Editorial

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Open AccessEditorial

Editorial on Special Issue “Remote Sensing Applications in Coastal Environment”

by Paweł Terefenko, Jacek Lubczonek and Dominik Paprotny

Remote Sens. 2021, 13(23), 4734; https://doi.org/10.3390/rs13234734 - 23 Nov 2021

Cited by 2 | Viewed by 1359

Coastal regions are susceptible to rapid changes as they constitute the boundary between the land and the sea [...] Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

Research

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19 pages, 7365 KiB

Open AccessArticle

Autonomous Lidar-Based Monitoring of Coastal Lagoon Entrances

by Bilal Arshad, Johan Barthelemy and Pascal Perez

Remote Sens. 2021, 13(7), 1320; https://doi.org/10.3390/rs13071320 - 30 Mar 2021

Cited by 6 | Viewed by 2193

Abstract

Intermittently closed and open lakes or Lagoons (ICOLLs) are characterised by entrance barriers that form or break down due to the action of wind, waves and currents until the ocean-lagoon exchange becomes discontinuous. Entrance closure raises a variety of management issues that are [...] Read more.

Intermittently closed and open lakes or Lagoons (ICOLLs) are characterised by entrance barriers that form or break down due to the action of wind, waves and currents until the ocean-lagoon exchange becomes discontinuous. Entrance closure raises a variety of management issues that are regulated by monitoring. In this paper, those issues are investigated, and an automated sensor solution is proposed. Based upon a static Lidar paired with an edge computing device. This solar-powered remote sensing device provides an efficient way to automatically survey the lagoon entrance and estimate the berm profile. Additionally, it estimates the dry notch location and its height, critical factors in the management of the lagoon entrances. Generated data provide valuable insights into landscape evolution and berm behaviour during natural and mechanical breach events. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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20 pages, 6378 KiB

Open AccessArticle

Determining Long-Term Land Cover Dynamics in the South Baltic Coastal Zone from Historical Aerial Photographs

by Andrzej Giza, Paweł Terefenko, Tomasz Komorowski and Paweł Czapliński

Remote Sens. 2021, 13(6), 1068; https://doi.org/10.3390/rs13061068 - 11 Mar 2021

Cited by 3 | Viewed by 1538

Abstract

Coastal regions are dynamic environments that have been the main settlement destinations for human society development for centuries. Development by humans and environmental changes have resulted in intensive land cover transformation. However, detailed spatiotemporal analyses of such changes in the Polish Baltic coastal [...] Read more.

Coastal regions are dynamic environments that have been the main settlement destinations for human society development for centuries. Development by humans and environmental changes have resulted in intensive land cover transformation. However, detailed spatiotemporal analyses of such changes in the Polish Baltic coastal zone have not been given sufficient attention. The aim of the presented work is to fill this gap and, moreover, present a method for assessing indicators of changes in a coastal dune environment that could be an alternative for widely used morphological line indicators. To fulfill the main aim, spatial and temporal variations in the dune areas of the Pomeranian Bay coast (South Baltic Sea) were quantified using remote sensing data from the years 1938–2017, supervised classification, and a geographic information system post-classification change detection technique. Finally, a novel quantitative approach for coastal areas containing both sea and land surface sections was developed. The analysis revealed that for accumulative areas, a decrease in the land area occupied by water was typical, along with an increase in the surface area not covered by vegetation and a growth in the surface area occupied by vegetation. Furthermore, stabilized shores were subject to significant changes in tree cover area mainly at the expense of grass-covered terrains and simultaneous slight changes in the surface area occupied by water and the areas free of vegetation. The statistical analysis revealed six groups of characteristic shore evolutionary trends, of which three exhibited an erosive nature of changes. The methodology developed herein helps discover new possibilities for defining coastal zone dynamics and can be used as an alternative solution to methods only resorting to cross sections and line indicators. These results constitute an important step toward developing a predictive model of coastal land cover changes. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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23 pages, 6238 KiB

Open AccessArticle

Monitoring the Coastal Changes of the Po River Delta (Northern Italy) since 1911 Using Archival Cartography, Multi-Temporal Aerial Photogrammetry and LiDAR Data: Implications for Coastline Changes in 2100 A.D.

by Massimo Fabris

Remote Sens. 2021, 13(3), 529; https://doi.org/10.3390/rs13030529 - 02 Feb 2021

Cited by 15 | Viewed by 3190

Abstract

Interaction between land subsidence and sea level rise (SLR) increases the hazard in coastal areas, mainly for deltas, characterized by flat topography and with great social, ecological, and economic value. Coastal areas need continuous monitoring as a support for human intervention to reduce [...] Read more.

