AI-generated Key Takeaways
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The Global Human Settlement Layer (GHSL) provides datasets characterizing human settlements, including building heights and built-up surfaces, at resolutions ranging from 10m to 100m.
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GHSL data utilizes various sources like ALOS, SRTM, and Sentinel-2 imagery to model built environments and their functional components.
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Built-up surface datasets within GHSL offer insights into total and non-residential built areas, spanning multiple years and resolutions.
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The Tsinghua FROM-GLC dataset provides insights into annual impervious surface changes globally from 1985 to 2018 at a 30m resolution.
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GHSL: Global building height 2018 (P2023A)
This spatial raster dataset depicts the global distribution of building heights at a resolution of 100 m, referred to the year 2018. The input data used to predict building heights are the ALOS Global Digital Surface Model (30 m), the NASA Shuttle Radar Topographic Mission … alos building built built-environment builtup copernicus -
GHSL: Global built-up surface 10m (P2023A)
This raster dataset depicts the distribution of built-up surfaces, expressed in square metres per 10 m grid cell, for 2018 as observed from the S2 image data. The datasets measure: a) the total built-up surface, and b) the built-up surface allocated to grid cells of … built built-environment builtup copernicus ghsl jrc -
GHSL: Global built-up surface 1975-2030 (P2023A)
This raster dataset depicts the distribution of built-up surfaces, expressed in square metres per 100 m grid cell. The dataset measures: a) the total built-up surface, and b) the built-up surface allocated to grid cells of predominant non-residential (NRES) use. Data are spatially-temporally interpolated or … built built-environment builtup copernicus ghsl jrc -
GHSL: Global settlement characteristics (10 m) 2018 (P2023A)
This spatial raster dataset delineates human settlements at 10 m resolution, and describes their inner characteristics in terms of the functional and height-related components of the built environment. More information about the GHSL data products can be found in the GHSL Data Package 2023 report … building built builtup copernicus ghsl height -
Tsinghua FROM-GLC Year of Change to Impervious Surface
This dataset contains annual change information of global impervious surface area from 1985 to 2018 at a 30m resolution. Change from pervious to impervious was determined using a combined approach of supervised classification and temporal consistency checking. Impervious pixels are defined as above 50% impervious. … built population tsinghua urban