Monitoring of an embankment dam in southern Spain based on Sentinel-1 Time-series InSAR

Sentinel-1A/B data were freely provided by ESA through Copernicus Programme. Data have been processed by SARPROZ (Copyright (c) 2009-2020 Daniele Perissin). The satellite orbits are from ESA Quality Control Group of Sentinel-1. Research was supported by: (a) ESA Research and Service Support for providing hardware resources employed in this work, (b) ReMoDams project ESP2017-89344-R (AEI/FEDER, UE) from Spanish Ministry of Economy, Industry and Competitiveness, PAIUJA-2019/2020 and CEACTEMA from University of Jaen (Spain), and RNM-282 research group from the Junta de Andalucia (Spain), (c) ERDF through the Operational Programme for Competitiveness and Internationalisation -COMPETE 2020 Programme within project >, and by National Funds through the FCT -Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013, (d) The Ministry of Education, Youth and Sports from the National Programme of Sustainability (NPU II) project > (Czech Republic), and (e) Slovak Grant Agency VEGA under projects No. 2/0100/20.Deformation monitoring is a common practice in most of dams to ensure their structural health and safety status. Systematic monitoring is frequently carried out by means of geotechnical sensors and geodetic techniques that, although very precise an accurate, can be time-consuming and economically costly. Remote sensing techniques are proved to be very effective in assessing deformation. Changes in the structure, shell or associated infrastructures of dams, including adjacent slopes, can be efficiently recorded by using satellite Synthetic Aperture Radar Inteferometry (InSAR) techniques, in particular, Muti-Temporal InSAR time-series analyses. This is a mature technology nowadays but not very common as a routine procedure for dam monitoring. Today, thanks to the availability of spaceborne satellites with high spatial resolution SAR images and short revisit times, this technology is a powerful cost-effective way to monitor millimeter-level displacements of the dam structure and its surroundings. What is more, the potential of the technique is increased since the Copernicus C-band SAR Sentinel-1 satellites are in orbit, due to the high revisit time of 6 days and the free data availability. ReMoDams is a Spanish research project devoted to provide the deformation monitoring of several embankments dams using advances time-series InSAR techniques. One of these dams is The Arenoso dam, located in the province of Cordova (southern Spain). This dam has been monitored using Sentinel-1 SAR data since the beginning of the mission in 2014. In this paper, we show the processing of 382 SLC SAR images both in ascending and descending tracks until March 2019. The results indicate that the main displacement of the dam in this period is in the vertical direction with a rate in the order of -1 cm/year in the central part of the dam body.ESA Research and ServiceReMoDams project (AEI/FEDER, UE) from Spanish Ministry of Economy, Industry and Competitiveness ESP2017-89344-RCEACTEMA from University of Jaen (Spain)Junta de Andalucia European Commission RNM-282ERDF through the Operational Programme for Competitiveness and Internationalisation -COMPETE 2020 Programme POCI-01-0145FEDER-006961National Funds through the FCT -Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) UID/EEA/50014/2013Ministry of Education, Youth and Sports from the National Programme of Sustainability (NPU II) project "IT4Innovations excellence in science" (Czech Republic) LQ1602Vedecka grantova agentura MSVVaS SR a SAV (VEGA) 2/0100/20PAIUJA-2019/202

Assessment of k-Nearest Neighbor and Random Forest classifiers for mapping forest fire areas in central Portugal using Landsat-8, Sentinel-2, and Terra Imagery

Forest fires threaten the population’s health, biomass, and biodiversity, intensifying the desertification processes and causing temporary damage to conservation areas. Remote sensing has been used to detect, map, and monitor areas that are affected by forest fires due to the fact that the different areas burned by a fire have similar spectral characteristics. This study analyzes the performance of the k-Nearest Neighbor (kNN) and Random Forest (RF) classifiers for the classification of an area that is affected by fires in central Portugal. For that, image data from Landsat-8, Sentinel-2, and Terra satellites and the peculiarities of each of these platforms with the support of Jeffries–Matusita (JM) separability statistics were analyzed. The event under study was a 93.40 km2 fire that occurred on 20 July 2019 and was located in the districts of Santarém and Castelo Branco. The results showed that the problems of spectral mixing, registration date, and those associated with the spatial resolution of the sensors were the main factors that led to commission errors with variation between 1% and 15.7% and omission errors between 8.8% and 20%. The classifiers, which performed well, were assessed using the receiver operating characteristic (ROC) curve method, generating maps that were compared based on the areas under the curves (AUC). All of the AUC were greater than 0.88 and the Overall Accuracy (OA) ranged from 89 to 93%. The classification methods that were based on the kNN and RF algorithms showed satisfactory results.Research was supported by PAIUJA-2019/2020 and CEACTEMA from University of Jaen (Spain), and RNM-282 research group from the Junta de Andalucia (Spain). Special thanks to the four anonymous reviewers for their insightful comments

