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World Settlement Footprint (WSF) - Landsat-8/Sentinel-1 - Global, 2015

global, urbanization, land, settlement extent, Landsat-8, Sentinel-1

Map

Abstract:

The World Settlement Footprint WSF 2015 version 2 (WSF2015 v2) is a 10m resolution binary mask outlining the extent of human settlements globally for the year 2015. Specifically, the WSF2015 v2 is a pilot product generated by combining multiple datasets, namely:

  • The WSF2015 v1 derived at 10m spatial resolution by means of 2014-2015 multitemporal Landsat-8 and Sentinel-1 imagery (of which ~217K and ~107K scenes have been processed, respectively); Publication

  • The High Resolution Settlement Layer (HRSL) generated by the Connectivity Lab team at Facebook through the employment of 2016 DigitalGlobe VHR satellite imagery and publicly released at 30m spatial resolution for 214 countries; Publication

  • The novel WSF2019 v1 derived at 10m spatial resolution by means of 2019 multitemporal Sentinel-1 and Sentinel-2 imagery (of which ~ 1.2M and ~1.8M scenes have been processed, respectively); Publication

    • The WSF2015 v1 demonstrated to be highly accurate, outperforming all similar existing global layers; however, the use of Landsat imagery prevented a proper detection of very small structures, mostly due to their reduced scale. Based on an extensive qualitative assessment, wherever available the HRSL layer shows instead a systematic underestimation of larger settlements, whereas it proves particularly effective in identifying smaller clusters of buildings down to single houses, thanks to the employment of 2016 VHR imagery. The WSF2015v v2 has been then generated by: i) merging the WSF2015 v1 and HRSL (after resampling to 10m resolution and disregarding the population density information attached); and ii) masking the outcome by means of the WSF2019 product, which exhibits even higher detail and accuracy, also thanks to the use of Sentinel-2 data and the proper employment of state-of-the-art ancillary datasets (which allowed, for instance, to effectively mask out all roads globally from motorways to residential).

    Product Version: 2.0
    Coverage: global
    Resolution: 10 m x 10 m

    Attribution: WSF2015 version 2 Data are licensed under: Attribution 4.0 International (CC BY 4.0)

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    World Settlement Footprint (WSF) - Sentinel-1/Sentinel-2 - Global, 2019

    DLR, EOC, WSF, 2019, urbanization, land, global settlement extent, Sentinel-1, Sentinel-2, Copernicus

    Map

    Abstract:

    The World Settlement Footprint (WSF) 2019 is a 10m resolution binary mask outlining the extent of human settlements globally derived by means of 2019 multitemporal Sentinel-1 (S1) and Sentinel-2 (S2) imagery. Based on the hypothesis that settlements generally show a more stable behavior with respect to most land-cover classes, temporal statistics are calculated for both S1- and S2-based indices. In particular, a comprehensive analysis has been performed by exploiting a number of reference building outlines to identify the most suitable set of temporal features (ultimately including 6 from S1 and 25 from S2). Training points for the settlement and non-settlement class are then generated by thresholding specific features, which varies depending on the 30 climate types of the well-established Köppen Geiger scheme. Next, binary classification based on Random Forest is applied and, finally, a dedicated post-processing is performed where ancillary datasets are employed to further reduce omission and commission errors. Here, the whole classification process has been entirely carried out within the Google Earth Engine platform. To assess the high accuracy and reliability of the WSF2019, two independent crowd-sourcing-based validation exercises have been carried out with the support of Google and Mapswipe, respectively, where overall 1M reference labels have been collected based photointerpretation of very high-resolution optical imagery.

    The dataset is organized in 5138 GeoTIFF files (EPSG 4326 projection) each one referring to a portion of 2 x 2 degree size (~222 x 222 km) on the ground. Settlements are associated with value 255; all other pixels are associated with value 0.

    A comprehensive publication with all technical details and accuracy figures is currently being finalized. For the time being, please refer to Marconcini et al,. 2021 .

