Gridded population maps of Germany from disaggregated census data and bottom-up estimates

This dataset features three gridded population dadasets of Germany on a 10m grid. The units are people per grid cell.

Datasets

DE_POP_VOLADJ16: This dataset was produced by disaggregating national census counts to 10m grid cells based on a weighted dasymetric mapping approach. A building density, building height and building type dataset were used as underlying covariates, with an adjusted volume for multi-family residential buildings.

DE_POP_TDBP: This dataset is considered a best product, based on a dasymetric mapping approach that disaggregated municipal census counts to 10m grid cells using the same three underyling covariate layers.

DE_POP_BU: This dataset is based on a bottom-up gridded population estimate. A building density, building height and building type layer were used to compute a living floor area dataset in a 10m grid. Using federal statistics on the average living floor are per capita, this bottom-up estimate was created.

Please refer to the related publication for details.

Temporal extent

The building density layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: http://doi.org/10.1594/PANGAEA.920894)

The building height layer is representative for ca. 2015 (doi: 10.5281/zenodo.4066295)

The building types layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: 10.5281/zenodo.4601219)

The underlying census data is from 2018.

Data format

The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems.

Further information

For further information, please see the publication or contact Franz Schug ([e-mail]).
A web-visualization of this dataset is available here.

Publication

Schug, F., Frantz, D., van der Linden, S., & Hostert, P. (2021). Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates. PLOS ONE. DOI: 10.1371/journal.pone.0249044

Acknowledgements

Census data were provided by the German Federal Statistical Offices.

Funding
This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

本数据集包含三套德国10米分辨率栅格人口数据集，栅格单元的统计单位为人口数。

## 数据集
DE_POP_VOLADJ16：本数据集通过加权分区密度制图法（dasymetric mapping），将全国人口普查数据细化至10米分辨率栅格单元。研究采用建筑密度、建筑高度及建筑类型数据集作为基础协变量，并对多户住宅建筑的体积进行了调整。

DE_POP_TDBP：该数据集被认定为最优产品，基于分区密度制图法，采用与上述一致的三类基础协变量图层，将市级人口普查数据细化至10米分辨率栅格单元。

DE_POP_BU：本数据集采用自下而上的栅格人口估算方法。首先基于建筑密度、建筑高度及建筑类型图层，计算得到10米分辨率的居住建筑面积数据集；随后结合联邦层面的人均居住建筑面积统计数据，生成该自下而上的人口估算结果。

详细信息请参阅相关研究论文。

## 时间范围
建筑密度图层基于2018年Sentinel-2时序数据与2017年Sentinel-1时序数据（DOI：http://doi.org/10.1594/PANGAEA.920894）。
建筑高度图层的时间代表性约为2015年（DOI：10.5281/zenodo.4066295）。
建筑类型图层基于2018年Sentinel-2时序数据与2017年Sentinel-1时序数据（DOI：10.5281/zenodo.4601219）。
基础人口普查数据源自2018年。

## 数据格式
本数据集以30×30km的瓦片形式存储（详见配套形状文件（shapefile）），投影坐标系为EPSG:3035，数据格式为压缩GeoTIFF文件（*.tif）。此外还提供了GDAL虚拟格式的镶嵌文件（*.vrt），可在绝大多数地理信息系统软件中直接打开。

## 补充信息
如需获取更多信息，请参阅相关研究论文，或联系Franz Schug（邮箱：[e-mail]）。本数据集提供网页可视化工具，链接如下。

## 发表论文
Schug, F., Frantz, D., van der Linden, S., & Hostert, P. (2021). 基于地球观测数据获取的建筑密度、高度与类型信息，结合人口普查数据汇交及自下而上估算方法的德国栅格人口制图. PLOS ONE. DOI: 10.1371/journal.pone.0249044

## 致谢
本数据集的人口普查数据由德国联邦统计办公室提供。

## 资助信息
本数据集的制作得到了欧洲研究理事会（ERC）在欧盟“地平线2020”研究与创新计划下的资助（项目名称：MAT_STOCKS，协议编号：741950）。