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
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
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.

Abstract
Dams require continuous security and monitoring programs, integrated with visual inspection and testing in dam surveillance programs. New approaches for dam monitoring focus on multi-sensor integration, taking into account emerging technologies such as GNSS, optic fiber, TLS, InSAR techniques, GBInSAR, GPR, that can be used as complementary data in dam monitoring, eliciting causes of dam deformation that cannot be assessed with traditional techniques. This paper presents a Multi-temporal InSAR (MT-InSAR) monitoring of La Viñuela dam (Málaga, Spain), a 96 m height earth-fill dam built from 1982 to 1989. The presented MT-InSAR monitoring system comprises three C-band radar (~5,7 cm wavelength) datasets from the European satellites ERS-1/2 (1992-2000), Envisat (2003-2008), and Sentinel-1A/B (2014-2018). ERS-1/2 and Envisat datasets were processed using StaMPS. In the case of Sentinel-1A/B, two different algorithms were applied, SARPROZ and ISCE-SALSIT, allowing the comparison of the estimated LOS velocity pattern. The obtained results confirm that LaViñuela dam is deforming since its construction, as an earth-fill dam. Maximum deformation rates were measured in the initial period (1992-2000), being around -7 mm/yr (LOS direction) on the coronation of the dam. In the period covered by the Envisat dataset (2003-2008), the average deforming pattern was lower, of the order of -4 mm/yr. Sentinel-1A/B monitoring confirms that the deformation is still active in the period 2014-2018 in the central-upper part of the dam, with maximums of velocity reaching -6 mm/yr. SARPROZ and ISCE-SALSIT algorithms provide similar results. It was concluded that MT-InSAR techniques can support the development of new and more effective means of monitoring and analyzing the health of dams complementing actual dam surveillance systems. © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.

Abstract
Synthetic Aperture Radar Interferometry (InSAR) is a remote sensing technique very effective for the measurement of small displacements of the Earth's surface over large areas at a very low cost in comparison with conventional geodetic techniques. Advanced InSAR time series (Multi-Temporal InSAR or MT-InSAR) algorithms for monitoring and investigating surface displacement on Earth are based on conventional radar interferometry. These techniques allow us to measure deformation with uncertainties of one millimeter per year, interpreting time series of interferometric phases at coherent point scatterers (PS) without the need for human or special equipment presence. By applying InSAR processing techniques to a series of radar images over the same region, it is possible to monitor large areas and detect vertical displacements of ground, and infrastructures on the ground, and therefore identify abnormal or excessive movements indicating potential problems requiring detailed ground investigation. In this paper, we apply the PS-InSAR technique to a dataset of ERS-1/2 and Envisat radar images covering the period 1993-2010, to monitor the northern sector of the Valencia basin (Valencia city and its surroundings). Some subsiding areas were detected, with rates up to -5 mm/yr, whose causes are being investigated.

Abstract
The present paper addresses the use of evolutionary based algorithms for off-line fractional-order controller tuning. In particular, a linearized model of a motor-rotor propulsion device was assumed whose representativeness is supported by laboratorial measurements. Initially, the controller was calibrated, using the devised linear model, by a procedure that uses a cost function defined as the linear combination between the sum of the squared error and the sum of the absolute error. In this work, it was shown that this process can be improved by using an evolutionary based algorithm in order to find the best controller parameters. This strategy allows a more automatic tuning procedure isolating it from the user intervention. Moreover, the results achieved by this process, lead to an improved rotational speed regulation.