Flavio Borfecchia

Satellite estimate of grass biomass in a mountainous range in central Italy

One of the main problems in managing ranges used for extensive pastoralism is the difficulty of obtaining reliable estimates of grass biomass over very large areas. Estimates of grass biomass are useful as an indicator of both available forage and risk of soil erosion. Nevertheless, large scale field measurements are expensive and time-consuming. The use of satellite images may provide a complementary means of estimating grass biomass over very large areas at a reasonable cost. The aim of this study was to test the use of Landsat satellite data for estimating grass biomass in a mountainous range in central Italy used primarily for sheep breeding. During each of four ground campaigns carried out over two years, grass was cut and its biomass measured in 60-90 test plots. Four Landsat images taken simultaneously to the ground campaigns were processed to obtain several vegetation indexes calculated for each ground test plot. The vegetation indexes showed significant correlations with measured grass biomass. The Normalized Difference Vegetation Index (NDVI) provided the most accurate estimate of grass biomass. When data for each of the four ground campaigns were analyzed separately, correlations for early summer campaigns were higher than correlations for late summer campaigns, indicating that when the ratio of dry/green biomass increases, satellite estimate becomes less accurate. Overall, our results show that satellite data can provide a useful source of biomass information for the management of large ranges.

Posidonia oceanica genetic and biometry mapping through high-resolution satellite spectral vegetation indices and sea-truth calibration

In the framework of Posidonia oceanica (PO) preservation activities, a small-scale restoration pilot project was implemented in 2005 at a Santa Marinella site to replace the loss of this important species of seagrass in this zone of the central Tyrrhenian coast via an innovative transplantation approach. In this context, taking into account the recent advances in the fields of high-resolution (HR) satellite/airborne remote-sensing and genetics laboratory analysis techniques, we propose this integrated methodology for monitoring changes in transplanted meadows in regard to perspective to provide support in the assessment of the entire local PO and seagrass population dynamic. According to specific information requirements in terms of radiometric and spectral/spatial resolution, the multispectral data currently available from the QuickBird polar satellite’s four-band (red, green, blue visible and near-infrared) HR sensor were exploited for methodology implementation using a practical ‘image-based’ approach to account for atmospheric and water column turbidity typical of this mid-coastal Mediterranean region. First, the extents and types of seagrass cover were suitably mapped, and then also the distributions of specific vegetation parameters related to PO dynamics and health were assessed by exploiting the remotely sensed satellite-derived radiance signals and point sea-truth calibration measurements of the bio-genetic parameters. In particular, we implemented maps of leaf area index, genetic similarity, and density Giraud indices corresponding to distributions of PO patches using multivariate and data-mining models (artificial neural network) based on appropriately preprocessed radiometric and auxiliary (bathymetry) input variables.

Seismic vulnerability assessment using field survey and remote sensing techniques

In this paper, a seismic vulnerability assessment at large scale is described, within the SIMURAI project. A field survey was carried out in order to gather detailed information about geometric characteristics, structural typology and age of construction of each single building. An airborne Remote Sensing (RS) mission was also carried out over the municipality of Avellino, providing a detailed estimate of 3D geometric parameters of buildings through a quite fast and easy to apply methodology integrating active LIDAR technology, aerophotogrammetry and GIS techniques. An analytical seismic vulnerability assessment procedure for Reinforced Concrete buildings is illustrated and applied to the building stock considering (i) field survey data (assumed as a reference) and (ii) LIDAR data combined with census data as alternative sources of information, according to a multilevel approach. A comparison between the obtained results highlights an acceptable scatter when data provided by RS techniques are used.

Mapping Spatial Patterns of Posidonia oceanica Meadows by Means of Daedalus ATM Airborne Sensor in the Coastal Area of Civitavecchia (Central Tyrrhenian Sea, Italy)

The spatial distribution of sea bed covers and seagrass in coastal waters is of key importance in monitoring and managing Mediterranean shallow water environments often subject to both increasing anthropogenic impacts and climate change effects. In this context we present a methodology for effective monitoring and mapping of Posidonia oceanica (PO) meadows in turbid waters using remote sensing techniques tested by means of LAI (Leaf Area Index) point sea truth measurements. Preliminary results using Daedalus airborne sensor are reported referring to the PO meadows at Civitavecchia site (central Tyrrhenian sea) where vessel traffic due to presence of important harbors and huge power plant represent strong impact factors. This coastal area, 100 km far from Rome (Central Italy), is characterized also by significant hydrodynamic variations and other anthropogenic factors that affect the health of seagrass meadows with frequent turbidity and suspended sediments in the water column. During 2011–2012 years point measurements of several parameters related to PO meadows phenology were acquired on various stations distributed along 20 km of coast between the Civitavecchia and S. Marinella sites. The Daedalus airborne sensor multispectral data were preprocessed with the support of satellite (MERIS) derived water quality parameters to obtain here improved thematic maps of the local PO distribution. Their thematic accuracy was then evaluated as agreement (R2) with the point sea truth measurements and regressive modeling using an on purpose developd method.

Remote sensing and GIS in planning photovoltaic potential of urban areas

Abstract The last guidelines approved by Italian government to financially support the solar Photovoltaic (PV) Energy production development include specific indications for more advantageously funding installations exploiting roofs/covers surfaces mainly located in urban or industrial areas. Since the 3D heterogeneity, albedo, atmospheric turbidity and casting shadows significantly influence here the local solar irradiance, the implemented methodology allowed us to suitably account for these distributed factors by means active (LIDAR) and passive satellite/airborne remote sensing techniques and advanced GIS modelling tools in order to support more realistic estimates of PV potential at roofs level in urban areas.

