Unmanned Aerial Vehicles (UAV)-based remote sensing offers great possibilities to acquire in a fast and easy way field data for precision agriculture applications. This field of study is rapidly increasing due to the benefits and advantages for farm resources management, particularly for studying crop health. This paper reports some experiences related to the analysis of cultivations (vineyards and tomatoes) with Tetracam multispectral data. The Tetracam camera was mounted on a multi-rotor hexacopter. The multispectral data were processed with a photogrammetric pipeline to create triband orthoimages of the surveyed sites. Those orthoimages were employed to extract some Vegetation Indices (VI) such as the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Soil Adjusted Vegetation Index (SAVI), examining the vegetation vigor for each crop. The paper demonstrates the great potential of high-resolution UAV data and photogrammetric techniques applied in the agriculture framework to collect multispectral images and OPEN ACCESS Remote Sens. 2015, 7 4027 evaluate different VI, suggesting that these instruments represent a fast, reliable, and cost-effective resource in crop assessment for precision farming applications.

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Coastal dunes provide the hinterland with natural protection from marine dynamics. The specialized plant species that constitute dune vegetation communities are descriptive of the dune evolution status, which in turn reveals the ongoing coastal dynamics. The aims of this paper were to demonstrate the applicability of a low-cost unmanned aerial system for the classification of dune vegetation, in order to determine the level of detail achievable for the identification of vegetation communities and define the best-performing classification method for the dune environment according to pixel-based and object-based approaches. These goals were pursued by studying the north-Adriatic coastal dunes of Casal Borsetti (Ravenna, Italy). Four classification algorithms were applied to three-band orthoimages (red, green, and near-infrared). All classification maps were validated through ground truthing, and comparisons were performed for the three statistical methods, based on the k coefficient and on correctly and incorrectly classified pixel proportions of two maps. All classifications recognized the five vegetation classes considered, and high spatial resolution maps were produced (0.15 m). For both pixel-based and object-based methods, the support vector machine algorithm demonstrated a better accuracy for class recognition. The comparison revealed that an object approach is the better technique, although the required level of detail determines the final decision.

The paper reports a methodology developed to map energy consumption of the building stock at the urban scale on a GIS environment. Energy consumption has been investigated, focusing on the shift from the individual building scale to the district one with the purpose of identifying larger homogenous energy use areas for addressing policies and plans to improve the quality and the performance levels at the city scale. The urban planning zoning concept was extended to the energy issue to include the energy behavior of each zone that depends on the performance of its individual buildings. The methodology generates GIS maps providing a district scale visualization of energy consumption according to shared criteria. A case study in Bologna city (Italy) is provided. In the specific case, the last update of Emilia-Romagna regional urban planning regulation required a mapping action regarding energy efficiency of homogeneous urban portions defined by the General Urban Plan. The main achieved results are (a) a methodology to identify homogeneous areas for analyzing energy consumption; (b) an updated energy map of Bologna Municipality.

The occurrence of extreme windstorms and increasing heat and drought events induced by climate change leads to severe damage and stress in coniferous forests, making trees more vulnerable to spruce bark beetle infestations. The combination of abiotic and biotic disturbances in forests can cause drastic environmental and economic losses. The first step to containing such damage is establishing a monitoring framework for the early detection of vulnerable plots and distinguishing the cause of forest damage at scales from the management unit to the region. To develop and evaluate the functionality of such a monitoring framework, we first selected an area of interest affected by windthrow damage and bark beetles at the border between Italy and Austria in the Friulian Dolomites, Carnic and Julian Alps and the Carinthian Gailtal. Secondly, we implemented a framework for time-series analysis with open-access Sentinel-2 data over four years (2017–2020) by quantifying single-band sensitivity to disturbances. Additionally, we enhanced the framework by deploying vegetation indices to monitor spectral changes and perform supervised image classification for change detection. A mean overall accuracy of 89% was achieved; thus, Sentinel-2 imagery proved to be suitable for distinguishing stressed stands, bark-beetle-attacked canopies and wind-felled patches. The advantages of our methodology are its large-scale applicability to monitoring forest health and forest-cover changes and its usability to support the development of forest management strategies for dealing with massive bark beetle outbreaks.

