Environmental Data Platform

min10_LaimburgProvince

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Offering (timeseries group) of the Sensor Observation Service - SOS - collected within the MONALISA project belonging to a network of 31 measuring stations in the Bolzano province. The offering groups timeseries from a specific sensor installed in the station site. Timeseries are identified with the observed parameter name that are listed in the keywords list. The naming convention of the title define the offering identification name: “Offering”_”Station name and altitude”. The complete list of the timeseries provided by the web service, is available in json format in the API: http://monalisasos.eurac.edu/sos/api/v1/timeseries/ . Further information can be found on the project website: http://monalisasos.eurac.edu/sos/. To browse and/or download the timeseries data a map viewer is available: http://monalisasos.eurac.edu/sos/static/client/helgoland/index.html#/map

http://monalisasos.eurac.edu/sos/api/v1/

DESCRIBE HERE THE RESOURCE

Air Humidity - 10 minute average, Air Humidity - daily average, Air Pressure - 10 minute average, Air Pressure - daily average, Air Temperature - 10 minute average, Air Temperature - daily average, Air Temperature - daily maximum, Air Temperature - daily minimum, Dew point - 10 minute average, Global Radiation - 10 minute average, Global Radiation - daily average, Precipitation - 5 minute sum, Precipitation - daily sum, Sunshine duration - 10 minute average, Wind Direction - 10 minute average, Wind Speed - 10 minute average, Wind Speed - daily average, LaimburgProvince, collection, Land use, Land cover

CC-BY-4.0

Eurac Research - Institute for Earth Observation
bartolomeo.ventura@eurac.edu
Viale Druso, 1 / Drususallee 1, Eurac Research, Bolzano, Autonomous Province of Bolzano, 39100, Italy


2013-12-31T23:00:00.000Z 2017-01-01T22:50:00.000Z

WGS-84 (4326:EPSG)

Grid

mapDigital

Imagery base maps earth cover

Snippet code
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SOS TEST SNIPPET CODE
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#install the MonalisR package from Github using devtools
#install.packages("remotes")
#library(remotes)
#remotes::install_github("https://github.com/mattia6690/MonalisR")

library(MonalisR)
library(tibble)

#Set the path to the SOS
SOS="http://monalisasos.eurac.edu/sos/api/v1/timeseries/"

#Explore the elements of the database
mnls_foi=getMonalisaDB(url=SOS,subset="foi")
mnls_props=getMonalisaDB(url=SOS,subset="property")
mnls_proc=getMonalisaDB(url=SOS,subset="procedure")
mnls_comb=getMonalisaDB(url=SOS,subset="combined")

#Get the spatial response
mnls_geom=getMonalisaDB(url=SOS,subset = "geom")

#Get the best possible representation of all Info at once
mnls_all=getMonalisaDB(url=SOS,subset = "all")

#Download the data and store it to an object
down<-downloadMonalisa(starturl=SOS,
                       datestart="2013-12-31T23:00:00.000Z",
                       dateend="2017-01-01T22:50:00.000Z",
                       foi="LaimburgProvince",
                       procedure="min10_LaimburgProvince",
                       property="min10")

# Use the built-in plotting capabilities for the package
plotMonalisaLeaflet()
Related docs
Name Description Link Date published Category
SOS data upload Python System to automaticay upload data from files Link May 13, 2021 SOS
MonalisR for SOS-API Documentation and repository of the MonalisaR package to access SOS-API using R Link April 28, 2021 SOS