Abstract:The rising attention to energy consumption problems is renewing interest in the applications of thermal remote sensing in urban areas. The research presented here aims to test a methodology to retrieve information about roof surface temperature by means of a high resolution orthomosaic of airborne thermal infrared images, based on a case study acquired over Bologna (Italy). The ultimate aim of such work is obtaining datasets useful to support, in a GIS environment, the decision makers in developing adequate strategies to reduce energy consumption and CO2 emission. In the processing proposed, the computing of radiometric quantities related to the atmosphere was performed by the Modtran 5 radiative transfer code, while an object-oriented supervised classification was applied on a WorldView-2 multispectral image, together with a high-resolution digital surface model (DSM), to distinguish among the major roofing material types and to model the effects of the emissivity. The emissivity values were derived from literature data, except for some roofing materials, which were measured during ad hoc surveys, by means of a thermal camera and a contact probe. These preliminary results demonstrate the high sensitivity of the model to the variability of the surface emissivity and of the atmospheric parameters, especially transmittance and upwelling radiance.
A single-band surface temperature retrieval method is proposed, aiming at achieving a better accuracy by exploiting the integration of aerial thermal images with LiDAR data and ground surveys. LiDAR data allow the generation of a high resolution digital surface model and a detailed modeling of the Sky-View Factor (SVF). Ground surveys of surface temperature and emissivity, instead, are used to estimate the atmospheric parameters involved in the model (through a bounded least square adjustment) and for a first assessment of the accuracy of the results. The RMS of the difference between the surface temperatures computed from the model and measured on the check sites ranges between 0.8°C and 1.0°C, depending on the algorithm used to calculate the SVF. Results are in general better than the ones obtained without considering SVF and prove the effectiveness of the integration of different data sources. The proposed approach has the advantage of avoiding the modeling of the atmosphere conditions, which is often difficult to achieve with the desired accuracy; on the other hand, it is highly dependent on the accuracy of the data measured on the ground.
The ChoT project aims at analysing the potential of aerial thermal imagery to produce large scale datasets for energetic efficiency analyses and policies in urban environments. It is funded by the Italian Ministry of Education, University and Research (MIUR) in the framework of the SIR 2014 (Scientific Independence of young Researchers) programme. The city of Bologna (Italy) was chosen as the case study. The acquisition of thermal infrared images at different times by multiple aerial flights is one of the main tasks of the project. The present paper provides an overview of the ChoT project, but it delves into some specific aspects of the data processing chain: the computing of the radiometric quantities of the atmosphere, the estimation of surface emissivity (through an object-oriented classification applied on a very high resolution multispectral image, to distinguish among the major roofing materials) and sky-view factor (by means of a digital surface model). To collect ground truth data, the surface temperature of roofs and road pavings was measured at several locations at the same time as the aircraft acquired the thermal images. Furthermore, the emissivity of some roofing materials was estimated by means of a thermal camera and a contact probe. All the surveys were georeferenced by GPS. The results of the first surveying campaign demonstrate the high sensitivity of the model to the variability of the surface emissivity and the atmospheric parameters.
The management of an urban context in a Smart City perspective requires the development of innovative projects, with new applications in multidisciplinary research areas. They can be related to many aspects of city life and urban management: fuel consumption monitoring, energy efficiency issues, environment, social organization, traffic, urban transformations, etc. Geomatics, the modern discipline of gathering, storing, processing, and delivering digital spatially referenced information, can play a fundamental role in many of these areas, providing new efficient and productive methods for a precise mapping of different phenomena by traditional cartographic representation or by new methods of data visualization and manipulation (e.g. three-dimensional modelling, data fusion, etc.). The technologies involved are based on airborne or satellite remote sensing (in visible, near infrared, thermal bands), laser scanning, digital photogrammetry, satellite positioning and, first of all, appropriate sensor integration (online or offline). The aim of this work is to present and analyse some new opportunities offered by Geomatics technologies for a Smart City management, with a specific interest towards the energy sector related to buildings. Reducing consumption and CO2 emissions is a primary objective to be pursued for a sustainable development and, in this direction, an accurate knowledge of energy consumptions and waste for heating of single houses, blocks or districts is needed. A synoptic information regarding a city or a portion of a city can be acquired through sensors on board of airplanes or satellite platforms, operating in the thermal band. A problem to be investigated at the scale A problem to be investigated at the scale of the whole urban context is the Urban Heat Island (UHI), a phenomenon known and studied in the last decades. UHI is related not only to sensible heat released by anthropic activities, but also to land use variations and evapotranspiration reduction. The availability of thermal satellite sensors is fundamental to carry out multi-temporal studies in order to evaluate the dynamic behaviour of the UHI for a city. Working with a greater detail, districts or single buildings can be analysed by specifically designed airborne surveys. The activity has been recently carried out in the EnergyCity project, developed in the framework of the Central Europe programme established by UE. As demonstrated by the project, such data can be successfully integrated in a GIS storing all relevant data about buildings and energy supply, in order to create a powerful geospatial database for a Decision Support System assisting to reduce energy losses and CO2 emissions. Today, aerial thermal mapping could be furthermore integrated by terrestrial 3D surveys realized with Mobile Mapping Systems through multisensor platforms comprising thermal camera/s, laser scanning, GPS, inertial systems, etc. In this way the product can be a true 3D thermal model with good geometric properties, enlarging the possibilities in respect to conventional qualitative 2D images with simple colour palettes. Finally, some applications in the energy sector could benefit from the availability of a true 3D City Model, where the buildings are carefully described through three-dimensional elements. The processing of airborne LiDAR datasets for automated and semi-automated extraction of 3D buildings can provide such new generation of 3D city models.
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