Readers for data from the International Soil Moisture Network (ISMN) https://ismn.earth.
This package is installable through pip (verified for python>=3.9)
pip install ismn
This should also install all dependencies on Window, Linux or MacOS.
Initialise an ISMN_Interface by passing the path to your downloaded data. The interface shows you available ISMN networks, stations and sensors. You can load sensor time series as pandas DataFrames as well as metadata on the stations surroundings, soil conditions and probes (depths, sensor type, etc.).
>> from ismn.interface import ISMN_Interface
""" .zip archives are downloaded from https://ismn.earth """
>> ds = ISMN_Interface('Data_separate_files_header_20090101_20201231_9289_Cwpc_20221201.zip')
""" Read time series from your previously downloaded ISMN archive as pandas DataFrames """
>> ds["REMEDHUS"]["Canizal"][0].data
Out[0]:
soil_moisture soil_moisture_flag soil_moisture_orig_flag
date_time
2009-01-01 00:00:00 0.372 G M
2009-01-01 01:00:00 0.372 G M
... ... ... ...
2020-12-31 22:00:00 0.285 G M
2020-12-31 23:00:00 0.285 G M
""" Each ISMN sensor comes with additional information on soil/landcover/climate etc. """
>> ds["REMEDHUS"]["Canizal"][0].metadata.to_pd()
Out[0]:
variable key
climate_KG val BSk
instrument val Stevens-Hydra-Probe
depth_from 0.0
depth_to 0.05
... ... ...
latitude val 41.19603
lc_2010 val 20
longitude val -5.35997
network val REMEDHUS
station val CanizalMany more features to e.g. visualise, select or transform data are available. See the full documentation.
The full documentation is available at https://ismn.readthedocs.io/en/latest and includes a tutorial on reading ISMN data in python after downloading it from https://ismn.earth
The following tutorials are also available as ipython notebooks in docs/examples:
Data used in the tutorials is not provided in this package. Please create an account at ismn.earth to download the required files.
For a detailed description of the ISMN, technical data aspects (properties, coverage, etc.) and correct usage (applications), see
W. Dorigo et al. The International Soil Moisture Network: serving Earth system science for over a decade, Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, 2021.
The cartopy and matplotlib packages are only needed when creating data visualisations. They can be installed separately via
conda install -c conda-forge matplotlib cartopy
or pip install ismn[plot] for most operating systems if you already have geos installed.
If you want to convert ISMN data into xarray objects, please install xarray and dask via
conda install -c conda-forge xarray dask
or pip install ismn[xr] for most operating systems.
If you use the software in a publication then please cite it using the Zenodo DOI. Be aware that this badge links to the latest package version.
Please select your specific version at https://doi.org/10.5281/zenodo.855308 to get the DOI of that version. You should normally always use the DOI for the specific version of your record in citations. This is to ensure that other researchers can access the exact research artefact you used for reproducibility.
You can find additional information regarding DOI versioning at http://help.zenodo.org/#versioning
ISMN data can be downloaded for free after creating an account on the ISMN Website
ISMN data can be downloaded in two different formats:
- Variables stored in separate files (CEOP formatted)
- Variables stored in separate files (Header+values) (default format)
Both formats are supported by this package.
If you downloaded ISMN data in one of the supported formats in the past it can be that station names are not recognized correctly because they contained the '_' character which is supposed to be the separator. If you experience problems because of this please download new data from the ISMN since this issue should be fixed.
The following variables are available in the ISMN. Note that not every station measures all of the variables. You can use this package to read only data for locations where one or multiple of the variables were measured.
| Variable | Units |
|---|---|
| Soil Moisture | m3/m3 |
| Soil Suction | kPa |
| Soil Temperature | °C |
| Air Temperature | °C |
| Surface Temperature | °C |
| Precipitation | mm |
| Snow Depth | mm |
| Snow Water Equivalent | mm |
| Variable | Units |
|---|---|
| Climate classification | None |
| Land cover classification | None |
| Soil classification | None |
| Bulk density | g/cm³ |
| Sand fraction | % weight |
| Silt fraction | % weight |
| Clay fraction | % weight |
| Organic carbon | % weight |
| Saturation | % vol |
| Field capacity | % vol |
| Potential plant available water | % vol |
| Permanent wilting point | % vol |
The ISMN data comes with information about landcover classification from the ESA CCI land cover project (years 2000, 2005 and 2010) as well as from in-situ measurements. To use ESA CCI land cover variables for filtering the data in the get_dataset_ids function, set the keyword parameters (landcover_2000, landcover_2005 or landcover_2010) to the corresponding integer values (e.g. 10) in the list below. To get a list of possible values for filtering by in-situ values (keyword parameter: "landcover_insitu"), call the get_landcover_types method of your ISMN_Interface object and set landcover='landcover_insitu'.
