installable through pip (verified for ``python\u003e=3.9``)\n\n.. code::\n\n    pip install ismn\n\nThis should also install all dependencies on Window, Linux or MacOS.\n\nQuickstart\n----------\nInitialise an `ISMN_Interface` by passing the path to your downloaded data.\nThe interface shows you available ISMN networks, stations and sensors.\nYou can load sensor time series as pandas DataFrames as well as metadata\non the stations surroundings, soil conditions and probes\n(depths, sensor type, etc.).\n\n.. code-block:: python\n\n    \u003e\u003e from ismn.interface import ISMN_Interface\n    \"\"\" .zip archives are downloaded from https://ismn.earth \"\"\"\n    \u003e\u003e ds = ISMN_Interface('Data_separate_files_header_20090101_20201231_9289_Cwpc_20221201.zip')\n    \"\"\" Read time series from your previously downloaded ISMN archive as pandas DataFrames \"\"\"\n    \u003e\u003e ds[\"REMEDHUS\"][\"Canizal\"][0].data\n\n        Out[0]:\n                                 soil_moisture soil_moisture_flag soil_moisture_orig_flag\n        date_time\n        2009-01-01 00:00:00          0.372                  G                       M\n        2009-01-01 01:00:00          0.372                  G                       M\n        ...                          ...                   ...                     ...\n        2020-12-31 22:00:00          0.285                  G                       M\n        2020-12-31 23:00:00          0.285                  G                       M\n\n    \"\"\" Each ISMN sensor comes with additional information on soil/landcover/climate etc. \"\"\"\n    \u003e\u003e ds[\"REMEDHUS\"][\"Canizal\"][0].metadata.to_pd()\n\n        Out[0]:\n        variable        key\n        climate_KG      val                           BSk\n        instrument      val           Stevens-Hydra-Probe\n                        depth_from                    0.0\n                        depth_to                     0.05\n        ...             ...                           ...\n        latitude        val                      41.19603\n        lc_2010         val                            20\n        longitude       val                      -5.35997\n        network         val                      REMEDHUS\n        station         val                       Canizal\n\nMany more features to e.g. visualise, select or transform data are available.\nSee the `full documentation \u003chttps://ismn.readthedocs.io/en/latest/\u003e`_.\n\nDocumentation\n-------------\nThe full documentation is available at https://ismn.readthedocs.io/en/latest and includes\na tutorial on reading ISMN data in python after downloading it from\nhttps://ismn.earth\n\nThe following **tutorials** are also available as ipython notebooks in ``docs/examples``:\n\n #. `ISMN reader basic functionality \u003chttps://ismn.readthedocs.io/en/latest/examples/interface.html\u003e`_\n #. `Adding custom metadata readers \u003chttps://ismn.readthedocs.io/en/latest/examples/custom_meta.html\u003e`_\n\nData used in the tutorials is *not* provided in this package. Please create an account at `ismn.earth \u003chttps://ismn.earth/en/\u003e`_\nto download the required files.\n\nFor a detailed description of the ISMN, technical data aspects (properties, coverage, etc.) and correct usage (applications), see\n\n    W. Dorigo et al. **The International Soil Moisture Network: serving Earth system science for over a decade**,\n    Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, 2021.