Urban Atlas, land use modelling and spatial metric techniques

Recently, through the GMES program of ESA the Urban Atlas dataset was released. The Urban Atlas is providing pan-European comparable land use and land cover data for Large Urban Zones with more than 100.000 inhabitants as defined by the Urban Audit. The production of the various datasets started in 2009 and is expected to be completed by the end of 2011. At presently datasets for more than 150 urban areas have been released. Most importantly the datasets can be freely downloaded and distributed. The availability of such a huge dataset produced with the same standards will have a major impact on the development of urban transportation models and the comparative analysis of the urban areas across Europe. Combined with the data sets that will be developed from the various Census of population it could become the basis for the application of various models in the next ten years. In this paper two major themes are discussed. First, how the current state of art in urban modeling (behavioral, cellular automata and statistical) can use these models, what type of additional data might be needed and how these datasets can be combined with other data for developing land use transportation models. Second, spatial metric techniques are used to define indicators for the landscape that could be used for comparing the structure and the form of the various cities. In the last ten years there has been an increasing interest in applying spatial metric techniques analysis of urban environments, to examine unique spatial components of intra-and inter-city urban structure, as well as, the dynamics of change. The landscape perspective assumes abrupt transitions between individual patches that result in distinct edges. These measures provide a link between the detailed spatial structures that result from urban change processes. The spatial metric indicators were developed for several cities and are then used for a comparative study of city typologies and urban fabric characteristics.

Chapter Earth Observation for Urban Climate Monitoring: Surface Cover and Land Surface Temperature

The rate at which global climate change is happening is arguably the most pressing environmental challenge of the century, and it affects our cities. Climate change exerts added stress on urban areas through increased numbers of heat waves threatening people’s well-being and, in many cases, human lives. Earth observation (EO) systems and the advances in remote sensing technology increase the opportunities for monitoring the thermal behavior of cities. The Sentinels constitute the first series of operational satellites for Copernicus, a program launched to provide data, information, services, and knowledge in support of Europe’s goals regarding sustainable development and global governance of the environment. This chapter examines the exploitation of EO data for monitoring the urban climate, with particular focus on the urban surface cover and temperature. Two example applications are analyzed: the mapping of the urban surface and its characteristics, using EO data and the estimation of urban temperatures. Approaches, like the ones described in this chapter, can become operational once adapted to Sentinels, since their long-term operation plan guarantees the future supply of satellite observations. Thus, the described methods may support planning activities related to climate change mitigation and adaptation in cities, as well as routine urban planning activities

Urban Atlas, land use modelling and spatial metric techniques

Recently, through the GMES program of ESA the Urban Atlas dataset was released. The Urban Atlas is providing pan-European comparable land use and land cover data for Large Urban Zones with more than 100.000 inhabitants as defined by the Urban Audit. The production of the various datasets started in 2009 and is expected to be completed by the end of 2011. At presently datasets for more than 150 urban areas have been released. Most importantly the datasets can be freely downloaded and distributed. The availability of such a huge dataset produced with the same standards will have a major impact on the development of urban transportation models and the comparative analysis of the urban areas across Europe. Combined with the data sets that will be developed from the various Census of population it could become the basis for the application of various models in the next ten years. In this paper two major themes are discussed. First, how the current state of art in urban modeling (behavioral, cellular automata and statistical) can use these models, what type of additional data might be needed and how these datasets can be combined with other data for developing land use transportation models. Second, spatial metric techniques are used to define indicators for the landscape that could be used for comparing the structure and the form of the various cities. In the last ten years there has been an increasing interest in applying spatial metric techniques analysis of urban environments, to examine unique spatial components of intra-and inter-city urban structure, as well as, the dynamics of change. The landscape perspective assumes abrupt transitions between individual patches that result in distinct edges. These measures provide a link between the detailed spatial structures that result from urban change processes. The spatial metric indicators were developed for several cities and are then used for a comparative study of city typologies and urban fabric characteristics

A TRMM-Calibrated infrared technique for rainfall estimation: application on rain events over eastern Mediterranean

The aim is to evaluate the use of a satellite infrared (IR) technique for estimating rainfall over the eastern Mediterranean. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the Eastern Mediterranean for four rain events during the six month period of October 2004 to March 2005. Estimates from this technique are verified over a rain gauge network for different time scales. Results show that PR observations can be applied to improve IR-based techniques significantly in the conditions of a regional scale area by selecting adequate calibration areas and periods. They reveal, however, the limitations of infrared remote sensing techniques, originally developed for tropical areas, when applied to precipitation retrievals in mid-latitudes

