URBAN GROWTH SCENARIOS OF A FUTURE MEGA CITY: CASE STUDY AHMEDABAD

The study of urban areas and their development focuses on cities, their physical and demographic expansion and the tensions and impacts that go along with urban growth. Especially in developing countries and emerging national economies like India, consistent and up to date information or other planning relevant data all too often is not available. With its Smart Cities Mission, the Indian government places great importance on the future developments of Indian urban areas and pays tribute to the large-scale rural to urban migration. The potentials of urban remote sensing and its contribution to urban planning are discussed and related to the Indian Smart Cities Mission. A case study is presented showing urban remote sensing based information products for the city of Ahmedabad. Resulting urban growth scenarios are presented, hotspots identified and future action alternatives proposed

GROWTH SCENARIOS FOR THE CITY OF GUANGZHOU, CHINA: TRANSFERABILITY AND CONFIRMABILITY

This work deals with the development of urban growth scenarios and the prevision of the spatial distribution of built-up area and population for the urban area of the city of Guangzhou in China. Using freely-available data, including remotely sensed data as well as census data from the ground, expenditure of time and costs shall remain low. Guangzhou, one of the biggest cities within the Pearl River Delta, has faced an enormous economic and urban growth during the last three decades. Due to its economical and spatial characteristics it is a promising candidate for urban growth scenarios. The monitoring and prediction of urban growth comprises data of population and give them a spatial representation. The model, originally applied for the Indian city Ahmedabad, is used for urban growth scenarios. Therefore, transferability and confirmability of the model are evaluated. Challenges that may occur by transferring a model for urban growth from one region to another are discussed. With proposing the use of urban remote sensing and freely available data, urban planners shall be fitted with a comprehensible and simple tool to be able to contribute to the future challenge Smart Growth

Temporal aspects in the development of a cascading-event crisis scenario: a pilot demonstration of the CRISMA project

In this abstract we illustrate the various temporal aspects to be considered in a multi-hazard crisis scenario set up as pilot study in the EU-FP7 Integrated Project CRISMA. In the framework of CRISMA a simulation-based decision support system for crisis management is developed facilitating the modeling of realistic crisis scenarios, related pre-event vulnerabilities, as well as possible response actions and associated varying potential impacts on society. Both external factors driving crisis development and actions of the involved crisis management team are considered in the system setup

Zur radiometrischen Reliefkorrektur von Fernerkundungsdaten

ZusammenfassungBei der Auswertung von Fernerkundungsdaten ist es für verschiedeneAufgabenstellungen notwendig, reliefbedingte radiometrische Verzerrungenzu korrigieren. Komplexe bzw. physikalisch basierte Korrekturansätzekönnen i.d.R. nur mit Kenntnissen über die Landoberfläche wie z.B.Landbedeckung, Boden, Vegetation etc. angewendet werden. Diese Informationensind jedoch häufig das eigentliche Ziel der inhaltlichen Datenauswertungund stehen für den Vorverarbeitungsschritt nur begrenzt zur Verfügung.Mögliche Ansätze zur Lösung dieses Problems ergeben sich durch statistischeVerfahren (z.B. Hauptkomponentenanalyse) oder durch eine Segmentierung desFernerkundungsbildes in thematische Bereiche mit ähnlichen,einfallswinkel-abhängigen Reflexionscharakteristika. In den sodiskretisierten Bereichen ist die Anwendung angepasster Korrekturmodellemöglich, die lediglich den lokalen Einfallswinkel als Geländeparameterbenötigen. In drei anwendungsbezogenen Studien wird aufgezeigt, daß sowohlmit der Minnaert-Korrektur für optische Daten (Landsat-5 TM) als auch miteinem erweiterten Kosinusmodell für E-SAR Daten sowie derHauptkomponentenanalyse für ERS-1/2 SAR Daten eine erfolgreicheReliefkorrektur erzielt und damit eine topographische Normalisierungverwirklicht werden konnte.SummaryA contribution to the radiometric correction of topographically inducedillumination variation in remote sensing imagery.In several fields of application preprocessing of remote sensing datarequires the correction of topographically induced illumination variation.Physically based correction methods can only be applied having a prioriinformation of surface properties like e.g. land cover, soils, vegetationetc. However, the acquisition of this surface information is often theactual objective of the respective study, and therefore it is not availablefor the preprocessing steps of the remote sensing data.This problem can be solved by applying statistical methods(i.e. principle component analysis), or by the segmentation of image bandsinto several surface types showing similar reflection characteristicsdetermined by the incidence angle of the illumination source. Those areascan then be corrected by applying adapted correction models which requireonly the incidence angle as input parameter. Three application studies showthe effective topographic normalisation of spaceborne Landsat-5 TM data(Minnaert correction) and ERS-1/2 SAR data (principal component analysis)as well as of airborne E-SAR data (modified cosine correction)

Estimating urban population patterns from stereo-satellite imagery

With more than half of the world’s population living in towns and cities, urban areas get more and more into the focus of humanitarian relief organisations such as ICRC, Médecins sans Frontières (MSF), or SOS Children’s Villages. A key information required for almost any intervention is an estimation of the population numbers for the towns and cities where these organisations operate in. As census data are usually not available or outdated, population numbers have to be estimated by alternative methods such as remote sensing. To do that built-up densities are estimated from high-resolution image data and population numbers are disaggregated proportional to the densities in a top-down approach. Alternatively, population counts per density unit can be aggregated following a bottom-up approach. Both approaches were tested applying normalised Digital Surface Models (nDSM) derived from tri-stereo Pléiade images for Salzburg, Austria and Port-au-Prince, Haiti; the former for testing the quality and stability of the approach in a well-known setting, the latter for testing the approach in a critical environment. Key findings are that satellite-derived nDSMs provide sufficient accuracy for estimating population distributions, as long as reliable information is available for the separation of residential and non-residential urban areas