GHS-BUILT R2015B - GHS built-up datamask grid, derived from Landsat, multitemporal (1975, 1990, 2000, 2014) - OBSOLETE RELEASE

Collection: GHSL : Global Human Settlement Layer 


OBSOLETE RELEASE Get the latest release at

The Global Human Settlement Layer (GHSL) project is supported by European Commission, Joint Research Center and Directorate-General for Regional and Urban Policy. The GHSL produces new global spatial information, evidence-based analytics, and knowledge describing the human presence in the planet.

The GHSL relies on the design and implementation of new spatial data mining technologies allowing to process automatically and extract analytics and knowledge from large amount of heterogeneous data including: global, fine-scale satellite image data streams, census data, and crowd sources or volunteering geographic information sources. Spatial data reporting objectively and systematically about the presence of population and built-up infrastructures are necessary for any evidence-based modelling or assessing of i) human and physical exposure to threats as environmental contamination and degradation, natural disasters and conflicts, ii) impact of human activities on ecosystems, and iii) access to resources.

This dataset contains a data mask layer that supports the main product, i.e., the multitemporal information layer on bulit-up presence derived from Landsat image collections (GLS1975, GLS1990, GLS2000, and ad-hoc Landsat 8 collection 2013/2014). The data have been produced by means of Global Human Settlement Layer methodology in 2015.

Similarly to the main product, it is published in the production grid at high resolution, i.e. at around 38m

in Spherical Mercator (EPSG:3857).


jrc-ghsl-data (at)


How to cite

Pesaresi, Martino; Ehrlich, Daniele; Florczyk, Aneta; Freire, Sergio; Julea, Andreea; Kemper, Thomas; Soille, Pierre; Syrris, Vasileios (2015): GHS-BUILT R2015B - GHS built-up datamask grid, derived from Landsat, multitemporal (1975, 1990, 2000, 2014) - OBSOLETE RELEASE. European Commission, Joint Research Centre (JRC) [Dataset] PID:


global map Landsat built-up density remote sensing GHS-BUILT Datamask GHSL

Data access

  • The data are offered as a grid, which has been produced at high resolution ,approx. 38m in Spherical mercator. The dataset is distributed in a compressed ZIP, that contains TIF file with pyramids and documentation.

GHSL website
Access conditions
No limitations 
  • Project Web site

GHSL Data Packages. Instructions for data access. V1.0


Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014
Pesaresi M, Ehrlich D, Ferri S, Florczyk A, Carneiro Freire S, Halkia S, Julea A, Kemper T, Soille P, Syrris V. Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014. EUR 27741. Luxembourg (Luxembourg): Publications Office of the European Union; 2016. JRC97705
  • Publications Office of the European Union, Luxembourg, Luxembourg
Publication page 
  • Abstract

    A new global information baseline describing the spatial evolution of the human settlements in the past 40 years is presented. It is the most spatially global detailed data available today dedicated to human settlements, and it shows the greatest temporal depth. The core processing methodology relies on a new supervised classification paradigm based on symbolic machine learning.

    The information is extracted from Landsat image records organized in four collections corresponding to the epochs 1975, 1990, 2000, and 2014. The experiment reported here is the first known attempt to exploit global Multispectral Scanner data for historical land cover assessment. As primary goal, the Landsat-made Global Human Settlement Layer (GHSL) reports about the presence of built-up areas in the different epochs at the spatial resolution allowed by the Landsat sensor. Preliminary tests confirm that the quality of the information on built-up areas delivered by GHSL is better than other available global information layers extracted by automatic processing from Earth Observation data. An experimental multiple-class land-cover product is also produced from the epoch 2014 collection using low-resolution space-derived products as training set. The classification schema of the settlement distinguishes built-up areas based on vegetation contents and volume of buildings, the latter estimated from integration of SRTM and ASTER-GDEM data. On the overall, the experiment demonstrated a step forward in production of land cover information from global fine-scale satellite data using automatic and reproducible methodology.

Geographic areas


Temporal coverage

From date To date
1975-01-01 2014-12-30

Additional information

Published by
European Commission, Joint Research Centre
Created date
Modified date
Issued date
Landing page 
Data theme(s)
Regions and cities, Science and technology
Update frequency