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F2: ID.10510 MONITOR
4:30pm - 5:30pm
Session Chair: Yifang Ban
Session Chair: Chuanrong Li
Workshop: Land & Environment
Location: Sun Moon Room -2, 5.5 Floor, Junyi Dynasty Hotel
Downscaling Earth Observation data in the Thermal Infrared in Support of the study of the thermal environment in cities
University of Athens, Greece;
In this paper, an analysis is attempted on the presence of hot spots (small size areas with considerable and steadily higher temperatures within the urban web) in urban areas. The analysis extends from 1992 to 2015 for the mixed use urban agglomeration of Athens and reveals a set of hot spots, mostly in the central part of the city. Furthermore it shows a deteriorated thermal environment as a function of the urban population density, the type and stength of anthropogenic heat sources, urban geometry, the presence of green areas and the land use/land cover patterns. The analysis is based on the use of medium spatial resolution EO data of higher temporal resolution, as downscaled to high spatial resolution through the Pixel Block Intensity Modulation (PBIM) technique. Results are compared to the respective ones as they stem from the use of high resolution data, to show a comparable behaviour in terms of the patterns and spatial differences, although of lower land surface temperatures. Finally, a discussion is made on the potential to differentiate urban planning measures on the basis of EO data.
Earth observation in support of sustainable urban planning: results of the DRAGON-3 Monitor project - Part I on the thermal environment
University of Athens, Greece;
Sustainable urban planning increasingly demands innovative concepts and techniques to obtain up-to-date and area-wide information on the characteristics and development of the urban system. In this paper, a thorough and conclusive presentation will be made in terms of the results of the DRAGON-3 MONITOR project as based on the use of Earth Observation. Results refer in particular to a set of EO based dynamic urban indicators (i.e. urban form and expansion, land use/land cover changes, land surface temperature distribution, the presence and strength of urban heat island and thermal comfort) with the capacity to describe the state, dynamic changes and interaction of the land and thermal environment in urban areas. Furthermore results will be assessed in terms of their potentiality to operationally support sustainable urban planning and bridge the gap between EO scientists and urban planners. Constraints related to the spatial resolution and revisit time of satellite sensors will be discussed as they may influence the accuracy and applicability of the indicators. Methodologies to improve the applicability of the indicators will be also discussed along with the presentation of the respective results.
Estimating the Relationship Between Urban Form and Energy Consumption: A Case Study of Athens
National and Kapodistrian University of Athens, Greece;
Half of the world’s population lives in cities, a share that is likely to reach 70 percent in 2050. Cities consume as much as 80 percent of energy production worldwide and account for a roughly equal share of global greenhouse gas emissions as compared to other sources. As urban development advances, greenhouse gas emissions are driven less by industrial activities and more by the energy services required for lighting, heating, and cooling. At the same time urban density, the buildings’ stock and the spatial organizational patterns are crucial elements that influence energy consumption. In this study satellite data are used to assess the built-up features and dynamics of the urban agglomeration of Athens, Greece. The relation between the urban land use patterns and the land surface temperature was examined in order to assess the surface heat island phenomenon (SUHI) which affects significantly the energy demand for cooling and heating in large urban areas, thus affecting greenhouse gases emissions. In addition a number of metrics associated with urban extent and expansion were used to quantify the land use patterns and to serve as variables for the estimation of the relationship between land use patterns, energy consumption and CO2 emissions.