Analysis of spectral separability for detecting burned areas using Landsat-8 OLI/TIRS images under different biomes in Brazil and Portugal

Data supporting the findings of this study are available in the public domain. Landsat-8 data (https://earthexplorer.usgs.gov/, accessed on 20 April 2020). BDQueimadas vector data (https://queimadas.dgi.inpe.br/queimadas/aq30m/, accessed on 20 April 2020). ICNF burned areas vector data (https://www.icnf.pt/florestas/gfr/gfrgestaoinformacao/dfciinformacaocartgrafica, accessed on 20 April 2020).Fire is one of the natural agents with the greatest impact on the terrestrial ecosystem and plays an important ecological role in a large part of the terrestrial surface. Remote sensing is an important technique applied in mapping and monitoring changes in forest landscapes affected by fires. This study presents a spectral separability analysis for the detection of burned areas using Landsat-8 OLI/TIRS images in the context of fires that occurred in different biomes of Brazil (dry ecosystem) and Portugal (temperate forest). The research is based on a fusion of spectral indices and automatic classification algorithms scientifically proven to be effective with as little human interaction as possible. The separability index (M) and the Reed–Xiaoli automatic anomaly detection classifier (RXD) allowed the evaluation of the spectral separability and the thematic accuracy of the burned areas for the different spectral indices tested (Burn Area Index (BAI), Normalized Burn Ratio (NBR), Mid-Infrared Burn Index (MIRBI), Normalized Burn Ratio 2 (NBR2), Normalized Burned Index (NBI), and Normalized Burn Ratio Thermal (NBRT)). The analysis parameters were based on spatial dispersion with validation data, commission error (CE), omission error (OE), and the Sørensen–Dice coefficient (DC). The results indicated that the indices based exclusively on the SWIR1 and SWIR2 bands showed a high degree of separability and were more suitable for detecting burned areas, although it was observed that the characteristics of the soil affected the performance of the indices. The classification method based on bitemporal anomalous changes using the RXD anomaly proved to be effective in increasing the burned area in terms of temporal alteration and performing unsupervised detection without relying on the ground truth. On the other hand, the main limitations of RXD were observed in non-abrupt changes, which is very common in fires with low spectral signal, especially in the context of using Landsat-8 images with a 16-day revisit period. The results obtained in this work were able to provide critical information for fire mapping algorithms and for an accurate post-fire spatial estimation in dry ecosystems and temperate forests. The study presents a new comparative approach to classify burned areas in dry ecosystems and temperate forests with the least possible human interference, thus helping investigations when there is little available data on fires in addition to favoring a reduction in fieldwork and gross errors in the classification of burned areas.The article processing charge (APC) was funded by the University of Jaén through the Center for Advanced Studies on Earth Sciences, Energy and Environment CEACTEMA and the University of Minho.Research was supported by the project “Applied Remote Sensing in the Study of Hot Spots in Forests in Brazil and the Iberian Peninsula” from the Department of Cartographic Engineering and Surveying (DECart) of the Federal University of Pernambuco (UFPE/Brazil), by POIUJA-2023/2024 and CEACTEMA from University of Jaén (Spain), and RNM-282 research group from the Junta de Andalucía (Spain). This work was also supported by national funding awarded by FCT—Foundation for Science and Technology, I.P., projects UIDB/04683/2020 and UIDP/04683/2020

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

A Field Procedure for the Assessment of the Centring Uncertainty of Geodetic and Surveying Instruments

