A new approach to monitor water quality in the Menor sea (Spain) using satellite data and machine learning methods

Environmental Pollution, Год журнала: 2021, Номер 286, С. 117489 - 117489

Опубликована: Май 31, 2021

Язык: Английский

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Coastal Bathymetry Estimation from Sentinel-2 Satellite Imagery: Comparing Deep Learning and Physics-Based Approaches

Remote Sensing, Год журнала: 2022, Номер 14(5), С. 1196 - 1196

Опубликована: Фев. 28, 2022

The ability to monitor the evolution of coastal zone over time is an important factor in knowledge, development, planning, risk mitigation, and overall management. While traditional bathymetry surveys using echo-sounding techniques are expensive consuming, remote sensing tools have recently emerged as reliable inexpensive data sources that can be used estimate depth inversion models. Deep learning a growing field artificial intelligence allows for automatic construction models from has been successfully various Earth observation model applications. In this work, we make use publicly available Sentinel-2 satellite imagery multiple train deep learning-based estimation model. We explore first two complementary approaches, based on color information but also wave kinematics, inputs This offers possibility derive not only clear waters previously done with at common turbid zones. show competitive results state-of-the-art physical method satellite-derived bathymetry, Satellite Shores (S2Shores), demonstrating promising direction worldwide applicability inverse novel observation.

Язык: Английский

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Sentinel-2 Satellites Provide Near-Real Time Evaluation of Catastrophic Floods in the West Mediterranean

Water, Год журнала: 2019, Номер 11(12), С. 2499 - 2499

Опубликована: Ноя. 27, 2019

Flooding is among the most common natural disasters in our planet and one of main causes economic human life loss worldwide. Evidence suggests increase floods at European scale with Mediterranean coast being critically vulnerable to this risk. The devastating event West during second week September 2019 a clear case risk crystallization, when record-breaking flood (locally called “Cold Drop” (Gota Fría)) has swollen into catastrophe southeast Spain surpassing previous all-time records. By using straightforward approach Sentinel-2 twin satellites from Copernicus Programme ACOLITE atmospheric correction processor, an initial approximation delineated flooded zones, including agriculture urban areas, was accomplished quasi-real time. robust flexible requires no ancillary data for rapid implementation. A composite pre- post-flood images obtained identify change detection mask water pixels. identifies not only impacts on land but also ecosystem its services, providing information quality deterioration concentration suspended matter highly sensitive environments. Subsequent occurred large portions Mar Menor, largest coastal lagoon Mediterranean. present study demonstrates potentials brought by free open-data policy Sentinel-2, valuable source synoptic spatio-temporal local or regional support scientists, managers, stakeholders, society general after emergency.

Язык: Английский

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Using Machine-Learning Algorithms for Eutrophication Modeling: Case Study of Mar Menor Lagoon (Spain)

International Journal of Environmental Research and Public Health, Год журнала: 2020, Номер 17(4), С. 1189 - 1189

Опубликована: Фев. 13, 2020

The Mar Menor is a hypersaline coastal lagoon with high environmental value and characteristic example of highly anthropized hydro-ecosystem located in the southeast Spain. An unprecedented eutrophication crisis 2016 2019 abrupt changes quality its waters caused great social alarm. Understanding modeling level indicator, such as chlorophyll-a (Chl-a), benefits management this complex system. In study, we investigate potential machine learning (ML) methods to predict Chl-a. Particularly, Multilayer Neural Networks (MLNNs) Support Vector Regressions (SVRs) are evaluated using target dataset information up nine different water parameters. most relevant input combinations were extracted wrapper feature selection which simplified structure model, resulting more accurate efficient procedure. Although performance validation phase showed that SVR models obtained better results than MLNNs, experimental indicated both ML algorithms provide satisfactory prediction Chl-a concentration, reaching 0.7 R2CV (cross-validated coefficient determination) for best-fit models.

