Carmelo Riccardo Fichera

Land Cover classification and change-detection analysis using multi-temporal remote sensed imagery and landscape metrics

Abstract Remote Sensing (RS) data and techniques, in combination with GIS and landscape metrics, are fundamental to analyse and characterise Land Cover (LC) and its changes. The case study here described, has been conducted in the area of Avellino (Southern Italy). To characterise the dynamics of changes during a fifty year period (1954–2004), a multitemporal set of images has been processed: aerial photos (1954), and Landsat scenes (MSS 1975, TM 1985 and 1993, ETM+ 2004). LC pattern and its changes are linked to both natural and social processes whose driving role has been clearly demonstrated in the case study: after the disastrous Irpinia earthquake (1980), specific zoning laws and urban plans have significantly addressed landscape changes

GIS and remote sensing to study urban-rural transformation during a fifty-year period

A relevant issue in Remote Sensing (RS) and GIS is related to the analysis and the characterization of Land Use Land Cover (LULC) changes, very useful for a wide range of environmental applications and to efficiently undertake landscape planning and management policies. The methodology described has been applied to a case-study conducted in the area of the Province of Avellino (Southern Italy). Firstly, aerial photos and Landsat imagery have been classified to produce LULC maps for a fifty-year period (1954/2004). Then, through a GIS approach, change detection and spatiotemporal analysis has been integrated to characterize LULC dynamics, focusing on the urban-rural gradient. This study has shown that LULC patterns and their changes are linked to both natural and social processes whose driving role has been clearly demonstrated: after the disastrous Irpinia earthquake (1980), local specific zoning laws and urban plans have significantly addressed landscape changes.

A GIS-MCDA Based Model for the Suitability Evaluation of Traditional Grape Varieties: The Case-Study of ‘Mantonico' Grape (Calabria, Italy)

Physical land suitability evaluation is crucial to rural spatial planning, as it directly contributes to designing successful and sustainable interventions. This paper deals with a physical land-suitability evaluation model for Mantonico, a historical and traditional grape variety of Southern Calabria (Italy), which is showing a considerable decline in its cultivation, owing to the abandonment of this cultivar in favor of others that are certainly more quantitatively productive, yet less valuable from a traditional and cultural point of view. The evaluation model developed was based on consolidated GIS-based MCDA (Multi-Criteria Decision Analysis) procedure and showed that the choice of the criteria (factors and constraints), which describe the physical land suitability for a niche product, is important and delicate. In fact, it is not always easy to establish how territorial characteristics may influence the development of the cultivation of an agricultural product. In this paper, the choice and, above all, the values associated to the factors, adequately represented real conditions and, as a consequence, the results of the model showed a clear coherence between suitability gradients and lands with similar cultivations. Results were validated by comparing the real geographical distribution of the current vine growing to the suitability value obtaining a very positive feedback on the robustness of the implemented model. The comparison between current vine-growing areas and the values obtained from the model clearly shows that the current vine-growing sites of the study area fall in suitable and very suitable classes (83.8%).

Land Suitability Evaluation for Agro-forestry: Definition of a Web-Based Multi-Criteria Spatial Decision Support System (MC-SDSS): Preliminary Results

Land suitability evaluation (LSE) is a widespread methodology that supports environmental managers and planners in analysing the interactions between location, development actions, and environmental elements. In the present paper, we discuss on a web-based multi-criteria spatial decision support system (MC-SDSS) implemented to accomplish LSE for agro-forestry. We propose a MC-SDSS developed on a free open source software for geospatial (FOSS4G) environment, accessible through a user-friendly geographical user interface (GUI) that allows to perform geospatial analyses. To this end, the MC-SDSS has been conceived as a multi-tier architecture, able to manage processes executable via OGC (Open Geospatial Consortium) web processing services (WPSs) and produce output maps and data available via the largely used OGC services: web feature service (WFS), web coverage service (WCS) and web map service (WMS). In this first application, we chose the weighted linear combination (WLC) as decision rule to aggregate data, weighted by judgements provided by experts following the analytical hierarchy process (AHP).