The uncertainty evaluation of survey measurements is a daily and essential task in any surveying work. The result of a measurement is, in fact, only complete when accompanied by a statement of its uncertainty. Miscentring, or centring error, is one of the sources of uncertainty in every basic survey measurement which may have a great effect on horizontal angle measurement for short distances. In the literature, different terms and values are considered to refer to this source of uncertainty. Standard ISO 17123 provides different procedures for assessing the measurement uncertainty of geodetic and surveying instruments, with the aim of checking their suitability for the intending and immediate task in field conditions. ISO 17123 is aware of the importance of uncertainty in the instrument centring, but it does not propose any standardised procedure for its assessment. In this study, we propose such a procedure following a Type A evaluation (through the statistical analysis of series of observations), avoiding using values from Type B evaluations (from manufacturer’s specifications, handbooks, personal experiences, etc.) that could be unsuitable for the conditions of the task. Uncertainty can be individualised for a particular instrument (which includes the plummet type), ground mark, operator, and other factors on which the results could be dependent. The testing methodology includes a configuration of the test field, measurements, and calculation, following the structure of each part of the standard ISO 17123. An experimental application is included with two different total stations, which also includes a statistical analysis of the results.The work of J.R.-R. was funded by the Vice Chancellor of Relations with Society and Labour Insertion of the University of Jaén (Grant No. 06190505N5 IFT1). The article processing charge (APC) was funded by the Research Groups “Ingeniería Cartográfica” and “Microgeodesia Jaén” (Grant Nos. PAIDI-TEP-164 and PAIDI-RNM-282 from the Regional Government of Andalucía) which also received financial support from PAIUJA R5/1/2017 of the University of Jaén

Una perspectiva de las clases prácticas en Didáctica de las Matemáticas

La mejora de la calidad de la docencia universitaria constituye un difícil reto al que debe dar respuesta el sistema universitario. Conscientes de esta necesidad, los autores, después de múltiples sesiones de trabajo conjunto y de búsqueda sistemática en diversas fuentes de conocimiento, realizan una propuesta docente para las clases prácticas de Didáctica de la Matemática en la formación inicial de las Titulaciones de Maestro

Factors determining subsidence in urbanized floodplains: evidence from MT‐InSAR in Seville (southern Spain)

Major rivers have traditionally been linked with important human settlements throughout history. The growth of cities over recent river deposits makes necessary the use of multidisciplinary approaches to characterize the evolution of drainage networks in urbanized areas. Since under‐consolidated fluvial sediments are especially sensitive to compaction, their spatial distribution, thickness, and mechanical behavior must be studied. Here, we report on subsidence in the city of Seville (Southern Spain) between 2003 and 2010, through the analysis of the results obtained with the Multi‐Temporal InSAR (MT‐InSAR) technique. In addition, the temporal evolution of the subsidence is correlated with the rainfall, the river water column and the piezometric level. Finally, we characterize the geotechnical parameters of the fluvial sediments and calculate the theoretical settlement in the most representative sectors. Deformation maps clearly indicate that the spatial extent of subsidence is controlled by the distribution of under‐consolidated fine‐grained fluvial sediments at heights comprised in the range of river level variation. This is clearly evident at the western margin of the river and the surroundings of its tributaries, and differs from rainfall results as consequence of the anthropic regulation of the river. On the other hand, this influence is not detected at the eastern margin due to the shallow presence of coarse‐grain consolidated sediments of different terrace levels. The derived results prove valuable for implementing urban planning strategies, and the InSAR technique can therefore be considered as a complementary tool to help unravel the subsidence tendency of cities located over under‐consolidated fluvial deposits. Copyright © 2017 John Wiley & Sons, Ltd.Departamento de Geodinámica, Universidad de Granada, EspañaDepartamento de Ingeniería Cartográfica, Geodésica y Fotogrametría, Universidad de Jaén, EspañaCentro de Estudios Avanzados en Ciencias de la Tierra (CEACTierra), Universidad de Jaén, EspañaInstituto Andaluz de Ciencias de la Tierra, Consejo Superior de Investigaciones Científicas, EspañaInstituto Andaluz de Ciencias de la Tierra, Universidad de Granada, EspañaDepartamento de Ingeniería Civil, Universidad de Granada, EspañaInstitute for Systems and Computer Engineering, Technology and Science, Universidade de Trás‐os‐Montes e Alto Douro, PortugalInstituto Geológico y Minero de España, EspañaDepartment of Radar Technology, Netherlands Organisation for Applied Scientific Research, Países BajosGrupo de Investigación Microgeodesia Jaén, Universidad de Jaén, EspañaDepartment of Geoscience and Remote Sensing, Delft University of Technology, Países Bajo

