Details zur Publikation
|DOI / URL||Link|
|Volltext||Publikationsdokument einer UFZ-Veröffentlichung|
|Titel (primär)||Remote sensing based derivation of urban structure types to assess hydro-meteorological impacts in highly dynamic urban agglomerations in Latin America|
|Journal / Serie||PhD Dissertation|
|POF III (gesamt)||T11;|
|Keywords||Brasilien; Chile; Lateinamerika; Geoinformationssystem; Lufttemperatur; Oberflächentemperatur; Fernerkundung; Satellitenbild|
|UFZ Bestand||Leipzig, Bibliothek, Reportsammlung, 00501033, 15-0341 F/E|
|Abstract||The proportion of the population living in urban areas is increasing
worldwide. It is expected to achieve 60% (4.9 billion) by 2030. The
growth goes along with a lack of inner urban density and a continuous
spread into the suburban regions. Hence, the increasing amount of
impervious surface and the loss of green spaces affect temperature
distributions, runoff, and infiltration rates. Further on, the number
and intensity of natural and man-made hazards increased over the last
decades. Urban areas are in general more sensitive to these hazards due
to the high concentration of people and infrastructure.
Due to the high dynamics of urban growth and urbanization, a great part of maps, population statistics, and conventional sources of information are outdated within a very short time or in some cases not available at all. In any case, an intensive observation, monitoring, and forecasting is required according to the characteristics of cities with a high population density. Remote sensing (RS) offers information with a high temporal resolution and presents a cost effective alternative for the mapping of environmental parameters (micro- climate, heat islands, access to open space) and the monitoring of urban growth.
The objective of this study is to enhance the knowledge on the opportunities remote sensing data offer for the monitoring of urban areas and the assessment of hazard generation and exposure. This study concentrates on different aspects of the risk concept (hazard and exposure), emphasizing the opportunities of remote sensing data at different scales to support the risk assessment process. Therefore, the concept of Urban Structure Types (UST) is applied. The UST approach divides and classifies the urban area into homogeneous regions which can be related to various issues. UST can be classified using very high resolution Quickbird data in an object-based image analysis approach. The results are subsequently related to different socio-economic and socio-demographic data sets.
Two case study areas are used for the analysis of the hazard and hazard generation side of the risk concept including the identification of hazard-prone areas for heat (Santiago de Chile) and areas as sources of surface water contamination (Planaltina, Distrito Federal do Brasil). For Santiago de Chile, the UST concept was used to analyze the urban built-up in order to identify heat hazard-prone areas and characteristics of the local population.
Hazard-prone areas for heat are identified using air and surface temperature data. They are compared and afterwards related to the UST classified before. A logistic regression is used to demonstrate a significant influence of UST on hazard-prone areas. On the vulnerability and exposure side of the risk concept, UST are related to census data. The results demonstrate that different variables are well represented by UST. They were used further on to derive exposure maps. The information derived from UST can support a risk analysis at different stages. However, additional environmental and person-specific data of the inhabitants have to be taken into account.
The potential of UST in an IWRM context was demonstrated in a case study on Planaltina, Distrito Federal do Brasil. The same input data set as in the case study on Santiago de Chile was used to classify UST. However, in the case of Planaltina, Distrito Federal do Brasil, the UST are related to water-relevant information from different input data to identify possible sources of contamination of surface water caused by domestic pollution. In the further analysis, the results are used to emphasize the advantages of the spatial and temporal resolution of UST in a risk assessment. Although UST may show a lower level of detail compared to census information, the information is area-wide available and up-to-date and can support local decision makers.
The potentials and limitations of UST concerning the monitoring of urban areas and a hazard and exposure assessment were demonstrated in general. The influences of scale effects on the hazard and exposure analysis using different input data as well as the relation between UST and socio-economic variables from census data were pointed out. The results showed the applicability of UST as input proxy indicators for the hazard and exposure analysis. However, a full risk assessment and / or vulnerability analysis would require further information e. g. derived by field studies.
A prediction of the location and size of hazard-prone areas and the subsequent monitoring of these areas is necessary to raise the awareness among the local population and provide decision makers with suitable information. The results of the present research show that UST and RS data can support the process of disaster preparedness and planning.
|Höfer, R. (2013):
Remote sensing based derivation of urban structure types to assess hydro-meteorological impacts in highly dynamic urban agglomerations in Latin America
PhD Dissertation 6/2013
Helmholtz-Zentrum für Umweltforschung - UFZ, Leipzig, 208 pp.