Tutorials

Imports

Python class LucasRequest to define a request

from st_lucas import LucasRequest

Python class LucasIO to input / output LUCAS points

from st_lucas import LucasIO

Instantiate classes to create data request

request = LucasRequest()

and to control data input/output

lucasio = LucasIO()

Spatial filter

Spatial filter by bbox property (only EPSG:3035 is supported)

request.bbox = (4504276, 3020369, 4689608, 3105290)

By country code

request.countries = ['CZ']

Example for multiple countries (Python list)

request.countries = ['CZ', 'SK']

By AOI aoi_polygon (GML format)

request.aoi_polygon = '''
<Within>
    <PropertyName>lucas:geom</PropertyName>' \
    <gml:Polygon xmlns:gml="http://www.opengis.net/gml" srsName="urn:ogc:def:crs:EPSG::3035" gml:id="polygon_32.geom.0">' \
        <gml:exterior>' \
            <gml:LinearRing>' \
                 <gml:posList>3014669.3195414557 4640226.080241454 2981893.140187475 4628385.701013993 2965449.7283930806 4639492.816821902 2958781.6185918115 4658392.1858341275 2977549.274784839 4672892.4477362465 3004572.819247867 4661017.510044226 3014669.3195414557 4640226.080241454 </gml:posList>' \
             </gml:LinearRing>' \
         </gml:exterior>' \
    </gml:Polygon>' \
</Within>
'''

Temporal filter

Temporal filter by single year definition

request.years = [2006]

or by multiple years (Python list)

request.years = [2006, 2009]

Thematic filter

Thematic filter by setting codes of thematic groups

• CO - Copernicus;

• FO - Forestry;

• IN - INSPIRE;

• LC_LU - Land cover, Land use;

• LC_LU_SO - Land cover, Land use, Soil]

request.group = 'LC_LU'

Space-time aggregation

Space-time aggregation by st_aggregated property we determine whether the data should be space-time aggregated. Space-time aggregation means that one record in the attribute table represents one point with all values measured in all specified years.

request.st_aggregated = True

Download LUCAS points based on request

Download data by using download() method using on the prepared request

lucasio.download(request)

or optionally by build() method as a helper function to test the requrest without dowloading the data

request.build()

Convert downloaded data

Get data in specified format by to_geopandas() method to convert the data into GeoDataFrame object

lucasio.to_geopandas()

by to_gml() method to convert data into OGC GML format

lucasio.to_gml()

by to_gpkg() method to save the data in a OGC GeoPackage file

lucasio.to_gpkg('sample.gpkg')

• 1. Access harmonized LUCAS samples
  • 1.1. Install
    • 1.1.1. Note for Google Colab
    • 1.1.2. Install st_lucas package
  • 1.2. Usage
    • 1.2.1. Define a request
    • 1.2.2. Download data based on a request
    • 1.2.3. Get data in specified format
  • 1.3. Request examples
    • 1.3.1. Filter by countries
    • 1.3.2. Filter by polygon
    • 1.3.3. Filter by years
    • 1.3.4. Thematic groups
    • 1.3.5. Filter by attributes
    • 1.3.6. Space-time aggregation
    • 1.3.7. Show photos of selected LUCAS point
      • 1.3.7.1. Display photos
      • 1.3.7.2. Download photos
• 2. Land Cover Validation with LUCAS dataset
  • 2.1. Install
    • 2.1.1. Note for Google Colab
    • 2.1.2. Install requirements
  • 2.2. Land Cover validation
    • 2.2.1. Configure validation
    • 2.2.2. Initialize the validator
    • 2.2.3. Check validity of the inputs
    • 2.2.4. Run land cover map and reference overlay
    • 2.2.5. Report the validation results
    • 2.2.6. Plot confusion matrix
    • 2.2.7. Save the validation overlay geodata to a vector
    • 2.2.8. Classes aggregation
• 3. Analyze LUCAS data
  • 3.1. Install
    • 3.1.1. Note for Google Colab
    • 3.1.2. Install st_lucas package
  • 3.2. Download sample LUCAS points
    • 3.2.1. Define request
    • 3.2.2. Download data
    • 3.2.3. Inspect downloaded LUCAS data
    • 3.2.4. Show statistics
  • 3.3. Class aggregation
  • 3.4. Nomenclature translation