| Value | Meaning |
|---|---|
| 10 | Cropland, rainfed |
| 11 | Cropland, rainfed / Herbaceous cover |
| 12 | Cropland, rainfed / Tree or shrub cover |
| 20 | Cropland, irrigated or post-flooding |
| 30 | Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous) |
| 40 | Mosaic natural vegetation (>50%) / cropland (<50%) |
| 50 | Tree cover, broadleaved, evergreen, Closed to open (>15%) |
| 60 | Tree cover, broadleaved, deciduous, Closed to open (>15%) |
| 61 | Tree cover, broadleaved, deciduous, Closed (>40%) |
| 62 | Tree cover, broadleaved, deciduous, Open (15-40%) |
| 70 | Tree cover, needleleaved, evergreen, Closed to open (>15%) |
| 71 | Tree cover, needleleaved, evergreen, Closed (>40%) |
| 72 | Tree cover, needleleaved, evergreen, Open (15-40%) |
| 80 | Tree cover, needleleaved, deciduous, Closed to open (>15%) |
| 81 | Tree cover, needleleaved, deciduous, Closed (>40%) |
| 82 | Tree cover, needleleaved, deciduous, Open (15-40%) |
| 90 | Tree cover, mixed leaf type (broadleaved and needleleaved) |
| 100 | Mosaic tree and shrub (>50%) / herbaceous cover (<50%) |
| 110 | Mosaic herbaceous cover (>50%) / tree and shrub (<50%) |
| 120 | Shrubland |
| 121 | Shrubland / Evergreen Shrubland |
| 122 | Shrubland / Deciduous Shrubland |
| 130 | Grassland |
| 140 | Lichens and mosses |
| 150 | Sparse vegetation (tree, shrub, herbaceous cover) (<15%) |
| 152 | Sparse vegetation (<15%) / Sparse shrub (<15%) |
| 153 | Sparse vegetation (<15%) / Sparse herbaceous cover (<15%) |
| 160 | Tree cover, flooded, fresh or brackish water |
| 170 | Tree cover, flooded, saline water |
| 180 | Shrub or herbaceous cover, flooded, fresh/saline/brackish water |
| 190 | Urban areas |
| 200 | Bare areas |
| 201 | Consolidated bare areas |
| 202 | Unconsolidated bare areas |
| 210 | Water |
| 220 | Permanent snow and ice |
The ISMN data comes with information about climate classification from the Koeppen-Geiger Climate Classification (2007) as well as in-situ measurements. To use Koeppen-Geiger variable for filtering the data in the get_dataset_ids function, set the keyword parameter "climate" to the corresponding keys (e.g. 'Af') in the list below. To get a list of possible values for filtering by in-situ values (keyword parameter: "climate_insitu"), call the get_climate_types method of your ISMN_Interface object and set climate='climate_insitu'.
| Class | Meaning |
|---|---|
| Af | Tropical Rainforest |
| Am | Tropical Monsoon |
| As | Tropical Savanna Dry |
| Aw | Tropical Savanna Wet |
| BWk | Arid Desert Cold |
| BWh | Arid Desert Hot |
| BWn | Arid Desert With Frequent Fog |
| BSk | Arid Steppe Cold |
| BSh | Arid Steppe Hot |
| BSn | Arid Steppe With Frequent Fog |
| Csa | Temperate Dry Hot Summer |
| Csb | Temperate Dry Warm Summer |
| Csc | Temperate Dry Cold Summer |
| Cwa | Temperate Dry Winter, Hot Summer |
| Cwb | Temperate Dry Winter, Warm Summer |
| Cwc | Temperate Dry Winter, Cold Summer |
| Cfa | Temperate Without Dry Season, Hot Summer |
| Cfb | Temperate Without Dry Season, Warm Summer |
| Cfc | Temperate Without Dry Season, Cold Summer |
| Dsa | Cold Dry Summer, Hot Summer |
| Dsb | Cold Dry Summer, Warm Summer |
| Dsc | Cold Dry Summer, Cold Summer |
| Dsd | Cold Dry Summer, Very Cold Winter |
| Dwa | Cold Dry Winter, Hot Summer |
| Dwb | Cold Dry Winter, Warm Summer |
| Dwc | Cold Dry Winter, Cold Summer |
| Dwd | Cold Dry Winter, Very Cold Winter |
| Dfa | Cold Dry Without Dry Season, Hot Summer |
| Dfb | Cold Dry Without Dry Season, Warm Summer |
| Dfc | Cold Dry Without Dry Season, Cold Summer |
| Dfd | Cold Dry Without Dry Season, Very Cold Winter |
| ET | Polar Tundra |
| EF | Polar Eternal Winter |
| W | Water |
We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests against our master branch for new features or bug fixes.
If you want to contribute please follow these steps:
- Fork the ismn repository to your account
- Clone the repository
- make a new feature branch from the ismn master branch
- Add your feature
- Please include tests for your contributions in one of the test directories. We use pytest so a simple function called test_my_feature is enough
- submit a pull request to our master branch
To apply pep8 conform styling to any changed files [we use yapf](https://github.com/google/yapf). The correct settings are already set in setup.cfg. Therefore the following command should be enough:
yapf file.py --in-place
To release a new version of this package, make sure all tests are passing on the master branch and the CHANGELOG.rst is up-to-date, with changes for the new version at the top.
Then draft a new release at https://github.com/TUW-GEO/ismn/releases.
Create a version tag following the v{MAJOR}.{MINOR}.{PATCH} pattern.
This will trigger a new build on GitHub and should push the packages to pypi after
all tests have passed.
If this does not work (tests pass but upload fails) you can download the
whl and dist packages for each workflow run from
https://github.com/TUW-GEO/ismn/actions (Artifacts) and push them manually to
https://pypi.org/project/ismn/ (you need to be a package maintainer on pypi for that).
In any case, pip install ismn should download the newest version afterwards.