Monitoring of land subsidence in the city of Recife/Brazil using Sentinel-1 SAR interferometry

[EN] One of the main causes of land subsidence in the world is the exploitation of groundwater above the regeneration capacity of the aquifer systems. However, the rapid urban growth in estuarine areas can also contribute to the development of this phenomenon. An example of this occurs in the city of Recife, northeastern Brazil. The municipality is built on an estuarine plain composed of several rivers (Capibaribe, Beberibe, Tejipió), which formation results from the occupation of humid areas and mangroves. In recent decades, the excessive removal of water resources from the subsoil has caused the reduction of more than 100 meters of the deep aquifer piezometric level in some places. The presence of these factors in Recife may contribute to land subsidence. To detect this phenomenon, the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique was used. The dataset consisted of 135 Sentinel-1A Interferometric Wide (IW) Single Look Complex (SLC) images from September 2016 to April 2021. The images were acquired in descending orbits and VV polarization. The results of the PSInSAR analysis reveal that in Recife there are several areas of land subsidence with a rate close to -15 mm/year. The main occurrence of soil settlement is observed in large recently built areas in the west zone, and small areas in the north zone. Minor cases occur in the southern zone due to the exploitation of groundwater. The identification of these land subsidence areas can help in the study of urban drainage to avoid flooding sites and in the adoption of mitigating measures for the suitable use of underground water resources.Sentinel-1 data were freely provided by ESA through Copernicus Programme. Data have been processed by SARPROZ (Copyright (c) 2009-2022 Daniele Perissin). Research was supported by POIUJA-2021/2022 and CEACTEMA from University of Jaén (Spain), and RNM- 282 research group from the Junta de Andalucía (Spain)Souza, W.; Ruiz-Armenteros, A.; Cabral, J. (2023). Monitoring of land subsidence in the city of Recife/Brazil using Sentinel-1 SAR interferometry. Editorial Universitat Politècnica de València. 439-445. https://doi.org/10.4995/JISDM2022.2022.1389943944

Exploring the Data Fusion of European SAR and Landsat Satellites for Monitoring the Urban Changes in Greater Cairo (Egypt) from 2010 to 2015

Before Arab Spring revolution, Greater Cairo had been the focus of urban growth studies due to its huge increase of population in the last decades, also using remote sensing satellites. Probably, the change in its urban extent may have been affected by the Arab Spring activity since it started in 2011, as it has been discussed by international organisations for which they are trying to get the answer to this phenomenon. This work uses the European Envisat and Sentinel-1A satellites as well as the American Landsat 7 and 8 for creating pre-revolution (2010) and post-revolution (2015) land use maps by combining the different SAR and Multi-Spectral (MS) sensors. By comparing the generated LUC maps, we identify the urban changes that occurred during the past 5 years, giving an answer to the question of the quantification of the urban increase in Greater Cairo.status: publishe

Characterization of Olive Oil Tourism as a Type of Special Interest Tourism: An Analysis from the Tourist Experience Perspective

Olive oil tourism is an emerging activity that is sparking a growing interest among tourists seeking to partake in this experience and the self-fulfilment it offers. An ever-greater number of olive oil mills are diversifying their businesses to incorporate this type of tourism. In this article, olive oil tourism is characterized as a type of special interest tourism (SIT), under a demand-side approach. Based on quantitative research carried out with olive oil tourists, which examined the aspects of the destination they value, as well as their preferences and motivations for consumption, this article proposes four dimensions that are considered key for characterizing olive oil tourism as SIT: experience, sustainability awareness, the promotion of local culture, and the image of status and prestige held by the tourist. This proposal to characterize olive oil tourism as a type of SIT can contribute to the development of more effective and successful marketing strategies that orient olive oil tourism towards services that tourists value and demand. In turn, this will have an impact in terms of wealth creation for rural olive oil producing areas