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Modeling Population Distribution Based on EO-Derived Data on the Built-Environment

Voinov, Sergey (2014) Modeling Population Distribution Based on EO-Derived Data on the Built-Environment. Master's, Hochschule für Technik Stuttgart.

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Abstract

Last years, German Aerospace Center (DLR) made very big step forward in the context of global urban mapping. TanDEM-X mission, utilizing TerraSAR-X and TanDEM-X satellites, made it possible to derive very high resolution built-environment raster products – e.g., the Global Urban Footprint (GUF) settlement mask (Esch et al., 2013). The goal of this master thesis project is to investigate the potential to model the human population distributions based on a combination of the above mentioned Global Urban Footprint product, statistical census data and – optionally - additional land cover maps (e.g., CORINE Land Cover). Resulting layers on the spatial distribution of population – once provided on global level - would be highly beneficial for sustainable spatial and environmental planning, land management as well as policy. To conduct the study, algorithms were implemented as a tool for ArcGIS that were based on spatial/areal weighting and dasymetric mapping technics. In general, this includes the spatial disaggregating of information (Sleeter, 2004). By comparing with officially available numbers, the results of evaluation showed good enough accuracy for the test area, namely Federal State of Bavaria. Further modifications and developments of this project are possible.

Item URL in elib:https://elib.dlr.de/97361/
Document Type:Thesis (Master's)
Title:Modeling Population Distribution Based on EO-Derived Data on the Built-Environment
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Voinov, Sergeysergey.voinov (at) dlr.deUNSPECIFIED
Date:March 2014
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:43
Status:Published
Keywords:GIS, population grids, dasymetric mapping, urban mapping
Institution:Hochschule für Technik Stuttgart
Department:Faculty Geomatics, Computer Science und Mathematics
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Fernerkundung der Landoberfläche (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Voinov, Sergey
Deposited On:21 Jul 2015 14:42
Last Modified:31 Jul 2019 19:54

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