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.

Remote sensing can play a key role in risk assessment and management, especially when several concurrent factors coexist, such as a predisposition to natural disasters and the urban sprawl, spreading over highly vulnerable areas. In this context, multitemporal analysis can provide decision-makers with tools and information to reduce the impacts of disasters (e.g. flooding) and to encourage a sustainable development. The present work focuses on the employment of multispectral satellite imagery to produce multitemporal land use/cover maps for the city of Dhaka, which is subject to frequent flooding events. In particular, the evaluation of the urban growth, the analysis of the annual dynamics of flooding and the study of the 2004 catastrophic event were performed. For the change-detection procedure, Landsat images were used. These images allow the quantification of the very rapid growth of the metropolis, with an increase in built-up areas from 75 to 111 km². The image of 2009 showed that an ordinary flood affects about 115 km² (on a studied area of 591 km²). On the other hand, the analysis of the 2004 extreme flooding event, performed on a wider area, showed that the affected lands added up to 750 km² (on about 3845 km²).

The availability of multispectral images, with both high spatial and spectral resolution, makes it possible to obtain valuable information about complex urban environment, reducing the need for more expensive surveying techniques. Here, a methodology is tested for the semi-automatic extraction of buildings and the mapping of the main roofing materials over a urban area of approximately 100 km², including the entire city of Bologna (Italy). The methodology follows an object-oriented approach and exploits a limited number of training samples. After a validation based on field inspections and close-range photos acquired by a drone, the final map achieved an overall accuracy of 94% (producer accuracy 79%) regarding the building extraction and of 91% for the classification of the roofing materials. The proposed approach proved to be flexible enough to catch the strong variability of the urban texture in different districts and can be easily reproducible in other contexts, as only satellite imagery is required for the mapping.

In this work, two processes related to the onset and the evolution of large‐scale rockfalls have been analysed by means of remote sensing techniques. First, the number of rock bridges as a proportion of pre‐existing fractures has been estimated in a newly formed landslide scarp by analysing the spectral information of the rock mass in terrestrial laser scanner (TLS) and unmanned aerial vehicle (UAV) photogrammetric point clouds. Second, the fragmentation of the rock mass after failure has been assessed by comparing the percentage of newly formed fractures in the scarp and in the deposit. For this purpose, an orthophoto of the landslide deposit was classified using an object‐based method. The presented workflow gained new data on the intact rock breakage during and after failure, and consequently deepened knowledge about rock failure and fragmentation mechanisms.