On Monotonicities of Interval Valued Functions

In this paper, we develop the notions of weak/directional monotonicity (developed by Sesma-Sara et al. in terms of the \emph{Kulisch-Miranker order}) and the notion of $G$-monotonicity (introduced by Santiago et al. for $[0,\!1]$) for intervals endowed with admissible orders.Comment: 3 page

Abstract homogeneity of interval-valued functions

In this paper we develop the idea of abstract homogeneity in the context of interval-valued (IV) functions endowed with admissible orders and investigate some of its properties.Comment: 2 page

Monitorización de infraestructuras críticas expuestas a riesgos naturales y antrópicos mediante interferometría radar de satélite

[EN] Synthetic Aperture Radar Interferometry (InSAR) is a remote sensing technique very effective for the measure of smalldisplacements of the Earth’s surface over large areas at a very low cost as compared with conventional geodetictechniques. Advanced InSAR time series algorithms for monitoring and investigating surface displacement on Earth arebased on conventional radar interferometry. These techniques allow us to measure deformation with uncertainties of 1mm/year, interpreting time series of interferometric phases at coherent point scatterers (PS) without the need for humanor special equipment presence on the site. By applying InSAR processing techniques to a series of radar images over thesame region, it is possible to detect line-of-sight (LOS) displacements of infrastructures on the ground and therefore identifyabnormal or excessive movement indicating potential problems requiring detailed ground investigation. A major advantageof this technology is that a single radar image can cover a major area of up to 100 km by 100 km or more as, for example,Sentinel-1 C-band satellites data cover a 250 km wide swath. Therefore, all engineering infrastructures in the area, suchas dams, dikes, bridges, ports, etc. subject to terrain deformation by volcanos, landslides, subsidence due to groundwater,gas, or oil withdrawal could be monitored, reducing operating costs effectively. In this sense, the free and open accessCopernicus Sentinel-1 data with currently up to 6-days revisit time open new opportunities for a near real-time landmonitoring. In addition, the new generation of high-resolution radar imagery acquired by SAR sensors such as TerraSARX,COSMO-SkyMed, and PAZ, and the development of multi-interferogram techniques has enhanced our capabilities inrecent years in using InSAR as deformation monitoring tool. In this paper, we address the applicability of using spaceborneSAR sensors for monitoring infrastructures in geomatics engineering and present several cases studies carried out by ourgroup related to anthropogenic and natural hazards, as well as monitoring of critical infrastructures.[ES] La interferometría radar de apertura sintética (InSAR) es una técnica de teledetección muy eficaz para medir pequeños desplazamientos de la superficie terrestre en grandes áreas a un coste muy pequeño en comparación con las técnicas geodésicas convencionales. Los algoritmos avanzados de series temporales InSAR para monitorizar e investigar el desplazamiento de la superficie terrestre se basan en la interferometría radar convencional. Estas técnicas nos permiten medir la deformación con incertidumbres de un milímetro por año, interpretando series temporales de fases interferométricas en retrodispersores puntuales coherentes (PS) sin necesidad de presencia humana o de equipos especiales en el sitio. Al aplicar técnicas de procesamiento InSAR a una serie de imágenes radar de la misma región, es posible detectar desplazamientos de infraestructuras proyectados en la línea de vista del satélite (line-of-sight o LOS) y, por lo tanto, identificar movimientos anormales o excesivos que indiquen problemas potenciales que requieran una investigación detallada del terreno. Una de las principales ventajas de esta tecnología es que una sola imagen radar puede cubrir un área importante de hasta 100 km por 100 km o más, ya que, por ejemplo, los datos de los satélites de banda C Sentinel-1 cubren una franja de 250 km de ancho. Por lo tanto, todas las infraestructuras civiles de la zona, como presas, diques, puentes, puertos, etc., sujetas a deformaciones del terreno por actividad volcánica, deslizamientos de tierra, hundimientos por extracción de agua subterránea, gas o petróleo, podrían ser monitorizados, reduciendo los costes operativos de manera efectiva. En este sentido, los datos Sentinel-1 de Copernicus, de acceso abierto, con hasta 6 días de tiempo de revisión actual abren nuevas oportunidades para una monitorización terrestre casi en tiempo real. Además, la nueva generación de imágenes radar de alta resolución adquiridas por sensores SAR como TerraSAR-X, COSMOSkyMed y PAZ, y el desarrollo de técnicas multi-interferograma ha mejorado nuestras capacidades en los últimos años en el uso del InSAR como herramienta para el control de deformaciones. En este trabajo se aborda la aplicabilidad del uso de sensores SAR espaciales para la monitorización de infraestructuras civiles en ingeniería geomática y presentamos varios casos de estudio realizados por nuestro grupo relacionados con riesgos naturales y antrópicos, así como de monitorización de infraestructura crítica.ERS-1/2 and Envisat datasets were provided by the European Space Agency (ESA). Sentinel-1A/B data were freely provided by ESA through Copernicus Programme. Data have been processed by DORIS (TUDelft), StaMPS (Andy Hooper), SARPROZ (Copyright (c) 2009-2020 Daniele Perissin), and SNAP (ESA). The satellite orbits are from TUDelft and ESA, as well as from the ESA Quality Control Group of Sentinel-1. Research was supported by [ESA Research and Service Support] for providing hardware resources employed in this work; [Spanish Ministry of Economy, Industry and Competitiveness] under ReMoDams project ESP2017-89344-R (AEI/FEDER, UE); [University of Jaén (Spain)] under PAIUJA-2021/2022 and CEACTEMA; [Junta de Andalucía (Spain)] under RNM-282 research group; [ERDF through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme] within project «POCI-01-0145-FEDER006961»; [National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology)] as part of project UID/EEA/50014/2013; [The Ministry of Education, Youth and Sports from the National Programme of Sustainability (NPU II)] under project «IT4Innovations excellence in science - LQ1602» (Czech Republic); and [Slovak Grant Agency VEGA] under projects No. 2/0100/20Ruiz-Armenteros, A.; Delgado-Blasco, J.; Bakon, M.; Lazecky, M.; Marchamalo-Sacristán, M.; Lamas-Fernández, F.; Ruiz-Constán, A.... (2021). Monitoring critical infrastructure exposed to anthropogenic and natural hazards using satellite radar interferometry. En Proceedings 3rd Congress in Geomatics Engineering. Editorial Universitat Politècnica de València. 137-146. https://doi.org/10.4995/CiGeo2021.2021.12736OCS13714

