The opportunities of retrieving geospatial datasets as open data and the reliability of Free and Open Source Software (FOSS) GIS increased the possibilities of performing a large number of geospatial analyses. In particular, the worldwide availability of Digital Elevation Model (DEM) permits to compute several topographic indexes able to characterize the land morphology. In this paper, we evaluate the performances of different open source GIS in the calculation of the Topographic Wetness Index (TWI), a widespread index in hydrological analysis that describes the tendency of an area to accumulate water. Nowadays, there is a large number of available open source desktop GIS, maintained as FOSS projects, each of them focusing on developing specific goals. Therefore, from user point of view, the choice of the best software in solving a particular task is influenced by the GIS specific features. The test was performed computing the TWI for the Rio Sinigo basin, in northern Italy. The DEM of the test area has been processed with GRASS GIS, Whitebox GAT and SAGA GIS. In order to identify equal workflows, all the combinations of available algorithms and parameters have been studied for each considered GIS. The final TWI maps produced as output were compared and discussed.

No abstract

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.

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 km

The analysis of the vertical movements of the soil in the Po River plane of the Emilia-Romagna Region (Italy) was updated through an interferometric analysis referred to the 2011-2016 time-span. This activity is a continuation of previous studies on the state of knowledge of vertical soil movements in the same area, analyzed firstly by levelling and GNSS and more recently by SAR interferometry for the periods 1992-2000, 2002-2006, 2006-2011, on behalf of the Emilia-Romagna Region. The survey area analysed was approximately 13 300 km 2 , which corresponds to the territory of the regional plain. The interferometric dataset was calibrated through the use of velocity time series of several permanent GNSS stations. Among the 36 stations analysed, 22 were included in the study area: 16 were used for the calibration and 6 as check points). The velocities required for the calibration of the SAR analysis were calculated in the period following the important seismic events that struck the territory of the Emilia Romagna Region in May 2012. The interferometric analysis was carried out by TRE ALTAMIRA using the SqueeSAR™ technology. In particular, in order to update the interferometric dataset to 2016, it was necessary to perform a joint processing of the available RADARSAT-1 data and of the data acquired by the RADARSAT-2 satellite using a specific operating mode of the SqueeSAR™ algorithm known as stitching; this approach allowed the joint processing of images acquired in the same geometry by these two satellites. The study of the time series of the GNSS permanent stations used to provide the velocity datum to the interferometric analysis, is described, and the results of the SqueeSAR™ interferometric processing are reported. Statistical analyses on the spatial distribution and the type of scatterers have been performed during the screening and validation procedures of the dataset, and for the identification and removal of the outliers. Finally, the resulting map is described in order to analyse the measured soil movements with respect to the results obtained in past analyses, and the possible geological and human-induced causes, which could have produced them.Published by Copernicus Publications on behalf of the International Association of Hydrological Sciences. 40 G. Bitelli et al.: Updating the subsidence map of Emilia-Romagna region (Italy)

No abstract

In this work, two processes related to the onset and the evolution of largescale 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.

No abstract