Earth2Observe

Design Concept

earth2Observe is designed following the Template/Factory design pattern to create an abstract class as a template for different data sources.

The main objective of the earth2Observe is to provide a unified API for all remote sensing data sources, where you only have to worry about the domain of your data (date range and spatial extent) and the package does everything in the backend. For some data source like google earth engine and ECMWF you still have to register and create access key.

Design Concept

earth2observe provides a unified API for the following data sources - ECMWF - CHIRPS - Amazon-S3 - Google Earth Engine (still under development)

Some of the data sources provides the data in servers that needs an authentication key, to create the authentication key required for each data source check the authentication instruictions .

The API takes few parameters to determine the domain of your data - The date range you want to download the data within in the form of start, end, and the temporal_resolution - The spatial extent of your area of interest in the form of latitude and longitude limit latlim, lonlim - If the user does not provide the latlim, lonlim the Earth2Observe class will be initialized with the extent longitude limit [-180, 180], and latitude limit [-90, 90].

from earth2observe.earth2observe import Earth2Observe
start = "2009-01-01"
end = "2009-01-10"
temporal_resolution = "daily"
latlim = [4.19, 4.64]
lonlim = [-75.65, -74.73]

Each data source has different climate variables/datasets, and to know what variables/datasets each data source provides you can use the Catalog class that is with each data source. in this tutorial we will be downloading precipitation from the CHIRPS and Amazon S3 data source and temperature from ECMWF

• The downloaded data format differs also based on the data source the CHIRPS and the ECMWF has a post_download

  function that is triggered after a the end of each downloaded chunck of data is done, and this post_download functions triggers some function from the Pyramids GIS package. to convert the netcdf format into geotiff.

• If you like to convert the downloaded data to anyother format or crop the data to a smaller area that what you have

  originally downloaded, reproject, or re-align the rasters to have the same alignment (rows and columns) like other raster data you can also find all the required functions in the Pyramids GIS package.

Note

in future versions the latlim and lonlim will be deprecated and will be replaced by a geodataframe containing a polygon geometry

ECMWF

source = "ecmwf"
path = r"examples\data\ecmwf"
variables = ["precipitation"]

e2o = Earth2Observe(
    data_source=source,
    start=start,
    end=end,
    variables=variables,
    lat_lim=latlim,
    lon_lim=lonlim,
    temporal_resolution=temporal_resolution,
    path=path,
)
e2o.download()

CHIRPS

source = "chirps"
path = r"examples\data\chirps"
variables = ["precipitation"]
e2o = Earth2Observe(
    data_source=source,
    start=start,
    end=end,
    variables=variables,
    lat_lim=latlim,
    lon_lim=lonlim,
    temporal_resolution=temporal_resolution,
    path=path,
)
e2o.download()

parallel download

path = r"examples\data\chirps-cores"
e2o = Earth2Observe(
    data_source=source,
    start=start,
    end=end,
    variables=variables,
    lat_lim=latlim,
    lon_lim=lonlim,
    temporal_resolution=temporal_resolution,
    path=path,
)
e2o.download(cores=4)

Amazon-S3

path = r"examples\data\s3-backend"
source = "amazon-s3"
variables = ["precipitation"]
e2o = Earth2Observe(
    data_source=source,
    start=start,
    end=end,
    variables=variables,
    # lat_lim=latlim,
    # lon_lim=lonlim,
    temporal_resolution=temporal_resolution,
    path=path,
)
e2o.download()