Deformation monitoring of dam infrastructures via spaceborne MT-InSAR. The case of La Viñuela (Málaga, southern Spain)

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

MT-InSAR and Dam Modeling for the Comprehensive Monitoring of an Earth-Fill Dam: The Case of the Benínar Dam (Almería, Spain)

The Benínar Dam, located in Southeastern Spain, is an earth-fill dam that has experienced filtration issues since its construction in 1985. Despite the installation of various monitoring systems, the data collected are sparse and inadequate for the dam’s lifetime. The present research integrates Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) and dam modeling to validate the monitoring of this dam, opening the way to enhanced integrated monitoring systems. MT-InSAR was proved to be a reliable and continuous monitoring system for dam deformation, surpassing previously installed systems in terms of precision. MT-InSAR allowed the almost-continuous monitoring of this dam since 1992, combining ERS, Envisat, and Sentinel-1A/B data. Line-of-sight (LOS) velocities of settlement in the crest of the dam evolved from maximums of −6 mm/year (1992–2000), −4 mm/year (2002–2010), and −2 mm/year (2015–2021) with median values of −2.6 and −3.0 mm/year in the first periods (ERS and Envisat) and −1.3 mm/year in the Sentinel 1-A/B period. These results are consistent with the maximum admissible modeled deformation from construction, confirming that settlement was more intense in the dam’s early stages and decreased over time. MT-InSAR was also used to integrate the monitoring of the dam basin, including critical slopes, quarries, and infrastructures, such as roads, tracks, and spillways. This study allows us to conclude that MT-InSAR and dam modeling are important elements for the integrated monitoring systems of embankment dams. This conclusion supports the complete integration of MT-InSAR and 3D modeling into the monitoring systems of embankment dams, as they are a key complement to traditional geotechnical monitoring and can overcome the main limitations of topographical monitoring

Routine monitoring of hydraulic infrastructures using the European Ground Motion Service and other satellite radar sensors

Ensuring the safety and operational efficiency of hydraulic infrastructures is paramount, considering the widespread consequences that damages can inflict on people, communities, and the environment. To mitigate risks and prevent significant losses, continuous surveillance is vital. While some damages might appear minor, they can jeopardize the complete operational reliability of dams, leading to substantial economic losses, especially in energy production and related activities. The rapid growth in 20th-century infrastructure development globally has made security monitoring a necessity for numerous civil structures. Rigorous inspection programs, particularly for reservoir dams, are essential for safeguarding citizens and their properties. However, individually monitoring each dam is often impractical due to the associated costs and time constraints, potentially posing safety risks. Fortunately, satellite-based differential radar interferometry (DInSAR) offers an effective and cost-efficient remote sensing solution. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques, particularly utilizing Persistent Scatterers, have proven successful in monitoring various infrastructures, natural phenomena, and geological activities. MT-InSAR provides precise measurements without the need for fieldwork, utilizing historical SAR image archives dating back to the 1990s. Technological advancements, such as the Sentinel-1 C-band with a six-day revisit time until the end of 2021, have enhanced monitoring capabilities. Additionally, commercial radar images in the X-band and the development of multi-interferometric InSAR techniques have opened new avenues for monitoring. This study showcases the adaptation and application of MT-InSAR for monitoring dams and large ponds constructed with loose materials. By assessing vertical displacements and consolidation rates, the technique identifies potential issues, aiding in further field investigations. Case studies involving dams and large reservoirs in Andalusia illustrate the effectiveness of satellite radar interferometry in monitoring their structural stability from space as a routine practice

