Mario Palladino

An Integrated Approach for the Environmental Characterization of a Wide Potentially Contaminated Area in Southern Italy

This paper deals with the environmental characterization of a large and densely populated area, with a poor reputation for contamination, considering the contribution of environmental features (air, soil, soil hydraulic and groundwater) and the potential effects on human health. The use of Geographic Information System (GIS) has made possible a georeferenced inventory and, by overlaying environmental information, an operational synthesis of comprehensive environmental conditions. The cumulative effects on environmental features were evaluated, taking into account superposition effects, by means of the Spatial MultiCriteria Decision Analysis (S-MCDA). The application of the S-MCDA for converging the combination of heterogeneous factors, related to soil, land and water, deeply studied by heterogeneous groups of experts, constitutes the novelty of the paper. The results confirmed an overall higher potential of exposure to contaminants in the environment and higher mortality rates in the study area for some tumours, but hospital admissions for tumours were generally similar to the regional trend. Besides, mortality data may be strictly dependent on the poor socioeconomic conditions, quality of therapy and a lack of welfare in the area relative to the rest of Italy. Finally, as regards the possible relationship between presence of contaminants in the environment and health conditions of the population no definite conclusions can be drawn, although the present study encourages the use of the new proposed methods, that increase the possibilities for studying the combined effect of more environmental factors.

Evaluation of near-surface soil water status through the inversion of soil–canopy radiative transfer models in the reflective optical domain

Knowledge of the spatial and temporal variability of surface soil water content (SWC) is important to understand the linkage between hydrological, ecological and geological processes in a region. Optical Earth observation (EO) data offer the possibility to retrieve surface soil water information, since an overall decrease of soil reflectance corresponds to increasing SWC. Sensitivity analysis of the combined leaf (PROSPECT) and canopy (SAILH) reflectance models (PROSAIL) to soil reflectance variations was carried out, and remote sensing and ground data from different experimental agricultural sites (ESA Spectra Barrax Campaigns (SPARC) 2004, ESA Airborne SAR and Optic Campaigns (AgriSAR) 2006 and participatory multi-level EO-assisted tools for irrigation water management and agricultural decision-support (PLEIADeS) 2007) were exploited. A simple look-up table (LUT) inversion technique was implemented to estimate canopy and soil variables. High negative relationships (r = −0.87) between the soil reflectance factor of the model and the measured SWC were found for several crop types and different locations exhibiting a low fractional vegetation cover (fCover). Even though quantification of SWC is difficult, the method could be useful to obtain relative SWC information, especially before the start and at the beginning of the growing season. Furthermore, the physically based estimation approach offers the possibility of getting information about soil and canopy characteristics concurrently from optical EO data. The methodology presented in this article may also represent a suitable complement in the retrieval of SWC from active microwave.

Assessing the ability of hybrid poplar for in-situ phytoextraction of cadmium by using UAV-photogrammetry and 3D flow simulator

ABSTRACT The purpose of this study is to evaluate the capability of hybrid poplar (Populus deltoides × Populus nigra) to reduce cadmium (Cd) concentrations in an experimental site of Campania Region (southern Italy) subjected to illegal deposit of industrial and household waste. We propose to evaluate the efficiency of poplar for Cd phytoextraction by coupling the use of a process-based, distributed hydrological model (HydroGeoSphere, HGS) with photogrammetric images acquired by Unmanned Aerial Vehicle (UAV). This scenario-based approach exploits in-situ measurements so as to be able to reproduce reliable near-real-world processes. The original bare soil (BS; unplanted reference location) is used as benchmark and compared to the situation where poplar trees are planted (PP) for bioremediation purposes. The ‘virtual’ positions of poplars were chosen by considering the expected Cd accumulation areas that are correlated to topographic indices retrieved from the high-resolution (0.03 × 0.03 m) digital elevation model (DEM) generated by UAV photogrammetric photos. Transfer and accumulation of Cd in the poplars were described by a time-variant sink term featuring the HGS transport equation. The numerical simulations show that poplar trees are able to reduce Cd concentrations by 15%, 36%, and 64% in spring, summer, and autumn, respectively. Coupling an advanced 3D hydrological model with a high-resolution DEM generated by UAV-photogrammetry seems a promising and viable approach for assessing the efficiency of phytoremediation techniques.

