Global Urban Footprint (GUF) by DLR (Thomas Esch) for Italy to Croatia.
The Global Urban Footprint by DLR (Thomas Esch) has been released and provides a global coverage of urbanized areas. Previous versions of this data set has already been used by ongoing research in our department and we will now update the data for our scientific work. It is a great source for mapping human impact on a global scale. From the DLR website: Currently, more than half of the world’s population are urban dwellers and this number is still rapidly increasing. Since settlements – and urban areas in particular – represent the centers of human activity, the environmental, economic, political, societal and cultural impacts of urbanization are far-reaching. They include negative aspects like the loss of natural habitats, biodiversity and fertile soils, climate impacts, waste, pollution, crime, social conflicts or transportation and traffic problems, making urbanization to one of the most pressing global challenges. Accordingly, a profound understanding of the global spatial distribution and evolution of human settlements constitutes a key element in envisaging strategies to assure sustainable development of urban and rural settlements.
In this framework, the objective of the “Global Urban Footprint” (GUF) project is the worldwide mapping of settlements with unprecedented spatial resolution of 0.4 arcsec (~12 m). A total of 180 000 TerraSAR-X and TanDEM-X scenes have been processed to create the GUF. The resulting map shows the Earth in three colors only: black for “urban areas”, white for “land surface” and grey for “water”. This reduction emphasizes the settlement patterns and allows for the analysis of urban structures, and hence the proportion of settled areas, the regional population distribution and the arrangement of rural and urban areas. More details at: www.dlr.de/guf
Further data portals and visualizations are available here:
Via U-TEP Website: https://urban-tep.eo.esa.int
U-TEP Geobrowser: https://urban-tep.eo.esa.int/geobrowser/?id=guf
and a ESA GUF article: http://www.esa.int/Our_Activities/Observing_the_Earth/New_map_offers_precise_snapshot_of_human_life_on_Earth
Tobias Sieg submitted his MSc thesis “The potential of interferometric and polarimetric SAR data to characterize urban areas at the example of Mumbai and Manila” successfully and started with his PhD soon after. The thesis has been conducted in close cooperation with the DLR-EOC (Schmidt, Taubenböck) within the Global Change Ecology MSc study program. A publication is aimed at and is planned to be submitted within the end of this year. The studies, conducted in the course of this thesis, prove the feasibility of interferometric and polarimetric SAR data to separate between urban areas with different apparent structures. Further studies should aim for investigating an improvement of this separation and its reliability e.g. by means of polarimetric SAR data with an even higher spatial resolution or the use of enhanced TanDEM-X datasets. However, the use of SAR products with a spatial resolution lower than 2 meters is very limited. Furthermore, this thesis proves the suitability of the framework of the Kennaugh elements and the Schmittlet coefficients to characterize and separate urban areas. Especially the use of the Schmittlet coefficients to assess structures of cities in the future is highly recommended. Also, the use of nDSM data in conjunction with the Schmittlet coefficients is proved to increase the separability between building areas with different building heights tremendously. Once these results are further approved by the application of better suited datasets and the conduction of the methods to a few more cities, they could potentially serve as an helpful source of information for many other studies dealing with urban environments. For example, the results of the area-wide separability of chapter 4 could serve as an pre-classification to detect informal settlements, which could be helpful for urban planners. Also with regard to urban climate, information about the height and the structure or density can help to improve urban climate models. The estimation of the number of inhabitants of a city could benefit from a reliable pre-classification.
The publication by our former MSc student Sadroddin Alavipanah has been published. The article “The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season” is the result of his MSc thesis within the Global Change Ecology study program.
abstract: The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.
Alavipanah, S.; Wegmann, M.; Qureshi, S.; Weng, Q.; Koellner, T. The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season. Sustainability 2015, 7, 4689-4706.
The Department of Remote Sensing at the University of Wuerzburg, Germany, seeks to appoint a PhD student with strong interest or background knowledge of remote sensing, spatial modelling and biodiversity. The context for this position is the on going modification and variation of our environment and its impact on animal movement.
We are seeking a person capable of developing spatially explicit models to predict the effects of environmental variation and urban growth on animal movement patterns in Central Europe. Significant data for calibration will be available. The successful candidate will conduct her/his PhD in the project “Opt4Environment” funded by the Federal Ministry for Economic Affairs and Energy (BMWi).
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You will analyse environmental variables based or related to latest animal tracking and remote sensing tech-nology (Sentinel, TerraSAR-X, Tandem-X, Movebank.org data) that allow a better understanding of the interac-tion of vegetated and urbanized areas to assess the effects of both on animal movement patterns at appropri-ate scales. This will be coupled with ecological knowledge on impacts of vegetation variation and urban areas. Recent and current environmental impacts on movement, and new understandings of environmental dynamics with respect to animals, will inform your models. Vegetation and urban mapping within Central Europe is currently available at different scales but is increasing quickly in spatial and temporal resolution owing to new remote-sensing techniques. As data accuracy improves we will incorporate the best available information allowing us to continually improve the understanding of species-environment interaction model accuracy.
To be successful in this position you will have:
• a MSc in a relevant field (geography, biology, global change ecology, remote sensing)
• ability and interest to undertake independent research
• a strong interest and preferably also background in remote sensing, GIS or spatial modelling with re-cent experience in analysis and interpretation of complex data sets at a range of spatial scales
• demonstrated communication skills
• good skills or interest to learn the programming language R
• high interest to publish and present the outcome of this study
• high interest in interdisciplinary work
The successful candidate will receive a PhD position for 36 months (TV-L E13/2, 50% of a PostDoc salary). Please submit your application (in English) containing – as one document – a letter of interest, CV and names and contact information of two academic references by e-mail before December 15th 2014 – APPLICATION CLOSED
This position will be embedded in an interdisciplinary collaboration with the German Aerospace Center and the Max-Planck-Institute in Radolfzell. Regular travels to these collaborating institutes are scheduled.
- Dr. Martin Wegmann, University of Würzburg
- Dr. Thomas Esch, DLR
- Dr. Kamran Safi, MPI
The University of Wuerzburg is an equal opportunity employer that tries to increase the number of women in research and teaching. Applicants with disabilities but otherwise equal qualifications will be preferred.