Язык: Английский

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Use of the Sentinel-2 and Landsat-8 Satellites for Water Quality Monitoring: An Early Warning Tool in the Mar Menor Coastal Lagoon

Remote Sensing, Год журнала: 2022, Номер 14(12), С. 2744 - 2744

Опубликована: Июнь 7, 2022

During recent years, several eutrophication processes and subsequent environmental crises have occurred in Mar Menor, the largest hypersaline coastal lagoon Western Mediterranean Sea. In this study, Landsat-8 Sentinel-2 satellites are jointly used to examine evolution of main water quality descriptors during latest ecological crisis 2021, resulting an important loss benthic vegetation unusual mortality events affecting different aquatic species. Several field campaigns were carried out March, July, August, November 2021 measure variables over 10 control points. The validation satellite biogeochemical against on-site measurements indicates precise results algorithms with median errors 0.41 mg/m3 2.04 FNU for chlorophyll-a turbidity, respectively. preprocessing scheme shows consistent performance both satellites; therefore, using them tandem can improve mapping strategies. findings demonstrate suitability methodology capture spatiotemporal distribution turbidity concentration at 10–30 m spatial resolution on a systematic basis cost-effective way. multitemporal products allow identification critical areas close mouth Albujon watercourse beginning process above 3 mg/m3. These innovative tools support decision makers improving current monitoring strategies as early warning systems timely assistance these disasters, thus preventing detrimental conditions lagoon.

Язык: Английский

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The impact of marine pollution on the probability of business failure: A case study of the Mar Menor lagoon

Journal of Environmental Management, Год журнала: 2023, Номер 332, С. 117381 - 117381

Опубликована: Фев. 1, 2023

Язык: Английский

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Sentinel 2 Analysis of Turbidity Patterns in a Coastal Lagoon

Remote Sensing, Год журнала: 2019, Номер 11(24), С. 2926 - 2926

Опубликована: Дек. 6, 2019

Coastal lagoons are transitional ecosystems with complex spatial and temporal variability. Remote sensing tools essential for monitoring unveiling their Turbidity is a water quality parameter used studying eutrophication sediment transport. The objective of this research to analyze the monthly turbidity pattern in shallow coastal lagoon along two years different precipitation regimes. selected study area Albufera de Valencia (Spain). For purpose, we Sentinel 2 images situ data from program Environment General Subdivision regional government. We obtained 2A 2B 2017 2018 processed them SNAP software. results correlation analysis between satellite data, corroborate that reflectance band 5 (705 nm) suitable patterns (average depth 1 m), such as lagoon, even eutrophic conditions. show similar trend wet dry years, which mainly linked irrigation practice rice paddies. High periods higher residence time closed floodgates. However, wind also play an important role distribution turbidity. During storm events, phytoplankton sediments discharged sea, if floodgates remain open. Fortunately, harvesting season, when open, coincides beginning rainy period. Nevertheless, lucky coincidence. It develop conscious management floodgates, because having during rain events can have several negative effects both receiving waters ecosystem. Non-discharged solids may accumulate worsening clogging problems, beaches next will not receive load nourish them.

Язык: Английский

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Role of small-sized phytoplankton in triggering an ecosystem disruptive algal bloom in a Mediterranean hypersaline coastal lagoon

Marine Pollution Bulletin, Год журнала: 2021, Номер 164, С. 111989 - 111989

Опубликована: Янв. 20, 2021

Язык: Английский

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Evaluation of water quality based on UAV images and the IMP-MPP algorithm

Ecological Informatics, Год журнала: 2021, Номер 61, С. 101239 - 101239

Опубликована: Янв. 20, 2021

Язык: Английский

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Synergistic Use of Earth Observation Driven Techniques to Support the Implementation of Water Framework Directive in Europe: A Review

Remote Sensing, Год журнала: 2023, Номер 15(8), С. 1983 - 1983

Опубликована: Апрель 9, 2023

The development of a sustainable water quality monitoring system at national scale remains big challenge until today, acting as hindrance for the efficient implementation Water Framework Directive (WFD). This work provides valuable insights into current state-of-the-art Earth Observation (EO) tools and services, proposing synergistic use innovative remote sensing technologies, in situ sensors, databases, with ultimate goal to support European Member States effective WFD implementation. proposed approach is based on recent research scientific analysis six-year period (2017–2022) after reviewing 71 peer-reviewed articles international journals coupled results 11 European-founded projects related EO WFD. Special focus placed data sources (spaceborne, situ, etc.), sensors use, observed Quality Elements well computer science techniques (machine/deep learning, artificial intelligence, etc.). combination different technologies can offer, among other things, low-cost monitoring, an increase monitored per body, minimization percentage bodies unknown ecological status.

Язык: Английский

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