Lorenzo Boccia

Estimating Plant Traits of Grasslands from UAV-Acquired Hyperspectral Images: A Comparison of Statistical Approaches

Grassland ecosystems cover around 40% of the entire Earth’s surface. Therefore, it is necessary to guarantee good grassland management at field scale in order to improve its conservation and to achieve optimal growth. This study identified the most appropriate statistical strategy, between partial least squares regression (PLSR) and narrow vegetation indices, for estimating the structural and biochemical grassland traits from UAV-acquired hyperspectral images. Moreover, the influence of fertilizers on plant traits for grasslands was analyzed. Hyperspectral data were collected from an experimental field at the farm Haus Riswick, near Kleve in Germany, for two different flight campaigns in May and October. The collected image blocks were geometrically and radiometrically corrected for surface reflectance. Spectral signatures extracted for the plots were adopted to derive grassland traits by computing PLSR and the following narrow vegetation indices: the MERIS Terrestrial Chlorophyll Index (MTCI), the ratio of the Modified Chlorophyll Absorption in Reflectance and Optimized Soil-Adjusted Vegetation Index (MCARI/OSAVI) modified by Wu, the Red-edge Chlorophyll Index (CIred-edge), and the Normalized Difference Red Edge (NDRE). PLSR showed promising results for estimating grassland structural traits and gave less satisfying outcomes for the selected chemical traits (crude ash, crude fiber, crude protein, Na, K, metabolic energy). Established relations are not influenced by the type and the amount of fertilization, while they are affected by the grassland health status. PLSR is found to be the best strategy, among the approaches analyzed in this paper, for exploring structural and biochemical features of grasslands. Using UAV-based hyperspectral sensing allows for the highly detailed assessment of grassland experimental plots.

Photogrammetry for environmental monitoring: the use of drones and hydrological models for detection of soil contaminated by copper.

Campania Region of Southern Italy has a complex environmental situation, due to geogenic and anthropogenic soil pollution. Some of the pollutants such as copper are mobilized in the organic matter. It has been shown that wetlands provide physical as well as biogeochemical barriers against pollutants. Therefore, the objective of this study was to introduce and test an innovative approach able to predict copper accumulation points at plot scales, using a combination of aerial photos, taken by drones, micro-rill network modelling and wetland prediction indices usually used at catchment scales. Data were collected from an area measuring 4500 m(2) in Trentola Ducenta locality of Caserta Province of southern Italy. The photos processing with a fifth generation software for photogrammetry resulted in a high resolution Digital Elevation Model (DEM), used to study micro-rill processes. The DEM was also used to test the ability of Topographic Index (TI) and the Clima-Topographic Index (CTI) to predict copper sedimentation points at plot scale (0.1-10 ha) by comparing the map of the predicted and the actual copper distribution in the field. The DEM obtained with a resolution of 30 mm showed a high potential for the study of micro-rill processes and TI and CTI indices were able to predict zones of copper accumulation at a plot scale.

Indirect field technology for detecting areas object of illegal spills harmful to human health: application of drones, photogrammetry and hydrological models

The accumulation of heavy metals in agricultural soils is a serious environmental problem. The Campania region in southern Italy has higher levels of cancer risk, presumably due to the accumulation of geogenic and anthropogenic soil pollutants, some of which have been incorporated into organic matter. The aim of this study was to introduce and test an innovative, field-applicable methodology to detect heavy metal accumulation using drone-based photogrammetry and microrill network modelling, specifically to generate wetlands wetlands prediction indices normally applied at large catchment scales, such as a large geographic basin. The processing of aerial photos taken using a hexacopter equipped with fifth-generation software for photogrammetry allowed the generation of a digital elevation model (DEM) with a resolution as high as 30 mm. Not only this provided a high potential for the study of micro-rill processes, but it was also useful for testing and comparing the capability of the topographic index (TI) and the clima-topographic index (CTI) to predict heavy metal sedimentation points at scales from 0.1 to 10 ha. Our results indicate that the TI and CTI indices can be used to predict points of heavy metal accumulation for small field catchments.