    General information:

    • Satellite: Sentinel-1, Sentinel-2
    • Period: 2019
    • Resolution: 10 x 10
    • Coverage: Global

    Download: HTTP download via EOC Download Service

    Related datasets:

    References:

    • Mattia Marconcini, Annekatrin Metz-Marconcini, Thomas Esch and Noel Gorelick. Understanding Current Trends in Global Urbanisation - The World Settlement Footprint Suite. GI_Forum 2021, Issue 1, 33-38 (2021) https://austriaca.at/0xc1aa5576%200x003c9b4c.pdf

    Attribution: WSF2019 data are licensed under: Attribution 4.0 International (CC BY 4.0)

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    World Settlement Footprint (WSF) Evolution

    global settlement growth, urbanization, land, Landsat-5, Landsat-7

    Map

    Abstract:

    The World Settlement Footprint (WSF) Evolution is a 30m resolution dataset outlining the global settlement extent on a yearly basis from 1985 to 2015. Based on the assumption that settlement growth occurred over time, all pixels categorized as non-settlement in the WSF2015 (Marconcini et al., 2020) are excluded a priori from the analysis. Next, for each target year in the past, all available Landsat-5/7 scenes acquired over the given area of interest are gathered and key temporal statistics (i.e., temporal mean, minimum, maximum, etc.) are then extracted for different spectral indices. Among others, these include: the normalized difference built-up index (NDBI), normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI). Temporal features proved generally robust if computed over at least 7 clear cloud-/cloud-shadow-free observations; accordingly, if for a given pixel in the target year this constraint is not satisfied, the time frame is enlarged backwards (at 1-year steps) as long as the condition is met.

    Starting backwards from the year 2015 - for which the WSF2015 is used as a reference - settlement and non-settlement training samples for the given target year t are iteratively extracted by applying morphological filtering to the settlement mask derived for the year t+1, as well as excluding potentially mislabeled samples by adaptively thresholding the temporal mean NDBI, MNDWI and NDVI. Finally, binary Random Forest classification in performed.

    To quantitatively assess the high accuracy and reliability of the dataset, an extensive campaign based on crowdsourcing photointerpretation of very high-resolution airborne and satellite historical imagery has been performed with the support of Google. In particular, for the years 1990, 1995, 2000, 2005, 2010 and 2015, ~200K reference cells of 30x30m size distributed over 100 sites around the world have been labelled, hence summing up to overall ~1.2M validation samples.

    It is worth noting that past Landsat-5/7 availability considerably varies across the world and over time. Independently from the implemented approach, this might then result in a lower quality of the final product where few/no scenes have been collected. Accordingly, to provide the users with a suitable and intuitive measure that accounts for the goodness of the Landsat imagery, we conceived the Input Data Consistency (IDC) score, which ranges from 6 to 1 with: 6) very good; 5) good; 4) fair; 3) moderate; 2) low; 1) very low. The IDC score is available on a yearly basis between 1985 and 2015 and supports a proper interpretation of the WSF evolution product.

    The WSF evolution and IDC score datasets are organized in 5138 GeoTIFF files (EPSG4326 projection) each one referring to a portion of 2 x 2 degree size (~222 x 222 km) on the ground. WSF evolution values range between 1985 and 2015 corresponding to the estimated year of settlement detection, whereas 0 is no data. A comprehensive publication with all technical details and accuracy figures is currently being finalized. For the time being, please refer to Marconcini et al,. 2021 .

    General information:

    • Satellite: Landsat 5, 7
    • Period: 1985 - 2015
    • Resolution: 30 x 30
    • Coverage: Global

    Related datasets:

    Download: HTTP download via EOC Download Service

    References:

    • Mattia Marconcini, Annekatrin Metz-Marconcini, Thomas Esch and Noel Gorelick. Understanding Current Trends in Global Urbanisation - The World Settlement Footprint Suite. GI_Forum 2021, Issue 1, 33-38 (2021) https://austriaca.at/0xc1aa5576%200x003c9b4c.pdf

    Attribution:WSF Evolution Data are licensed under: Attribution 4.0 International (CC BY 4.0)

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    World Settlement Footprint (WSF) 3D - Global, 90m

    DLR, EOC, WSF, 3D, building density, building height, building volume, urbanization, global, Sentinel-1, Sentinel-2, TanDEM-X

    Map

    Abstract:

    The World Settlement Footprint (WSF) 3D provides detailed quantification of the average height, total volume, total area and the fraction of buildings at 90 m resolution at a global scale.

