This dataset features a map of building fractions (as opposed to built-up fractions including other impervious surfaces such as roads) for Germany on a 10m grid based on Sentinel-1A/B and Sentinel-2A/B time series. The data were created by using machine learning regression and spectral unmixing, using synthetically mixed training data. The dataset is completely based on freely accessible satellite imagery, and was validated with freely available building footprint reference data for three federal states. We recommend to use data at an aggregated resolution of 20m, 50m, or 100m, and to clip data at about 20% building fraction when using 10m resolution maps (or roughly the corresponding RMSE at any other resolution). Temporal extent Used Se...
Gridded population data is widely used to map fine scale population patterns and dynamics to underst...
The dynamics of societal material stocks such as buildings and infrastructures and their spatial pat...
Knowledge of the German building stock is largely based on census data and annual construction stati...
Urban areas have a manifold and far-reaching impact on our environment, and the three-dimensional st...
Abstract The identification of buildings has become a major research focus of settlement mapping wi...
Abstract Urban areas and their vertical characteristics have a manifold and far-reaching impact on ...
This dataset features a map of building types for Germany on a 10m grid based on Sentinel-1A/B and S...
Mapping urban areas with remote sensing is particularly challenging due to the spatial spectral hete...
The increasing impact of humans on land and ongoing global population growth requires an improved un...
This is a cross-link to an existing PANGAEA datasaet: https://doi.org/10.1594/PANGAEA.920894 This m...
Abstract The increasing impact of humans on land and ongoing global population growth requires an i...
This dataset features three gridded population dadasets of Germany on a 10m grid. The units are peop...
Urban agglomerations play a key role in giving shelter to the growing world population. Mapping the ...
Abstract Gridded population data is widely used to map fine scale population patterns and dynamics ...
Gridded population data is widely used to map fine scale population patterns and dynamics to underst...
Gridded population data is widely used to map fine scale population patterns and dynamics to underst...
The dynamics of societal material stocks such as buildings and infrastructures and their spatial pat...
Knowledge of the German building stock is largely based on census data and annual construction stati...
Urban areas have a manifold and far-reaching impact on our environment, and the three-dimensional st...
Abstract The identification of buildings has become a major research focus of settlement mapping wi...
Abstract Urban areas and their vertical characteristics have a manifold and far-reaching impact on ...
This dataset features a map of building types for Germany on a 10m grid based on Sentinel-1A/B and S...
Mapping urban areas with remote sensing is particularly challenging due to the spatial spectral hete...
The increasing impact of humans on land and ongoing global population growth requires an improved un...
This is a cross-link to an existing PANGAEA datasaet: https://doi.org/10.1594/PANGAEA.920894 This m...
Abstract The increasing impact of humans on land and ongoing global population growth requires an i...
This dataset features three gridded population dadasets of Germany on a 10m grid. The units are peop...
Urban agglomerations play a key role in giving shelter to the growing world population. Mapping the ...
Abstract Gridded population data is widely used to map fine scale population patterns and dynamics ...
Gridded population data is widely used to map fine scale population patterns and dynamics to underst...
Gridded population data is widely used to map fine scale population patterns and dynamics to underst...
The dynamics of societal material stocks such as buildings and infrastructures and their spatial pat...
Knowledge of the German building stock is largely based on census data and annual construction stati...