GHSL - Global Human Settlement Layer 全球人类居住层数据数据 #卫星数据资源# 欧盟的开放和免费的数据和工具全球栅格数据,包括建筑、人口和居住区数据原用了卫星数据、人口普查数据、提供GIS数据处理方式新的空间数据挖掘技术,进行自动处理,分析和知识提取提供不同投影、分辨率、时间数据链接:O网页链接 ...
The Global Human Settlement Layer (GHSL) has been developed by the European Commission Joint Research Centre. It contains fine-scale global and multitemporal geospatial data on populations and built-up areas. The GHSL opens the possibility to study all cities in a globally consistent and ...
While researching population visualizations, I came acrossthese chartsby Alasdair Rae that used the Global Human Settlement Layer (GHSL) data from 2016 to explore population. I was utterly blown away. GHSL combines baseline data on human presence on the planet’s surface using observations of buildi...
et al. Unveiling 25 years of planetary urbanization with remote sensing: perspectives from the global human settlement layer. Remote Sens 10, 768 (2018). Article Google Scholar Seltenrich, N. Remote-sensing applications for environmental health research. Environ. Health Perspect. 122, A268–A275...
Population data is obtained from the Global Human Settlement Layer (GHSL). This data repository aims to provide global, uniform, validated, and semantic information, analytics, and knowledge about the human occupation on the entire planet at a fine resolution43. Particularly, the population data is...
Till now, several Landsat-derived global ISA datasets have been produced, including: (1) Global Human Settlement Layer (GHSL) (Pesaresi et al., 2016), which was constructed by the Joint Research Centre of European Commission using symbolic machine learning methods with training data extracted from...
et al. A global human settlement layer from optical HR/VHR RS data: concept and first results. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 6, 2102–2131 (2013) ADS Google Scholar Pesarese, M. et al. Operating Procedure for the Production of the Global Human Settlement Layer ...
These conditions imply that some popular datasets such as Google Street View, WorldPop, and the Global Human Settlement Layer were omitted due to either proprietary or granularity reasons. Data retrieval is a non-trivial task given the size, scope, and diversity of data. To create a consistent ...
Utilizing mainland Southeast Asia as a testbed, LandScan was found to be superior in terms of spatial accuracy and estimated errors when compared with other world grid datasets such as Worldpop, Global Human Settlement Layer-Population, and the Gridded Population of the World43. To estimate the ...
Here, we used the NTL-derived urban extent time series data with an annual interval because other global urban extent data with finer spatial resolutions, such as the built-up maps of Global Human Settlement Layer (GHSL)60, are generally only available at coarse temporal resolutions. The NTL-...