Unit 30 - PyWPS LST region zones¶

A last (fourth) version of the process will return for input region and dates LST zones in vector format (GML). The output parameter is defined as ComplexOutput, see lines 26-29. Zones defined on lines 85-88 are created by r.recode (92). Than raster zones are convert to vector by r.to.vect on line 99. Finally vector zones are exported into GML format on line 106 by v.out.ogr. Response content is set on line 112.

Note that also class name (31), process identifier (33), title (34), abstract (39) and version (40) needs to be updated.

#!/usr/bin/env python3

from subprocess import PIPE
from datetime import datetime

from grass.pygrass.modules import Module
from grass.script import parse_key_val
from pywps import Process, LiteralInput, ComplexInput, ComplexOutput, Format


class ModisV4(Process):

    def __init__(self):
        inputs = list()
        outputs = list()

        inputs.append(ComplexInput('region', 'Input vector region',
                    supported_formats=[
                        Format('text/xml'),
                        Format('application/gml+xml')]))
        inputs.append(LiteralInput('start', 'Start date (eg. 2023-03-01)',
                                   data_type='string'))
        inputs.append(LiteralInput('end', 'End date (eg. 2023-03-01)',
                                   data_type='string'))

        outputs.append(ComplexOutput('output', 'Output LST zones',
                     supported_formats=[
                         Format('text/xml'),
                         Format('application/gml+xml')]))

        super(ModisV4, self).__init__(
            self._handler,
            identifier="modis-v4",
            title="Modis process (v4)",
            inputs=inputs,
            outputs=outputs,
            # here you could also specify the GRASS location, for example:
            # grass_location="EPSG:5514",
            abstract="Computes LST stats for given area and period (limited to Germany and 2023).",
            version="0.4",
            store_supported=True,
            status_supported=True)

    @staticmethod
    def _handler(request, response):
        def check_date(date_str):
            d = datetime.strptime(date_str, '%Y-%m-%d')
            if d.year != 2023:
                raise Exception("Only year 2023 allowed")

        check_date(request.inputs['start'][0].data)
        check_date(request.inputs['end'][0].data)

        Module('v.import',
                input=request.inputs['region'][0].file,
                output='poly', overwrite=True)
        Module('g.region', vector='poly', align='c_001')
        Module('r.mask', vector='poly', overwrite=True)

        output_map = "lst_zones"
        Module("t.rast.series",
               overwrite=True,
               input="modis_c@PERMANENT",
               method="average",
               order="start_time",
               nprocs=1,
               memory=300,
               where="start_time >= '{}' and start_time < '{}'".format(
                   request.inputs["start"][0].data,
                   request.inputs["end"][0].data),
               output=output_map,
               file_limit=1000)

        m = Module("r.univar",
                   flags="ge",
                   overwrite=True,
                   map=output_map,
                   percentile=90,
                   nprocs=1,
                   separator="pipe",
                   stdout_=PIPE)

        stats = parse_key_val(m.outputs.stdout, val_type=float)

        recode_table = """{min}:{first}:1
{first}:{median}:2
{median}:{third}:3
{third}:{max}:4""".format(
    min=stats['min'], first=stats['first_quartile'],
    median=stats['median'], third=stats['third_quartile'],
    max=stats['max'])                     
        Module("r.recode",
               overwrite=True,               
               input = output_map,
               output = output_map + '_zones',
               rules = "-",
               stdin_=recode_table)

        Module("r.to.vect",
               overwrite=True,
               flags = 'v',
               input = output_map + '_zones',
               output = output_map + '_zones',
               type = "area")

        Module('v.out.ogr',
               overwrite=True,
               input=output_map + '_zones',
               output=output_map + '.gml',
               format='GML')

        response.outputs['output'].file = output_map + '.gml'

        return response


if __name__ == "__main__":
    from pywps.app.Service import Service

    processes = [ModisV4()]
    application = Service(processes)

Sample process to download: modis_v4.py

Important

Do not forget to import process as done in Unit 27 and restart demo PyWPS server.

Execute process:

http://localhost:5000/wps?request=Execute&service=WPS&identifier=modis-v4&version=1.0.0&datainputs=start=2023-03-01;end=2023-04-01;region=@xlink:href=http://localhost:5000/static/data/jena_boundary.gpkg

Compare with (output return as reference):

../_images/qgis-result.png — Fig. 127 Example of WPS process consumption in QGIS using WPS Client plugin. Install the plugin from ZIP file.¶

Note

It is the end (of the workshop), enjoy GRASS GIS (and your real life)! :-)

Unit 30 - PyWPS LST region zones¶

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