\n\nOptional dependencies\n---------------------\n\nThe `cartopy \u003chttps://github.com/SciTools/cartopy\u003e`_ and `matplotlib \u003chttps://github.com/matplotlib/matplotlib\u003e`_ packages\nare only needed when creating data visualisations. They can be installed separately via\n\n.. code::\n\n    conda install -c conda-forge matplotlib cartopy\n\nor ``pip install ismn[plot]`` for most operating systems if you already have `geos \u003chttps://libgeos.org/\u003e`_ installed.\n\nIf you want to convert ISMN data into xarray objects, please install `xarray \u003chttps://github.com/pydata/xarray\u003e`_ and\n`dask \u003chttps://github.com/dask/dask\u003e`_ via\n\n.. code::\n\n    conda install -c conda-forge xarray dask\n\nor ``pip install ismn[xr]`` for most operating systems.\n\nCitation\n--------\n\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.855308.svg\n   :target: https://doi.org/10.5281/zenodo.855308\n\nIf you use the software in a publication then please cite it using the Zenodo DOI.\nBe aware that this badge links to the latest package version.\n\nPlease select your specific version at https://doi.org/10.5281/zenodo.855308 to get the DOI of that version.\nYou should normally always use the DOI for the specific version of your record in citations.\nThis is to ensure that other researchers can access the exact research artefact you used for reproducibility.\n\nYou can find additional information regarding DOI versioning at http://help.zenodo.org/#versioning\n\nDescription\n===========\n\nISMN data can be downloaded for free after creating an account on the `ISMN Website\n\u003chttp://ismn.geo.tuwien.ac.at/\u003e`_\n\nISMN data can be downloaded in two different formats:\n\n* Variables stored in separate files (CEOP formatted)\n* Variables stored in separate files (Header+values) (default format)\n\nBoth formats are supported by this package.\n\nIf you downloaded ISMN data in one of the supported formats in the past it can\nbe that station names are not recognized correctly because they contained the\n'_' character which is supposed to be the separator. If you experience problems\nbecause of this please download new data from the ISMN since this issue should\nbe fixed.\n\nVariables and Units\n-------------------\nThe following variables are available in the ISMN. Note that not every station\nmeasures all of the variables. You can use this package to read only data for\nlocations where one or multiple of the variables were measured.\n\n.. list-table:: Temporally dynamic variables and their units in ISMN\n   :widths: 25 15\n   :header-rows: 1\n\n   * - Variable\n     - Units\n   * - Soil Moisture\n     - m\\ :sup:`3`\\ /m\\ :sup:`3`\\\n   * - Soil Suction\n     - kPa\n   * - Soil Temperature\n     - °C\n   * - Air Temperature\n     - °C\n   * - Surface Temperature\n     - °C\n   * - Precipitation\n     - mm\n   * - Snow Depth\n     - mm\n   * - Snow Water Equivalent\n     - mm\n\n----\n\n.. list-table:: Temporally static variables and their units in ISMN\n   :widths: 35 35\n   :header-rows: 1\n\n   * - Variable\n     - Units\n   * - Climate classification\n     - None\n   * - Land cover classification\n     - None\n   * - Soil classification\n     - None\n   * - Bulk density\n     - g/cm³\n   * - Sand fraction\n     - % weight\n   * - Silt fraction\n     - % weight\n   * - Clay fraction\n     - % weight\n   * - Organic carbon\n     - % weight\n   * - Saturation\n     - % vol\n   * - Field capacity\n     - % vol\n   * - Potential plant available water\n     - % vol\n   * - Permanent wilting point\n     - % vol\n\nLandcover Classification\n------------------------\nThe ISMN data comes with information about landcover classification from the\nESA CCI land cover project (years 2000, 2005 and 2010) as well as from in-situ\nmeasurements. To use ESA CCI land cover variables for filtering the data in the get_dataset_ids\nfunction, set the keyword parameters (landcover_2000, landcover_2005 or landcover_2010)\nto the corresponding integer values (e.g. 10) in the list below. To get a list of\npossible values for filtering by in-situ values (keyword parameter: \"landcover_insitu\"),\ncall the get_landcover_types method of your ISMN_Interface object and set landcover='landcover_insitu'.