Spatial distribution of soil water content from airborne thermal and optical remote sensing data

Spatial and temporal information of soil water content is of essential importance for modelling of land surface processes in hydrological studies and applications for operative systems of irrigation management. In the last decades, several remote sensing domains have been considered in the context of soil water content monitoring, ranging from active and passive microwave to optical and thermal spectral bands. In the framework of an experimental campaign in Southern Italy in 2007, two innovative methodologies to retrieve soil water content information from airborne earth observation (E.O.) data were exploited: a) analyses of the dependence of surface temperature of vegetation with soil water content using thermal infrared radiometer (TIR), and b) estimation of superficial soil moisture content using reflectance in the visible and near infrared regions acquired from optical sensors. The first method (a) is applicable especially at surfaces completely covered with vegetation, whereas the second method is preferably applicable at surfaces without or with sparse vegetation. The synergy of both methods allows the establishment of maps of spatially distributed soil water content. Results of the analyses are presented and discussed, in particular in view of an operative context in irrigation studies.

Exploiting optical E.O. data for soil moisture retrieval

In the context of agricultural applications, the knowledge of soil moisture availability is an essential aspect for irrigation management. The microwave waveband region (SAR) has been primarily used to estimate soil moisture from Earth Observation (E.O.) data. However, the optical domain (0.4 - 2.5 μm) may as well offer the possibility to get information about soil moisture since an overall decrease of soil reflectance corresponds to increasing surface soil water content. Data from two different experiments (ESA SPARC and AgriSAR) have been exploited aiming at estimating soil moisture from optical E.O. data by using the radiative transfer model PROSAILH. A soil scale factor (α) was introduced into the model and estimated using a LUT inversion technique. Relatively high negative relationships between the α-factor and the measured soil water content (up to R2 = 0.73) could be found for several crop types with low vegetation cover. The results of this study indicate the potential to retrieve surface soil moisture information from optical E.O. data for similar soil types. The method gives the advantage of retrieving simultaneously soil and canopy characteristics from the same E.O. data sources by using a physical method of parameter estimation.

E.O.-based estimation of transpiration and crop water requirements for vineyards: a case study in southern Italy

An efficient use of water for irrigation is a challenging task. From an agronomical point of view, it requires establishing the optimal amount of water to be supplied, at the correct time, based on phenological phase and water stress spatial distribution. Indeed, the knowledge of the actual water stress is essential for agronomic decisions, vineyards need to be managed to maintain a moderate water stress, thus allowing to optimize berries quality and quantity. Methods for quickly quantifying where, when and in what extent, vines begin to experience water stress are beneficial. Traditional point based methodologies, such those based on Scholander pressure chamber, even if well established are time expensive and do not give a comprehensive picture of the vineyard water deficit. Earth Observation (E.O.) based methodologies promise to achieve a synoptic overview of the water stress. Some E.O. data, indeed, sense the territory in the thermal part of the spectrum and, as it is well recognized, leaf radiometric temperature is related to the plant water status. However, current satellite sensors have not detailed enough spatial resolution to detect pure canopy pixels; thus, the pixel radiometric temperature characterizes the whole soil-vegetation system, and in variable proportions. On the other hand, due to limits in the actual crop dusters, there is no need to characterize the water stress distribution at plant scale, and a coarser spatial characterization would be sufficient. The research aims to assess to what extent: 1) E.O. based canopy radiometric temperature can be used, straightforwardly, to detected plant water status; 2) E.O. based canopy transpiration, would be more suitable (or not) to describe the spatial variability in plant water stress. To these aims: 1) radiometric canopy temperature measured in situ, and derived from a two-source energy balance model applied on airborne data, were compared with in situ leaf water potential from freshly cut leaves; 2) two source energy balance components were validated trough flux tower measures, then, the actual canopy latent heat flux is compared to in situ leaf water potential.