Abstract
Machine Learning (ML) progressed significantly in the last decade, evolving the computer-based learning/prediction paradigm to a much more effective class of models known as Deep learning (DL). Since then, hyperspectral data processing relying on DL approaches is getting more popular, competing with the traditional classification techniques. In this paper, a valid ML/DL-based works applied to hyperspectral data processing is reviewed in order to get an insight regarding the approaches available for the effective meaning extraction from this type of data. Next, a general DL-based methodology focusing on hyperspectral data processing to provide farmers and winemakers effective tools for earlier threat detection is proposed.

Abstract
This study aimed to characterize vineyard vegetation thorough multi-temporal monitoring using a commercial low-cost rotary-wing unmanned aerial vehicle (UAV) equipped with a consumer-grade red/green/blue (RGB) sensor. Ground-truth data and UAV-based imagery were acquired on nine distinct dates, covering the most significant vegetative growing cycle until harvesting season, over two selected vineyard plots. The acquired UAV-based imagery underwent photogrammetric processing resulting, per flight, in an orthophoto mosaic, used for vegetation estimation. Digital elevation models were used to compute crop surface models. By filtering vegetation within a given height-range, it was possible to separate grapevine vegetation from other vegetation present in a specific vineyard plot, enabling the estimation of grapevine area and volume. The results showed high accuracy in grapevine detection (94.40%) and low error in grapevine volume estimation (root mean square error of 0.13 m and correlation coefficient of 0.78 for height estimation). The accuracy assessment showed that the proposed method based on UAV-based RGB imagery is effective and has potential to become an operational technique. The proposed method also allows the estimation of grapevine areas that can potentially benefit from canopy management operations.

Abstract
This article is devoted to the problem of training cyclists from a system approach. Technologies were used to monitor and evaluate in an integrated way the physical form, load parameters and level of functional capabilities of the athlete's body. For correlation between the physiological indices and performance, data from cardiac activity (ECG), muscle activity (EMG and temperature), respiratory processes (oximetry), as well as data from the environment where this athlete is inserted (ambient temperature, pressure, humidity).

Abstract
The Aswan High Dam, Egypt, was built in the 1960s and is one of the biggest dams in the world. It stopped the seasonal flood of Nile river allowing the urban expansion of cities/villages and the full year cultivation, producing 10x10(9) kWh of power annually. The dam is located in an area where several earthquakes (M-L<6) occurred from 1981 to 2007. In this paper, we want to identify any potential damage that could be caused to the dam, and assess its overall structural stability using Multi-Temporal InSAR (MT-InSAR). To reach this goal, we process Envisat data from descending orbits acquired between 2003 and 2010. Our initial estimates show relatively small rates (maximum around -3 mm/yr in the satellite Line-Of-Sight) of subsidence, whose implications must be further investigated. In addition, we perform a preliminary stress-strain analysis of the dam using FEL and FEM methods to assess if the detected movements correspond to the expected vertical behavior for such mega-structure.

Abstract
The offset tracking technique based on synthetic aperture radar (SAR) image intensity information can estimate glacier displacement even when glacier velocities are high and the time interval between images is long, allowing for the broad use of this technique in glacier velocity monitoring. Terrestrial laser scanners, a non-contact measuring system, can measure the velocity of a glacier even if there are no control points arranged on a glacier. In this study, six COSMO-SkyMed images acquired between 31 July and 22 December 2016 were used to obtain the glacial movements of five glaciers on the northern slope of the central Himalayas using the offset tracking approach. During the period of image acquirement, a terrestrial laser scanner was used, and point clouds of two periods in a small area at the terminus of the Pingcuoliesa Glacier were obtained. By selecting three fixed areas of the point clouds that have similar shapes across two periods, the displacements of the centers of gravity of the selected areas were calculated by using contrast analyses of feature points. Although the overall low-density point clouds data indicate that the glacial surfaces have low albedos relative to the wavelength of the terrestrial laser scanner and the effect of its application is therefore influenced in this research, the registration accuracy of 0.0023 m/d in the non-glacial areas of the scanner's measurements is acceptable, considering the magnitude of 0.072 m/d of the minimum glacial velocity measured by the scanner. The displacements from the point clouds broadly agree with the results of the offset tracking technique in the same area, which provides further evidence of the reliability of the measurements of the SAR data in addition to the analyses of the root mean squared error of the velocity residuals in non-glacial areas. The analysis of the movement of five glaciers in the study area revealed the dynamic behavior of these glacial surfaces across five periods. G089972E28213N Glacier, Pingcuoliesa Glacier and Shimo Glacier show increasing surface movement velocities from the terminus end to the upper part with elevations of 1500 m, 4500 m, and 6400 m, respectively. The maximum velocities on the glacial surface profiles were 31.69 cm/d, 62.40 cm/d, and 42.00 cm/d, respectively. In contrast, the maximum velocity of Shie Glacier, 50.60 cm/d, was observed at the glacier's terminus. For each period, G090138E28210N Glacier exhibited similar velocity values across the surface profile, with a maximum velocity of 39.70 cm/d. The maximum velocities of G089972E28213N Glacier, Pingcuoliesa Glacier, and Shie Glacier occur in the areas where the topography is steepest. In general, glacial surface velocities are higher in the summer than in the winter in this region. With the assistance of a terrestrial laser scanner with optimized wavelengths or other proper ground-based remote sensing instruments, the offset tracking technique based on high-resolution satellite SAR data should provide more reliable and detailed information for local and even single glacial surface displacement monitoring.

Abstract
In this paper we analyze the subsidence behavior of a coastal area in the province of Málaga (Costa del Sol), southern Spain, in the period 1992-2018 using C-band SAR interferometry. The area comprises several zones of interest where continuous deformation has happened during the analyzed period. Using SAR data from ESA's ERS-1/2, Envisat, and Sentinel-1A/B satellites, and Multi-Temporal InSAR methods we detect and monitor subsidence in highly populated and industrial areas, airport, harbor, as well as local instabilities over a railway line and a highway. In a previous work, we reported a subsidence due to intensive use of groundwater in some populated towns in the period 1992-2009 with maximum line-of-sight (LOS) rates of the order of -11 mm/yr. In this contribution, we confirm the subsidence trend. Furthermore, we detect an increase in the deformation rates for the most recent period (2014-2018), suggesting that the overexploitation of the aquifers has not ceased. © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.