\n\n.. list-table:: ISMN Landcover classes and meanings\n   :widths: 5 50\n   :header-rows: 1\n\n   * - Value\n     - Meaning\n   * - 10\n     - Cropland, rainfed\n   * - 11\n     - Cropland, rainfed / Herbaceous cover\n   * - 12\n     - Cropland, rainfed / Tree or shrub cover\n   * - 20\n     - Cropland, irrigated or post-flooding\n   * - 30\n     - Mosaic cropland (\u003e50%) / natural vegetation (tree, shrub, herbaceous)\n   * - 40\n     - Mosaic natural vegetation (\u003e50%) / cropland (\u003c50%)\n   * - 50\n     - Tree cover, broadleaved, evergreen, Closed to open (\u003e15%)\n   * - 60\n     - Tree cover, broadleaved, deciduous, Closed to open (\u003e15%)\n   * - 61\n     - Tree cover, broadleaved, deciduous, Closed (\u003e40%)\n   * - 62\n     - Tree cover, broadleaved, deciduous, Open (15-40%)\n   * - 70\n     - Tree cover, needleleaved, evergreen, Closed to open (\u003e15%)\n   * - 71\n     - Tree cover, needleleaved, evergreen, Closed (\u003e40%)\n   * - 72\n     - Tree cover, needleleaved, evergreen, Open (15-40%)\n   * - 80\n     - Tree cover, needleleaved, deciduous, Closed to open (\u003e15%)\n   * - 81\n     - Tree cover, needleleaved, deciduous, Closed (\u003e40%)\n   * - 82\n     - Tree cover, needleleaved, deciduous, Open (15-40%)\n   * - 90\n     - Tree cover, mixed leaf type (broadleaved and needleleaved)\n   * - 100\n     - Mosaic tree and shrub (\u003e50%) / herbaceous cover (\u003c50%)\n   * - 110\n     - Mosaic herbaceous cover (\u003e50%) / tree and shrub (\u003c50%)\n   * - 120\n     - Shrubland\n   * - 121\n     - Shrubland / Evergreen Shrubland\n   * - 122\n     - Shrubland / Deciduous Shrubland\n   * - 130\n     - Grassland\n   * - 140\n     - Lichens and mosses\n   * - 150\n     - Sparse vegetation (tree, shrub, herbaceous cover) (\u003c15%)\n   * - 152\n     - Sparse vegetation (\u003c15%) / Sparse shrub (\u003c15%)\n   * - 153\n     - Sparse vegetation (\u003c15%) / Sparse herbaceous cover (\u003c15%)\n   * - 160\n     - Tree cover, flooded, fresh or brackish water\n   * - 170\n     - Tree cover, flooded, saline water\n   * - 180\n     - Shrub or herbaceous cover, flooded, fresh/saline/brackish water\n   * - 190\n     - Urban areas\n   * - 200\n     - Bare areas\n   * - 201\n     - Consolidated bare areas\n   * - 202\n     - Unconsolidated bare areas\n   * - 210\n     - Water\n   * - 220\n     - Permanent snow and ice\n\nClimate Classification\n----------------------\nThe ISMN data comes with information about climate classification from the Koeppen-Geiger\nClimate Classification (2007) as well as in-situ measurements. To use\nKoeppen-Geiger variable for filtering the data in the get_dataset_ids function, set the\nkeyword parameter \"climate\" to the corresponding keys (e.g. 'Af') in the list below. To get a list of\npossible values for filtering by in-situ values (keyword parameter: \"climate_insitu\"), call the\nget_climate_types method of your ISMN_Interface object and set climate='climate_insitu'.