Simulating Brown hare (Lepus europaeus Pallas) dispersion: a tool for wildlife management of wide areas

Abstract The second half of the 20th century was characterised by intense processes of urbanisation, industrialisation and agricultural mechanisation, leading to a fragmentation of the agricultural and forest landscape. This, in turn, reduced the bio-permeability of the territory and affected the dispersion of many wild species. Brown hare (Lepus europeus) dispersion is dramatically affected by habitat fragmentation, presence of predators, intense tillage and elevated hunting pressure. Consequently, the only stable populations of hare are often in no-hunting areas where wildlife management is efficient. It is necessary, therefore, to identify not only additional areas suitable for reproduction, but also the most suitable dispersion pathways for hares, in order to optimise management. In the present study, by means of a Geographic Information System (GIS), a deterministic hare suitability model was developed on the basis of a multicriterial approach and fuzzy logic. Subsequently, a friction surface was derived from the suitability map in order to describe the land bio-permeability. Finally, on the basis of species potential, the spread of hares from stable population areas (source areas) to the remaining territory was simulated. The area of study was the province of Viterbo (central Italy). The suitability map showed good discrimination ability (ROC=0.705). The hare dispersion simulation map allowed the potential spreading of this species throughout the provincial territory to be analysed. Isolated or less connected zones were highlighted, allowing the distribution of habitat enhancements, and/or the institution of new no-hunting areas devoted to the reproduction and consequent spread of hares throughout the territory, to be localised. The presented flexible and reiterable methodology could prove useful for wildlife management and hunting planning over a wide area. It would thus provide an important contribution to reducing the importance of animal translocation and favouring an increase in native resources spontaneously spreading throughout a territory. In a more general sense, this study is in accordance with the sustainable land management perspective, meeting the requirements of environmental protection, without compromising the anthropic development of non-urban areas.

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.

Using historical maps to analyze two hundred years of land cover changes: case study of Sorrento peninsula (south Italy)

ABSTRACT Historical maps are effective sources of geographical information and useful for historical and territorial research. In this study, the examination of landscape dynamics on the basis of historical maps over a period of more than 200 years was conducted. The study area is Sorrento peninsula and part of the near Sarno river basin in South Italy. This study provides a general framework for the assessment of the overall quality and accuracy of historical maps. The application of the methodology used in this specific case study can contribute to a better understanding of the dynamics of the landscape in the long term. The derived knowledge can be applied in the planning of the landscape in order to implement correct conservation strategies. The comparison was made on four maps 1817, 1875, 1960, and 2006. Geodetic accuracy of the sheet maps of 1817 and 1875 offer a right basis for a macro analysis of land cover dynamics, evaluating conversion from one land cover category to another. Main transformation, identified in the period between 1875 and 1960, was the disappearance of vineyards, which covered 25% of the total study area in 1875. Agricultural areas increased in this period to cover 57% of the total area.

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.

Nitrate leakage in a high buffalo breeding district (Caserta province)

Abstract Livestock farming in Campania region is largely concentrate in Volturno Garigliano catchments, with a great excess of animals referred to the agricultural land and consequently serious wastewater management problems. The actual strategy of “planned manurig”, up to date used, could be unsatisfactory because spreading is too much expensive, because the agricultural land of the farm are too little related to the number of animals and because we wish in an enlargement of the buffalo breeding in the region. A surveying on nitrate concentration over 150 wells was carried on in 1999-2000 and a repetition on 40 wells was carried in 2005 to asses the change in nitrate leakage. On the basis of the kriging analysis some conclusions were advanced.

A novel approach for detecting agricultural terraced landscapes from historical and contemporaneous photogrammetric aerial photos

Abstract Terraces are the most distinctive sign of human activity on the shape of the Earth surface. Their construction has increased the soils permeability and reduced the slope gradient of mountains since those territories could be exploited both for agricultural and habitable purposes. Over the last decades, they have been the subject of a quick abandonment due to their scarce competitiveness. This has caused some environmental problems, such as soil degradation and hydrological instability. Minori in Italy is one of the most ancient municipalities in the Mediterranean area characterized by the presence of terraces. This paper intends to develop a method for automatic extraction of terraces from historical and contemporaneous aerial photos using an Object-based Image Analysis (OBIA) approach. Historic photos from 1956, acquired by the Geographical Military Institute (IGM), and a contemporaneous block of RGB and multispectral images, taken in 2017 of the study area have been processed to generate a high resolution Digital Elevation Model (DEM) and detailed orthophotos. Subsequently, the OBIA classification has been applied for producing a binary map of terraced and not terraced landscapes for both datasets. Orthophoto resolution was equal to 240 mm, 7 mm and 15 mm for the historical, RGB and multispectral pictures, respectively. DEM resolution results equal to 480 mm and 0.19 mm for the historical and RGB set of data. The R2 between the check points and the estimated values, generated during the metric reconstructions of the two obtained DEMs, resulted equal to 0.99 for both datasets (1956 and 2017). The classification accuracy of the generated binary maps (terraced/not terraced landscapes) were equal to 93% and 98%, respectively. The developed approach looks promising for the historical and contemporaneous datasets. That outcome is essential because it allows to detect terraces position and to compare them over the years in order to analyse their evolution and geomorphological changes.