jachym
commented
6 years ago 
Conversion script sample (python):
import csv
import json
features = {}
with open('czechrep.csv', newline='') as csvfile:
spamreader = csv.reader(csvfile, delimiter=',')
for CountryOrTerritory,ReportingYear,UpdateTime,StationLocalId,SamplingPointLocalId,SamplingPoint_Latitude,SamplingPoint_Longitude,Pollutant,AggregationType,Namespace,Unit,BeginPosition,EndPosition,Validity,Verification,DataCoverage,DataCapture,TimeCoverage,AQValue in spamreader:
if StationLocalId in features:
features[StationLocalId]["properties"][Pollutant] = float(AQValue)
else:
features[StationLocalId] = {
"type": "Feature",
"properties": {
"CountryOrTerritory": CountryOrTerritory,
"ReportingYear": ReportingYear,
"UpdateTime": UpdateTime,
"StationLocalId": StationLocalId,
"SamplingPointLocalId": SamplingPointLocalId,
"Namespace": Namespace,
Pollutant: float(AQValue)
},
"geometry": {
"type": "Point",
"coordinates": [float(SamplingPoint_Longitude), float(SamplingPoint_Latitude) ]
}
}
j = {
"type":"FeatureCollection",
"features": []
}
for f in features:
j["features"].append(features[f])
with open("czechrep.geojson", "w") as out:
json.dump(j, out, indent=4)
As a result of the categorization of received data from individual measurement stations provided as pm10 parameter the analysis of the occurrence of dust decay can be carried out. For this purpose, a tool Categorization will be used to categorize values on a layer. The categorization process depends on the user and the parameters that will be determined by the user. A dot layer is displayed, divided into data values. User can also interpolate the data and present the min the form of isolines.