\n\n.. list-table:: Climate Classes and Meanings\n   :widths: 5 50\n   :header-rows: 1\n\n   * - Class\n     - Meaning\n   * - Af\n     - Tropical Rainforest\n   * - Am\n     - Tropical Monsoon\n   * - As\n     - Tropical Savanna Dry\n   * - Aw\n     - Tropical Savanna Wet\n   * - BWk\n     - Arid Desert Cold\n   * - BWh\n     - Arid Desert Hot\n   * - BWn\n     - Arid Desert With Frequent Fog\n   * - BSk\n     - Arid Steppe Cold\n   * - BSh\n     - Arid Steppe Hot\n   * - BSn\n     - Arid Steppe With Frequent Fog\n   * - Csa\n     - Temperate Dry Hot Summer\n   * - Csb\n     - Temperate Dry Warm Summer\n   * - Csc\n     - Temperate Dry Cold Summer\n   * - Cwa\n     - Temperate Dry Winter, Hot Summer\n   * - Cwb\n     - Temperate Dry Winter, Warm Summer\n   * - Cwc\n     - Temperate Dry Winter, Cold Summer\n   * - Cfa\n     - Temperate Without Dry Season, Hot Summer\n   * - Cfb\n     - Temperate Without Dry Season, Warm Summer\n   * - Cfc\n     - Temperate Without Dry Season, Cold Summer\n   * - Dsa\n     - Cold Dry Summer, Hot Summer\n   * - Dsb\n     - Cold Dry Summer, Warm Summer\n   * - Dsc\n     - Cold Dry Summer, Cold Summer\n   * - Dsd\n     - Cold Dry Summer, Very Cold Winter\n   * - Dwa\n     - Cold Dry Winter, Hot Summer\n   * - Dwb\n     - Cold Dry Winter, Warm Summer\n   * - Dwc\n     - Cold Dry Winter, Cold Summer\n   * - Dwd\n     - Cold Dry Winter, Very Cold Winter\n   * - Dfa\n     - Cold Dry Without Dry Season, Hot Summer\n   * - Dfb\n     - Cold Dry Without Dry Season, Warm Summer\n   * - Dfc\n     - Cold Dry Without Dry Season, Cold Summer\n   * - Dfd\n     - Cold Dry Without Dry Season, Very Cold Winter\n   * - ET\n     - Polar Tundra\n   * - EF\n     - Polar Eternal Winter\n   * - W\n     - Water\n\n\nContribute\n==========\n\nWe are happy if you want to contribute. Please raise an issue explaining what\nis missing or if you find a bug. We will also gladly accept pull requests\nagainst our master branch for new features or bug fixes.\n\n\nGuidelines\n----------\n\nIf you want to contribute please follow these steps:\n\n- Fork the ismn repository to your account\n- Clone the repository\n- make a new feature branch from the ismn master branch\n- Add your feature\n- Please include tests for your contributions in one of the test directories.\n  We use pytest so a simple function called test_my_feature is enough\n- submit a pull request to our master branch\n\nCode Formatting\n---------------\nTo apply pep8 conform styling to any changed files [we use `yapf`](https://github.com/google/yapf). The correct\nsettings are already set in `setup.cfg`. Therefore the following command\nshould be enough:\n\n    yapf file.py --in-place\n\nRelease new version\n-------------------\n\nTo release a new version of this package, make sure all tests are passing on the\nmaster branch and the CHANGELOG.rst is up-to-date, with changes for the new version\nat the top.\n\nThen draft a new release at https://github.com/TUW-GEO/ismn/releases.\nCreate a version tag following the ``v{MAJOR}.{MINOR}.{PATCH}`` pattern.\nThis will trigger a new build on GitHub and should push the packages to pypi after\nall tests have passed.\n\nIf this does not work (tests pass but upload fails) you can download the\n``whl`` and ``dist`` packages for each workflow run from\nhttps://github.com/TUW-GEO/ismn/actions (Artifacts) and push them manually to\nhttps://pypi.org/project/ismn/ (you need to be a package maintainer on pypi for that).\n\nIn any case, ``pip install ismn`` should download the newest version afterwards.\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.5194/hess-25-5749-2021","https://doi.org/10.5281/zenodo.855308"],"works":{"https://doi.org/10.5281/zenodo.855308":null},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["earth-science","smap","ecmwf","cci","esa","preprocess","read","sm"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/1056","html_url":"https://ost.ecosyste.ms/projects/1056"}