Macroscopic Traffic Flow Model Calibration Using Different Optimization Algorithms

AbstractThis study tests and compares different optimization algorithms employed for the calibration of a macroscopic traffic flow model. In particular, the deterministic Nelder-Mead algorithm, a stochastic genetic algorithm and the stochastic cross-entropy method are utilized to estimate the parameter values of the METANET model for a particular freeway site, using real traffic data. The resulting models are validated using various traffic data sets and the optimization algorithms are evaluated and compared with respect to the accuracy of the produced models as well as the convergence speed and the required computation time

Urban surface temperature time series estimation at the local scale by spatial-spectral unmixing of satellite observations

The study of urban climate requires frequent and accurate monitoring of land surface temperature (LST), at the local scale. Since currently, no space-borne sensor provides frequent thermal infrared imagery at high spatial resolution, the scientific community has focused on synergistic methods for retrieving LST that can be suitable for urban studies. Synergistic methods that combine the spatial structure of visible and near-infrared observations with the more frequent, but low-resolution surface temperature patterns derived by thermal infrared imagery provide excellent means for obtaining frequent LST estimates at the local scale in cities. In this study, a new approach based on spatial-spectral unmixing techniques was developed for improving the spatial resolution of thermal infrared observations and the subsequent LST estimation. The method was applied to an urban area in Crete, Greece, for the time period of one year. The results were evaluated against independent high-resolution LST datasets and found to be very promising, with RMSE less than 2 K in all cases. The developed approach has therefore a high potential to be operationally used in the near future, exploiting the Copernicus Sentinel (2 and 3) observations, to provide high spatio-temporal resolution LST estimates in cities

Thermal detection of plumes produced by industrial accidents in urban areas based on the presence of the heat

Abstract. Detection of plumes produced by industrial accidents using NOAA/AVHRR thermal imagery may be substantially supported in urban areas by the presence of the heat island phenomenon. In this study, an attempt is made to classify the urban web on the basis of the heat island and its impact on the brightness temperatures. Application of the classi cation scheme on a night-time thermal infrared NOAA-14 image depicting the urban web of Athens demonstrates the potential of this classi cation for the detection of a plume caused by a re in a warehouse. Detection of the plume in this case is favoured by the urban heat island phenomenon due to which the urban surface has higher temperature compared to the adjacent environment and the plume above. As a result, distinction of the pixels corresponding to the plume is more eVective

Thermal detection of plumes produced by industrial accidents in urban areas based on the presence of the heat

Abstract. The detection of plumes produced by industrial accidents with the use of NOAA/AVHRR thermal imagery, may be substantially supported in urban areas due to the presence of the heat island phenomenon. In this study, an attempt is made to classify the urban web on the basis of the heat island and its impact on the brightness temperatures. The application of the classification scheme on a night-time thermal infrared NOAA-14 image depicting the urban web of Athens, demonstrates the potential of this classification for the detection of a plume caused by a fire in a warehouse. Detecting the plume in this specific case, is favoured by the urban heat island phenomenon due to which the urban surface has higher temperature compared to the adjacent environment and the above plume. As a result, the distinction of the pixels corresponding to the plume is more effective

Incorporating bio-physical sciences into a decision support tool for sustainable urban planning

Deciding upon optimum planning actions in terms of sustainable urban planning involves the consideration of multiple environmental and socio-economic criteria. The transformation of natural landscapes to urban areas affects energy and material fluxes. An important aspect of the urban environment is the urban metabolism, and changes in such metabolism need to be considered for sustainable planning decisions. A spatial Decision Support System (DSS) prototyped within the European FP7-funded project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism), enables accounting for the urban metabolism of planning actions, by exploiting the current knowledge and technology of biophysical sciences. The main aim of the BRIDGE project was to bridge the knowledge and communication gap between urban planners and environmental scientists and to illustrate the advantages of considering detailed environmental information in urban planning processes. The developed DSS prototype integrates biophysical observations and simulation techniques with socio-economic aspects in fiveEuropean cities, selected as case studies for the pilot application of the tool. This paper describes the design and implementation of the BRIDGE DSS prototype, illustrates some examples of use, and highlights the need for further research and development in the field