    It is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery in combination with digital elevation data and radar imagery collected by the TanDEM-X mission. The framework includes three basic workflows: i) the estimation of the mean building height based on an analysis of height differences along potential building edges, ii) the determination of building fraction and total building area within each 90 m cell, and iii) the combination of the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. In addition, global height information on skyscrapers and high-rise buildings provided by the Emporis database is integrated into the processing framework, to improve the WSF 3D Building Height and subsequently the Building Volume Layer.

    A comprehensive validation campaign has been performed to assess the accuracy of the dataset quantitatively by using VHR 3D building models from 19 globally distributed regions (~86,000 km2) as reference data.

    The WSF 3D standard layers are provided in the format of Lempel-Ziv-Welch (LZW)-compressed GeoTiff files, with each file - or image tile - covering an area of 1 x 1 ° geographical lat/lon at a geometric resolution of 2.8 arcsec (~ 90 m at the equator). Following the system established by the TDX-DEM mission, the latitude resolution is decreased in multiple steps when moving towards the poles to compensate for the reduced circumference of the Earth.

    Click here to access the 3D viewer of the WSF 3D data

    Product Information:
    • Product Name: World Settlement Footprint (WSF) 3D - Global, 90m
    • Release: 2023-02-15
    • Contact: WSF Team, Thomas Esch

    Data Information:
    • Satellite: TanDEM-X, Sentinel-1, Sentinel-2
    • Format: Cloud Optimized GeoTIFF
    • Spatial Resolution: 90 x 90 m
    • Period: 2012 (TanDEM-X) - 2019 (WSF)
    • Coverage: Global
    • License: CC BY 4.0

    Data:

    References:

    DLR © 2023

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    World Settlement Footprint® (WSF) 3D - Material Stock

    DLR, EOC, WSF, 3D, building material, building volume, material stock, material Flow Analysis, Industrial Ecology, urbanization, global

    Map

    Abstract:

    Buildings provide indispensable services for human wellbeing, but their construction and use are responsible for a substantial fraction of societies’ resource requirements and greenhouse gas emissions. Mapping and quantifying the material stocks in buildings is a key research frontier in Industrial Ecology. Reliable and spatially highly resolved maps of material stocks in buildings world-wide are so far not available. Existing approaches based on nighttime light data allow large-scale coverage, but their spatial resolution is usually ~0.5-1 km. Other methods using light detection and ranging (LiDAR) and cadaster data achieve higher resolution and accuracy, but do not allow wall-to-wall mapping of large regions. Based on high-resolution Earth Observation data combined with material intensity factors (kg per m3 of building volume), we here quantify and map material stocks in buildings at the unprecedented resolution of 90 m globally. We distinguish 18 types of materials in five types of buildings. We find that global material stocks in buildings amount to 547 (391-672) Gt, approximately half of total global societal material stocks. We find highly unequal distributions of material stocks in buildings per capita and per unit area of each country. Our results agree well with previous detailed estimates of material stocks in buildings in dedicated regions or individual cities. Improved and harmonized material intensity factors emerge as a key research area for improving the accuracy of material stock maps. Our results are available as data products with high spatial and thematic resolution to facilitate future studies; e.g., of secondary resource potentials.

    Product Information:
    • Product Name: World Settlement Footprint (WSF) 3D - Material Stock
    • Release: 2024-03-25
    • Contact: WSF Team, Thomas Esch

    Data Information:
    • Format: Cloud Optimized GeoTIFF
    • Spatial Resolution: 90 x 90 m
    • Period: 2012 (TanDEM-X) - 2019 (WSF)
    • Coverage: Global
    • Input Data: WSF3D Volume Height and Area, GHS-BUILT-S R2023A
    • License: CC BY 4.0

    Data:

    References:
    • Haberl,H., Baumgart,A., Zeidler, J., Schug, F., Frantz, D. , Palacios-Lopez, D., Fishman, T., Peled, Y., Cai, B., Virág,D., Hostert, P., Wiedenhofer, D., Esch T. (2024): Weighing the Global Built Environment: High Resolution Mapping and Quantification of Material Stocks in Buildings. Journal of Industrial Ecology

    DLR © 2024

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