Maria Danese

Kernel Density Estimation Methods for a Geostatistical Approach in Seismic Risk Analysis: The Case Study of Potenza Hilltop Town (Southern Italy)

This paper focuses on an overview of kernel density estimation especially for what concerns the choice of bandwidth and intensity parameters according to local conditions. A case study inherent seismic risk analysis of the old town centre of Potenza hilltop town has been discussed, with particular attention to the evaluation of the possible local amplifying factors. This first integrated application of kernel density maps to analyse seismic damage scenarios with a geostatistical approach allowed to evaluate the local geological, geomorphological and 1857 earthquake macroseismic data, offering a new point of view of civil protection planning. The aim of geostatistical approach is to know seismic risk variability at local level, modelling and visualizing it.

Urban Versus Rural: The Decrease of Agricultural Areas and the Development of Urban Zones Analyzed with Spatial Statistics

Until a few decades ago it was very easy to distinguish between city and country: in most cases the edge was defined by defensive barriers. In recent times, the relationships between urban and rural areas completely changed, placing the country in a subordinate position. Consequently, many terms have been coined in order to describe the new phenomena taking place between city and country. The term adopted, “periurban area†, despite its large use, does not have a clear and unambiguous definition. Such various approaches are due to the complexity of the phenomenon to be analyzed and to the huge variety of territorial contexts in which it may reveal. The phenomenon is characterized by urban growth with soil consumption generating loss of competitiveness for agricultural activities. This paper defines more precise rules in order to describe the periurban phenomenon, using techniques of spatial statistic and point pattern analysis. This approach has been tested in the case of study of Potenza municipality. Interest in this area comes after the earthquake of 1980, when a large migration of inhabitants began towards the countryside around Potenza.

Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis

Abstract Traditional methods of recording fire burned areas and fire severity involve expensive and time-consuming field surveys. Available remote sensing technologies may allow us to develop standardized burn-severity maps for evaluating fire effects and addressing post fire management activities. This paper focuses on multiscale characterization of fire severity using multisensor satellite data. To this aim, both MODIS (Moderate Resolution Imaging Spectroradiometer) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data have been processed using geo-statistic analyses to capture pattern features of burned areas. Even if in last decades different authors tried to integrate geo-statistics and remote sensing image processing, methods used since now are only variograms, semivariograms and kriging. In this paper, we propose an approach based on the use of spatial indicators of global and local autocorrelation. Spatial autocorrelation statistics, such as Morans I and Getis–Ord Local Gi index, were used to measure and analyze dependency degree among spectral features of burned areas. This approach enables the characterization of pattern features of a burned area and improves the estimation of fire severity.

Satellite-Based Monitoring of Archaeological Looting in Peru

Illegal excavations represent one of the main risk factors which affect the archaeological heritage all over the world, in particular in those countries, from Southern America to Middle East, where the surveillance on site is little effective and time consuming and the aerial surveillance is non practicable due to military or political restrictions. In such contexts satellite remote sensing offers a suitable chance to monitor this phenomenon. The chapter deals with the results obtained on some areas of Cahuachi (Peru) by using a time series of very high resolution satellite images. The rate of success in detecting changes related to archaeological looting has been fruitfully improved by adopting a semiautomatic approach based on spatial autocorrelation.

Visual Impact Assessment in Urban Planning

Nearly half a century has passed since Lynch described visual quality of American cities. Although the issue of visual impact assessment in urban planning is not new, only few experiences exist considering visual aspect when realizing new development zones. Visual aspects are fundamental in urban planning, since each plan choice can generate manipulation or obstruction of urban elements, producing negative effects on the image of the city. Viewshed analysis can help to achieve a more objective and consequently more effective analysis of visual impacts. Traditional viewshed analyses (single, multiple and cumulative) do not show which target is visible from a certain cell. On this purpose, a new viewshed analysis has been developed, the Identifying Viewshed, which shows how many and which objects are visible in several areas. The implemented extension has been tested in three different contexts, Laurenzana and Venosa, in Basilicata Region, and Pisa, in Tuscany.

Predictive modeling for preventive Archaeology: overview and case study

The use of GIS and Spatial Analysis for predictive models is an important topic in preventive archaeology. Both of these tools play an important role in the Support Decision System (SDS) for archaeological research and for providing information useful to reduce archaeological risk. Over the years, a number of predictive models in the GIS environment have been developed and proposed. The existing models substantially differ from each other in methodological approaches and parameters used for performing the analysis. Until now, only few works consider spatial autocorrelation, which can provide more effective results. This paper provides a brief review of the existing predictive models, and then proposes a new methodological approach, applied to the neolithic sites in the Apulian Tavoliere (Southern Italy), that combines traditional techniques with methods that allow us to include spatial autocorrelation analysis to take into account the spatial relationships among the diverse sites.

Analyzing Neighbourhoods Suitable for Urban Renewal Programs with Autocorrelation Techniques

Since the Industrial Revolution the main model of urban development has been based on the concept of urban expansion, where new parts are added to existing towns in order to satisfy the housing demand. While in pre-industrial cities, main activities influence a portion of space within or immediately next to the border of urban settlements, the rapid growth of cities in the industrial era represents the transition from an almost sustainable city to a city that takes advantage of the carrying capacity of neighbouring regions (Stren et al., 1992).

Geostatistics in historical macroseismic data analysis

This paper follows a geostatistical approach for the evaluation, modelling and visualization of the possible local interactions between natural components and built-up elements in seismic risk analysis. This method, applied to old town centre of Potenza hilltop town, offers a new point of view for civil protection planning using kernel density and autocorrelation indexes maps to analyse macroseismic damage scenarios and to evaluate the local geological, geomorphological and 1857 earthquakes macroseismic data.

Using spatial autocorrelation techniques and multi-temporal satellite data for analyzing urban sprawl

Satellite time series offer great potential for a quantitative assessment of urban expansion, urban sprawl and for monitoring of land use changes and soil consumption. This study deals with the spatial characterization of expansion of urban areas by using spatial autocorrelation techniques applied to multi-date Thematic Mapper (TM) satellite images. The investigation focused on several very small towns close to Bari. Urban areas were extracted from NASA Landsat images acquired in 1976, 1999 and 2009, respectively. To cope with the fact that small changes have to be captured and extracted from TM multi-temporal data sets, we adopted the use of spectral indices to emphasize occurring changes, and spatial autocorrelation techniques to reveal spatial patterns. Urban areas were analyzed using both global and local autocorrelation indexes. This approach enables the characterization of pattern features of urban area expansion and it improves land use change estimation. The obtained results showed a significant urban expansion coupled with an increase of irregularity degree of border modifications from 1976 to 2009.

3D Simulations in Environmental Impact Assessment

The increase of petrol cost and the failure of Kyoto agreement generated huge investments in renewable energy sources. In recent times a lot of local authorities allowed wind farm location. In many cases, environmental impact assessments do not take into account visual aspects sufficiently. This component, often ignored, is the most observed by local communities. Visual noise produces strong opposition and public resistance to wind turbine generator placements. Some kinds of 3D simulations can support visual impact assessments each one with some limits and only for few aspects. This paper aims to highlight advantages of several techniques of 3D geo-visualization and improvements obtainable by means of geographical analysis as a support for environmental impact assessments. The study case has been applied in a region located in southern Italian Apennine with elevated wind power and at the same time excellent landscape from a naturalistic point of view.