A considerable amount of the plastics produced around the world is now dispersed throughout the environment, and in particular in aquatic ecosystems. This can have damaging consequences for plants, animals and human beings. This study investigates some approaches for detection and monitoring of plastics waste in river habitats through multispectral image classification. The data are acquired using a proximity sensor in the electromagnetic spectrum range that includes the ultraviolet, visible and near infrared bands, as for the WorldView‐2 satellite. The in‐depth analysis of the spectral signatures obtained shows typical plastics trends and reflectance values in the near infrared bands. Different classification methods were compared to test their effectiveness for the isolation of plastics samples dispersed in a river habitat. This project represents the first step within a wider research programme, with the aim to define a new approach for future river pollution monitoring.

The San Vitale pinewood (Ravenna, Italy) is part of the remaining wooded areas within the southeastern Po Valley. Several studies demonstrated a widespread saltwater intrusion in the phreatic aquifer caused by natural and human factors in this area as the whole complex coastal system. Groundwater salinization affects soils and vegetation, which takes up water from the shallow aquifer. Changes in groundwater salinity induce variations of the leaf properties and vegetation cover, recognizable by satellite sensors as a response to different spectral bands. A procedure to identify stressed areas from satellite remote sensing data, reducing the expensive and time-consuming ground monitoring campaign, was developed. Multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, acquired between May 2005 and August 2005, were used to calculate Normalized Difference Vegetation Index (NDVI). Within the same vegetation type (thermophilic deciduous forest), the areas with the higher vegetation index were taken as reference to identify the most stressed areas using a statistical approach. To confirm the findings, a comparison was conducted using contemporary groundwater salinity data. The results were coherent in the areas with highest and lowest average NDVI values. Instead, to better understand the behavior of the intermediate areas, other parameters influencing vegetation (meteorological data, water table depth, and tree density) were added for the interpretation of the results.

While indoor comfort represents a widely investigated research topic with relation to sustainable development and energy-demand reduction in the built environment, outdoor comfort remains an open field of study, especially with reference to the impacts of climate change and the quality of life for inhabitants, particularly in urban contexts. Despite the relevant efforts spent in the last few decades to advance the understanding of phenomena and the knowledge in this specific field, which obtained much evidence for the topic's relevance, a comprehensive picture of the studies, as well as a classification of the interconnected subjects and outcomes, is still lacking. This paper reports the outcomes of a literature review aimed at screening the available resources dealing with outdoor thermal comfort, in order to provide a state-of-the-art review that identifies the main topics focused by the researchers, as well as the barriers in defining suitable indexes for assessing thermal comfort in outdoor environments. Although several accurate models and software are available to quantify outdoor human comfort, the evocated state of mind of the final user still remains at the core of this uncertain process.Energies 2020, 13, 2079 2 of 22 more people to use outdoor spaces would bring greater benefits into the physical, environmental, economic and social spheres of the cities [6-9].Scientists worldwide have thus focused their attention on this topic, making available a wide range of tools and methods to assess human thermal outdoor comfort in different climatic contexts. Over 100 biometeorological and thermal stress indexes [10] have been developed, adopting different approaches and rationales, aiming at linking the microclimatic conditions to the perceived sensations.Since the available knowledge on human thermal perception and related evaluation protocols were mainly the ones previously developed for interior spaces and other confined spaces, the assessment of outdoor conditions initially refers to these patterns [11].In fact, human thermal comfort and its assessment were studied since the beginning of the 20th Century, when the first simplified models were developed [12]. The two node model applied thermodynamics principles to energy exchanges between the human body and its thermal environment [13] for the first time during the 1930s, but it is only from the 1960s onwards that researchers were able to analyze the main climatic parameters connected to the perception of thermal comfort (e.g., air temperature, radiant temperature, air humidity, air flow velocity) when the first climate chambers were made available [14]. The cornerstone studies of Givoni [15] and Fanger [16] led in the following years to the identification of new parameters that are currently considered essential elements in the contemporary assessment of thermal comfort. The advances in the physics of heat exchange knowledge gained during the 1980s and the increasing availability of computer tools to support the research activity allowed relevant progress on...