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The need to rely on accurate information about the wood biomass available in riparian zones under management, inspired the land reclamation authority of southern Tuscany to develop a research based on the new remote sensing technologies. With this aim, a series of unmanned aerial vehicle (UAV) flight campaigns flanked by ground-data collection were carried out on 5 zones and 15 stream reaches belonging to 3 rivers and 7 creeks, being representative of the whole area under treatment, characterized by a heterogeneous spatial distribution of trees and shrubs of different sizes and ages, whose species' mix is typical of this climatic belt. A careful preliminary analysis of the zones under investigation, based on the available local orthophotos, followed by a quick pilot inspection of the riverbank segments selected for trials, was crucial for choosing the test sites. The analysis of a dataset composed of both measured and remotely sensed acquired parameters allowed a system of four allometric models to be built for estimating the trees' biomass. All four developed models showed good results, with the highest correlation found in the fourth model (Model 4, R2 = 0.63), which also presented the lowest RMSE (0.09 Mg). The biomass values calculated with Model 4 were in line with those provided by the land reclamation authority for selective thinning, ranging from 38.9 to 70.9 Mg ha−1. Conversely, Model 2 widely overestimated the actual data, while Model 1 and Model 3 offered intermediate results. The proposed methodology based on these new technologies enabled an accurate estimation of the wood biomass in a riverbank environment, overcoming the limits of a traditional ground monitoring and improving management strategies to benefit the river system and its ecosystems. [ABSTRACT FROM AUTHOR]

The agricultural and forestry sector is constantly evolving, also through the increased use of precision technologies including Remote Sensing (RS). Remotely biomass estimation (WaSfM) in wood production forests is already debated in the literature, but there is a lack of knowledge in quantifying pruning residues from canopy management. The aim of the present study was to verify the reliability of RS techniques for the estimation of pruning biomass through differences in the volume of canopy trees and to evaluate the performance of an unsupervised segmentation methodology as a feasible tool for the analysis of large areas. Remote sensed data were acquired on four uneven-aged and irregularly spaced chestnut orchards in Central Italy by an Unmanned Aerial Vehicle (UAV) equipped with a multispectral camera. Chestnut geometric features were extracted using both supervised and unsupervised crown segmentation and then applying a double filtering process based on Canopy Height Model (CHM) and vegetation index threshold. The results show that UAV monitoring provides good performance in detecting biomass reduction after pruning, despite some differences between the trees' geometric features. The proposed unsupervised methodology for tree detection and vegetation cover evaluation purposes showed good performance, with a low undetected tree percentage value (1.7%). Comparing crown projected volume reduction extracted by means of supervised and unsupervised approach, R2 ranged from 0.76 to 0.95 among all the sites. Finally, the validation step was assessed by evaluating correlations between measured and estimated pruning wood biomass (Wpw) for single and grouped sites (0.53 < R2 < 0.83). The method described in this work could provide effective strategic support for chestnut orchard management in line with a precision agriculture approach. In the context of the Circular Economy, a fast and cost-effective tool able to estimate the amounts of wastes available as by-products such as chestnut pruning residues can be included in an alternative and virtuous supply chain. [ABSTRACT FROM AUTHOR]

According to the United Nations Educational, Scientific and Cultural Organization (UNESCO) agency, the World Heritage Sites (WHS) inscribed in the World Heritage List (WHL) must be safeguarded with an adequate protection system, in order to guarantee their integrity and authenticity. Currently, many UNESCO sites are threatened by geohazards, but the safeguard of these sites does not seem to be wide-ranging. Looking at the standard list of factors affecting the Outstanding Universal Value (OUV) of WHS, which has been adopted by the World Heritage Committee in 2008, it seems that only "sudden geological events" are considered as factors that undermine the protection of the properties. Furthermore, it is well known that slow-kinematic phenomena can also threaten cultural and natural heritage. This study proposes a satellite InSAR-based procedure to identify and monitor the temporal and spatial evolution of ground deformation related to slow-kinematic geohazards (slow-moving landslides and ground-subsidence). This procedure, applied in this work on the Tuscany Region (Italy), simplify the InSAR products interpretation, making them easily exploitable by the local WHS managers for long-term geohazards monitoring and conservation strategies. These activities, thanks to the main characteristics of the recent Sentinel-1 data (short revisit time, free availability without any restrictions and worldwide coverage), can be defined for each UNESCO site of the world. [ABSTRACT FROM AUTHOR]