Summer surface temperature and socioeconomic data of Dutch residential zones, 2014
The dataset combines and aggregates two data types at the scale of 2400 residential zones (“wijken”, in the terminology used by the Dutch Central Bureau for Statistics) of the Netherlands, 2014. The first type of data is summer surface temperature, the average of 40 dates in the summer of 2014, comprising the observations of four satellite images of four local overpassing times: MODIS Terra day (10:30 a.m.), MODIS Terra night (10:30 p.m.), MODIS Aqua day (1:30 p.m.), and MODIS Aqua night (1:30 a.m.). Second, ten variables describing the socioeconomic status of the residential zones: Western im... Mehr ...
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Dokumenttyp: | article/Letter to editor |
Erscheinungsdatum: | 2021 |
Schlagwörter: | Climate adaptation / Climate justice / Environmental justice / Land surface temperature / Socioeconomic geography / Summer surface temperature / Urban heat island |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27458541 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://research.wur.nl/en/publications/summer-surface-temperature-and-socioeconomic-data-of-dutch-reside |
The dataset combines and aggregates two data types at the scale of 2400 residential zones (“wijken”, in the terminology used by the Dutch Central Bureau for Statistics) of the Netherlands, 2014. The first type of data is summer surface temperature, the average of 40 dates in the summer of 2014, comprising the observations of four satellite images of four local overpassing times: MODIS Terra day (10:30 a.m.), MODIS Terra night (10:30 p.m.), MODIS Aqua day (1:30 p.m.), and MODIS Aqua night (1:30 a.m.). Second, ten variables describing the socioeconomic status of the residential zones: Western immigrants (%), Non-Western immigrants (%), Rental dwelling (%), Building age (median), Population age 65 or older (%), Population age 15-24 (%), Population age 14 or younger (%), Income per capita (x 1000 €), Property value (x 1000 €), Female minus male (%).