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Classifying crops using satellite data is a challenge, especially since most crops have similar growth cycles. Due to their different characteristics and chlorophyll content, different crops exhibit subtle differences in their reflectance spectra. This study uses a data-driven approach to build a series of deep learning models to classify 36 different land covers in Steele County and Traill Country, North Dakota, US. A Google Earth Engine workflow was implemented to generate a composite layer containing Sentinel 1 and Sentinel 2 satellite data and surface crop data over the study area. 200,000 sample points were generated on this layer, 140,000 for training dataset, 30,000 for validation dataset and 30,000 for testing dataset. Each sample point contains the values of 12 months of SAR and spectral data. In this way, a two-dimensional feature matrix of the time dimension and spectral band dimension (bands refer to specific wavelengths of data in remote sensing imagery and other type of data like NDVI) is generated for each sample point. The training dataset of the model is composed of the feature matrix of these sample points, and the surface crops as labels correspond to the feature matrix. Since this is a dataset with two-dimensional features, this research uses four deep learning models: Dense Neural Network (DNN), Long short-term memory (LSTM), Convolutional neural network (CNN) and Transformer. Among them, the Transformer model based on the self-attention mechanism performed the best, with a comprehensive accuracy rate of 85%, and the classification accuracy rate of crops with more than 2,000 sample points in the training data set reached more than 90%.

The archaeological site of Tiwanaku is among the most important examples of Bolivian archaeology and UNESCO World Heritage Site since 2000. This works reports a geomatic-based surveying and modelling methodology applied to a ritual receptacle excavated from the semi-subterranean temple in the archaeological complex. A high-resolution 3D survey was conducted through structured-light projection scanning and post-processing operations were carried out to emphasize surface details. Most of the operations were conducted in open-source software, with the aim to establish a quick and repeatable methodology to be applied to similar case studies. The final outputs, consisting of geometry projections (unrolled meshes), digitally enhanced surfaces and vector graphics can support the work of archaeologists in interpreting the iconography depicted on the receptacle and to conduct further studies to shed light about culture and religion of the civilization that inhabited Tiwanaku.

Global warming and changes in Earth’s weather patterns are the main consequences of climate change, and bioclimate discomfort has significant public health problems, especially for the elderly. Normally, the thermal characteristics of urban areas are poor due to a phenomenon known as urban heat island. Mobile and fixed temperature measurements were performed on 19 March 2021 in the city of Bologna, Italy. Mobile measurements took place with a car, along a 75-km transect, starting at 22:16 with a duration of 2 hours and 41 minutes, while fixed measurements were done using 15 present weather stations and also placing five thermometers in the city center. Various interpolation models (i.e., Traditional, Voronoi Tessellation, Global Trends, Triangulated Irregular Networks, Inverse Distance Weighting and Kriging) were applied to correct the mobile measurements using fixed data. Kriging fulfilled the best result with a correlation coefficient of 0.99 compared to the raw temperatures.

In this paper some experiences in 3D modelling of objects with very high-resolution are described, carried out by the DICAM Geomatics group of the University of Bologna in multi-disciplinary contexts within the field of the Civil Engineering. In all the addressed case studies the main aim is the generation of a 3D model of the surface at a sub-millimetric scale, allowing a very accurate characterization of the surface geometry, useful for different purposes. 3D scanning and Structure from Motion photogrammetry have been used to generate the 3D models. In the paper the encountered problems and the adopted solutions in data surveying and processing are underlined, also discussing the added value of very high-resolution 3D modelling in multi-disciplinary activities.

Oenological tannins (OETs) are winemaking processing aids used to facilitate stabilization and fining, to increase the antioxidant capacity, and to promote colour stability of grape juice and wine. A wide variability of pure or mix formulates are available for winemaking purposes, including hydrolysable tannins (gallotannins and ellagitannins), proanthocyanidins from grape skins and seeds (prodelphinidins and procyanidins), and from exotic wood (prorobinetinidins and profisetinidins). In this study, seventeen OETs pure and mix formulates were characterized in terms of polyphenolic content and antioxidant capacity in a model wine and in a red wine after one-month storage, as well as aroma, astringency, and bitterness sensory characteristics in water and red wine. Colour-related features were also analysed in the added red wine after one-month storage. For the first time, correlations among the obtained results in the different matrices were investigated to understand the most suitable OETs for winemaking applications. The results showed a great variability among the formulates studied in terms of phenolic content, which was strictly correlated to their antioxidant capacity. Regarding origin, hydrolysable tannins had the highest antioxidant ability, followed by exotic wood formulates. A strong and positive correlation was found in antioxidant capacity of OETs in model wine and red wine after one-month storage, in particular for ellagitannins, which confirmed also their ability to increase pigments polymerization. By contrast, quebracho tannins resulted the bitterest and most astringent when tasted in water (0.4 g/L), although in-mouth and aromatic descriptors of OETs tasted in water were not correlated with the ones of the added red wine. Therefore, the choice of OETs formulate and its optimal dose requires a characterization in terms of polyphenolic content and antioxidant capacity because these properties were well correlated with those of the added wines in a short storage period, whereas the sensory impact at oenological range doses is mainly dependent on wine features., (Copyright © 2022 Elsevier Ltd. All rights reserved.)