Mapping the earthquake-induced landslide hazard around the main oil pipeline network of the Agri Valley (Basilicata, southern Italy) by means of two GIS-based modelling approaches

Abstract This study presents a first-level spatial assessment of the susceptibility to earthquake-induced landslides in the seismic area of the Agri Valley (Basilicata Region, southern Italy), which hosts the largest onshore oilfield and oil/gas extraction and pre-treatment plant in Europe and is the starting point of the 136-km-long pipeline that transports the plant’s products to the refinery located in Taranto, on the Ionian seacoast. Two methodologies derived from the ones proposed by Newmark (Geotechnique 15(2):139–159, 1965) and Rapolla et al. (Eng Geol 114:10–25, 2010, Nat Hazards 61:115–126, 2012. doi:10.1007/s11069-011-9790-z), based on different modelling approaches, were implemented using the available geographic information system tools, which allowed a very effective exploitation of the two models capability for regional zoning of the earthquake-induced landslide hazard. Subsequently, the results obtained from the two models were compared by both visual evaluation of thematic products and statistical correlation analysis of quantitative indices, such as the Safety Index based on the Newmark’s approach and the Susceptibility Index from Rapolla’s model. The comparison showed a general agreement in highlighting the most critical areas. However, some slight differences between the two models’ results were observed, especially where rock materials and steep slopes are prevailing.

Landsat 8 OLI satellite data for mapping of the Posidonia oceanica and benthic habitats of coastal ecosystems

ABSTRACT The benthic seabeds and seagrass ecosystems, in particular the vulnerable Posidonia oceanica (PO), are increasingly threatened by climate change and other anthropogenic pressures. Along the 8000 km coastline of Italy, they are often poorly mapped and monitored to properly evaluate their health status. Thus to support these monitoring needs, the improved capabilities of the Landsat 8 Operational Land Imager (OLI) Earth Observation (EO) satellite system were tested for PO mapping by coupling its atmospherically corrected multispectral data with near-synchronous sea truth information. Two different approaches for the necessary atmospheric correction were exploited focusing on the Aerosol Optical Depth (AOD) and adjacency noise effects, which typically occur at land–sea interfaces. The general achievements demonstrated the effectiveness of High Resolution (HR) spectral responses captured by OLI sensor, for monitoring seagrass and sea beds in the optically complex Tyrrhenian shallow waters, with performance level dependent on the type of applied atmospheric pre-processing. The distribution of the PO leaf area index (LAI) on different substrates has been most effectively modelled using on purpose developed spectral indices. They were based on the coastal and blue-green OLI bands, atmospherically corrected using a recently introduced method for AOD retrieval, based on the Short Wave Infrared (SWIR) reflectance. The alternative correction method including a less effective AOD assessment but the removal of adjacency effects has proven its efficacy for improving the thematic discriminability of the seabed types characterized by different PO cover–substrate combinations.

Geomatics to Support the Environmental Impact Assessment in Renewable Energy Plants Installation

Projections to 2020 indicate that renewable energy sources (RES) could cover, from 20 to 30 percent of the world’s energy needs. To implement an effective e-governance in this direction, it is necessary to implement new methodologies to support decision-making in the local energy planning. The environmental impact is one of the main concern existing at different levels, in addition to the growing soil consumption in Europe. A significant problem for some types of plants, mainly solar and wind power, is the interaction of the devices with the surrounding environment, with possible negative effects in terms of visual impact and soil consumption. It is, therefore, very important to define which weight can have different impacts and to consider all possible scenarios.

Integrated remote sensing mission in the Venice Lagoon

In this work active and passive remote sensing techniques have been merged to collect information upon the distribution of natural, anthropic and industrial pollutants in the Venetian Lagoon. Some IR and UV images, sensed by a bispectral Daedalus AA3500 scanner, on board of an Italian Guardia di Finanza aircraft flying at 3000 m, have been integrated with lidar measurements, appropriately processed and georeferenced by means of GPS receivers, in order to display large scale distributions. The lidar fluorosensor, installed on a boat, has covered many different sites of the lagoon, while measuring amounts of chlorophyll, dissolved organic matter and oil slick. Lidar data have been used to calibrate the bispectral images acquired by the airborne scanner at low height by means of appropriate regression models. The models have shown a good correlation between the two different types of collected data. Finally, small scale detailed thematic maps of the distributions of the above- mentioned bio-chemical parameters have been produced for some risk sites of the lagoon, with the characterization and localization of pollutant sources.

Application of airborne remote sensing to the ancient Pompeii site

The ancient Pompeii site is in the Sarno Valley, an area of about 400 km2 in the South of Italy near Naples, that was utilized by man since old time (thousands of years ago). Actually the valley is under critical environmental conditions because of the relevant industrial development. ENEA is conducting various studies and research in the valley. ENEA is employing historical research, ground campaigns, cartography and up-to-date airborne multispectral remote sensing technologies to make a geographical information system. Airborne remote sensing technologies are very suitable for situations as that of the Sarno Valley. The paper describes the archaeological application of the research in progress as regarding the ancient site of Pompeii and its fluvial port.