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Table 1 Characteristics of the greenspace data sources

From: Comparing different data sources by examining the associations between surrounding greenspace and children's weight status

Type of measurements Biophysical variables in vegetation Data of categorical land uses Data of categorical land uses
Type of data Primary data Primary data Secondary data
Key characteristics Using Landsat image to calculate the visible and near-infrared light reflected by vegetation. The result refers to the NDVI A project which allows the community of Internet users to continuously update open and publicly available resources Land cover data based on satellite imagery
Data availability Worldwide provided Worldwide provided, although with different degrees of accuracy Data available for major urban cities in the European area
Time scale Depends on the Landsat satellites Continuously update Data prepared periodically, currently from 2006, 2012 and 2018
Responsible agency Landsat images available from the United States Geological Survey (USGS) Database maintained by the OpenStreetMap Foundation Project coordinated by the European Environment Agency (EEA)
Greenspace categories identified Greenspace were identified
with the use of supervised
classification based on the
representative samples for the
different green space types in the
digital image
– Allotments
– Cemetery
– Farmland/
– Forest/wood
– Garden
– Grassland
– Greenfield
– Greenhouse
– Meadow
– Nature reserve
– Orchard
– Park
– Plant nursery
– Scrub
– Trees
– Village green
– Wetland
– Green urban areas
(Code 14,100)
– Arable land (annual crops) (Code 21,000)
– Permanent crops (Code 22,000)
– Pastures (Code 23,000)
-Complex and mixed cultivation (Code 24,000)
– Forests (Code 30,000)
– Herbaceous vegetation associations (Code 32,000)
– Wetland (Code 40,000)
  1. *NDVI: Measurement of calculating the Normalized Difference Vegetation Index (NDVI) by analysising Landsat satellite images; OSM: the OpenStreetMap dataset; UA: the European Urban Atlas dataset