Sharing economy - short term rental vs property price

Bakalářská práce využívá regresní analýzu k zodpovězení otázky: Má krátkodobý pronájem nemovitostí vliv na cenu nemovitostí v centru Prahy? Empirická studie z roku 2007 ukazuje nejdůležitější faktory, které dokážou měnit ceny nemovitostí. Těmito faktory jsou: hypoteční úroková míra, saturace (počet bytů na 1000 obyvatel), nezaměstnanost, míra ekonomické aktivity, rozvodovost, cena pozemků a HDP. Autor vytváří ekonometrický model pomocí zmíněných faktorů a nabídky krátkodobého pronájmu. Výsledky modelu můžou být použity k předpovědi cen nemovitostí pro další rok a pomoci tím investorům, kteří plánují do trhu s nemovitostmi investovat.The bachelor thesis is using regressive analysis to answer the question: Does Airbnb short-term rental influence the property price in centre of Prague? Empiric study from 2007 shows the most important factors which can change the property prices such as: mortgage rate, saturation (number of properties for 1000 inhabitants), unemployment, rate of economic activity, divorce rate, land price and GDP. Author then create econometric model with these influences and supply of short-term rental. Results of this model can predict the future price of property and help investors who want to invest in property market

The effect of short-term rental of real estate on the price of real estate in Prague.

Krátkodobé pronajímání nemovitostí – Airbnb umožňuje zprostředkování ubytování prakticky kdekoliv na světě. Nicméně přítomnost Airbnb přináší taktéž diskusi o jejím vlivu na trh nemovitostí. Empirické studie se shodují na tom, že krátkodobé pronajímání – Airbnb zvyšuje ceny nemovitostí. V roce 2020 byla činnost krátkodobého pronajímání – Airbnb výrazně omezena pandemii covidu-19. Zde se nabízí otázka: Jaký efekt bude mít snížená aktivita Airbnb na trh nemovitostí? K zodpovězení této otázky je nutné disponovat kvalitními daty. Použitím metody web scraping vznikly v průběhu pandemie dva unikátní datové sety. První datový set obsahuje informace o krátkodobém pronájmu nemovitostí v Praze. Pomocí tohoto datového setu byla Praha rozdělená na skupinu 1, obsahující městské části s vysokým výskytem krátkodobého pronájmu a skupinu 0, která obsahuje městské části s nízkým výskytem krátkodobého pronájmu. Druhý datový set ukazuje vývoj cen dlouhodobého pronájmu nemovitostí a prodejních cen nemovitostí v Praze v průběhu pandemie covidu-19. Výsledky testů stacionarity naznačují, že ceny dlouhodobého pronájmu ve skupině 1 reagovaly během pandemie odlišně než ve skupině 0. U prodejních cen nemovitostí nebyl zaznamenán významný rozdíl mezi skupinami 1 a 0. Tato studie přichází se závěrem, že snížená aktivita Airbnb ovlivnila spíše ceny dlouhodobého pronájmu než prodejní ceny nemovitostí. Otázkou zůstává, zda se tento efekt projeví taktéž v budoucnosti na prodejních cenách nemovitostí.Peer to peer market has helped various individuals to find a required service efficiently and quickly. Airbnb as such example showed its big advantage for intermediation of accommodation for people all around the world. However, the presence of Airbnb brings the discussion about its effect on housing market. Empirical studies recorded positive effect of short-term rental on housing prices. In other words, Airbnb activities do increase housing prices. In 2020 short-term rental Airbnb was disrupted by Covid-19 pandemic. This raises the question: What effect this disruption will have on housing prices? To answer this question two Prague-based datasets were created using web scraping. The first dataset including short-term rental information divided Prague into two parts: the central part with higher number of Airbnb listings (Group 1) and the outer districts less effected by short-term rental (Group 0). This distribution was used in the second dataset which shows information about long-term rental prices and housing selling prices. The stationarity test pointed out that long-term rental prices in Group 1 reacted differently during the pandemic than in Group 0, whereas the difference in housing selling prices reaction between two groups was not significant. This research shows that the decreased activity of short-term rental – Airbnb more probably had an immediate effect on long-term rental prices. The question is whether this effect will appear in the future also in the housing selling prices