Exploring energy geography: Data insights on household consumption

Household energy consumption (HEC) varies across neighbourhoods and gender groups. This database provides raw and analysed data on HEC determinants and their estimated influence on HEC in 2707 residential neighbourhoods (Wijk) in the Netherlands in 2018. The raw data consists of 17 indicators on energy demand, socioeconomic characteristics, microclimate and buildings. The indicators are retrieved from and calculated based on open national and international datasets. The analysed data presents the local coefficients of the HEC determinants, the outcome of the geographically weighted regression model (GWR) presented in the related article [1].

Mobility, electricity, and parking data for EV infrastructure in the Amsterdam Metropolitan Area

The dataset combines and aggregate five data types of the Amsterdam Metropolitan Area in a polygon GIS shapefile with 79 three-digit postcode areas, and a csv file, including the outcome of an origin-destination analysis. The dataset area includes 1661 residential zones (“wijken”, in the terminology used by the Dutch Central Bureau for Statistics) of the Amsterdam Metropolitan Area (AMA), and the data aggregated was originally generated between 2017 and 2019. The first dataset, in format of GIS shapefile, contains data on mobility, parking capacity, electricity demand, census data and cadaster data. The second dataset, csv format, includes the outcomes of an origin-destination analysis between the 79 three-digit postcodes areas in AMA. The two datasets provide the basis for analysis and adaptation of electric mobility in AMA.

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 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 (%).

Spatializing household energy consumption in the Netherlands: Socioeconomic, urban morphology, microclimate, land surface temperature and vegetation data

Household energy consumption (HEC) is affected by a variety of determinants. In addition to the level of HEC in 2612 residential zones in the Netherlands (the so-called wijk) in 2014, this dataset provides a geographically-referenced data of 11 determinants of HEC on: (1) socioeconomic characteristics - namely income per capita, household size, population density; (2) urban morphology -namely buildings' surface to volume ratio, building age; (3) microclimate factors -namely number of summer days, number of frost days, humidity, wind speed at 10 m height; (4) land surface temperature; (5) normalized difference vegetation index (NDVI). The dataset is initially prepared for an analysis titled as "Land surface temperature and households' energy consumption: who is affected and where?" [1].

Airport location in European airport regions: Five typologies based on the regional road network and land use data

Describing the location of an airport within a region, the vocabulary of urban studies is often dominated by ill-defined terms such as urban fringe, centre, suburb, corridors, etc. The dataset presented by this manuscript aims to provide a basis to describe and compare the location of 76 major European airports within their respective urban regions. The dataset consists of seven types of data: Betweenness centrality of major roads at 45 km radius of each airport region, population density, distribution of urbanized areas, location of agricultural lands, location of the natural area, and distribution of leisure and industrial sites. Ultimately, employing hierarchical clustering, five typologies of the European airport regions, given the regional location of airport, are identified: (1) Urban airports; (2) Urban periphery airports; (3) Agricultural-area airports; (4) Natural-area airports; (5) Remote airports.