Interaction between land subsidence and sea level rise (SLR) increases the hazard in coastal areas, mainly for deltas, characterized by flat topography and with great social, ecological, and economic value. Coastal areas need continuous monitoring as a support for human intervention to reduce the hazard. Po River Delta (PRD, northern Italy) in the past was affected by high values of artificial land subsidence: even if at low rates, anthropogenic settlements are currently still in progress and produce an increase of hydraulic risk due to the loss of surface elevation both of ground and levees. Many authors have provided scenarios for the next decades with increased flooding in densely populated areas. In this work, a contribution to the understanding future scenarios based on the morphological changes that occurred in the last century on the PRD coastal area is provided: planimetric variations are reconstructed using two archival cartographies (1911 and 1924), 12 multi-temporal high-resolution aerial photogrammetric surveys (1933, 1944, 1949, 1955, 1962, 1969, 1977, 1983, 1990, 1999, 2008, and 2014), and four LiDAR (light detection and ranging) datasets (acquired in 2006, 2009, 2012, and 2018): obtained results, in terms of emerged surfaces variations, are linked to the available land subsidence rates (provided by leveling, GPS—global positioning system, and SAR—synthetic aperture radar data) and to the expected SLR values, to perform scenarios of the area by 2100: results of this work will be useful to mitigate the hazard by increasing defense systems and preventing the risk of widespread flooding. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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23 pages, 7213 KiB

Open AccessArticle

Application of Multiple Geomatic Techniques for Coastline Retreat Analysis: The Case of Gerra Beach (Cantabrian Coast, Spain)

by José Juan de Sanjosé Blasco, Enrique Serrano-Cañadas, Manuel Sánchez-Fernández, Manuel Gómez-Lende and Paula Redweik

Remote Sens. 2020, 12(21), 3669; https://doi.org/10.3390/rs12213669 - 09 Nov 2020

Cited by 9 | Viewed by 2932

Abstract

The beaches of the Cantabrian coast (northern Spain) are exposed to strong winter storms that cause the coastline to recede. In this article, the coastal retreat of the Gerra beach (Cantabria) is analyzed through a diachronic study using the following different geomatic techniques: [...] Read more.

The beaches of the Cantabrian coast (northern Spain) are exposed to strong winter storms that cause the coastline to recede. In this article, the coastal retreat of the Gerra beach (Cantabria) is analyzed through a diachronic study using the following different geomatic techniques: orthophotography of the year 1956; photogrammetric flights from 2001, 2005, 2010, 2014, 2017; Light Detection and Ranging (LiDAR) survey from August 2012; Unmanned Aerial Vehicle (UAV) survey from November 2018; and terrestrial laser scanner (TLS) through two dates per year (spring and fall) from April 2012 to April 2020. With the 17 observations of TLS, differences in volume of the beach and the sea cliff are determined during the winter (November–April) and summer (May–October) periods, searching their relationship with the storms in this eight-year period (2012–2020). From the results of this investigation it can be concluded that the retreat of the base of the cliff is insignificant, but this is not the case for the top of the cliff and for the existing beaches in the Cantabrian Sea where the retreat is evident. The retreat of the cliff top line in Gerra beach, between 1956 and 2020 has shown values greater than 40 m. The retreat in other beaches of the Cantabrian Sea, in the same period, has been more than 200 m. With our measurements, investigations carried out on the retreat of the cliffs on the Atlantic coast have been reinforced, where the diversity of the cliff lithology and the aggressive action of the sea (storms) have been responsible for the active erosion on the face cliff. In addition, this research applied geomatic techniques that have appeared commercially during the period (1956–2020), such as aerial photogrammetry, TLS, LiDAR, and UAV and analyzed the results to determine the precision that could be obtained with each method for its application to similar geomorphological structures. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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20 pages, 2665 KiB

Open AccessArticle

Mapping Coastal Dune Landscape through Spectral Rao’s Q Temporal Diversity

by Flavio Marzialetti, Mirko Di Febbraro, Marco Malavasi, Silvia Giulio, Alicia Teresa Rosario Acosta and Maria Laura Carranza

Remote Sens. 2020, 12(14), 2315; https://doi.org/10.3390/rs12142315 - 18 Jul 2020

Cited by 16 | Viewed by 3606

Abstract

Coastal dunes are found at the boundary between continents and seas representing unique transitional mosaics hosting highly dynamic habitats undergoing substantial seasonal changes. Here, we implemented a land cover classification approach specifically designed for coastal landscapes accounting for the within-year temporal variability of [...] Read more.

Coastal dunes are found at the boundary between continents and seas representing unique transitional mosaics hosting highly dynamic habitats undergoing substantial seasonal changes. Here, we implemented a land cover classification approach specifically designed for coastal landscapes accounting for the within-year temporal variability of the main components of the coastal mosaic: vegetation, bare surfaces and water surfaces. Based on monthly Sentinel-2 satellite images of the year 2019, we used hierarchical clustering and a Random Forest model to produce an unsupervised land cover map of coastal dunes in a representative site of the Adriatic coast (central Italy). As classification variables, we used the within-year diversity computed through Rao’s Q index, along with three spectral indices describing the main components of the coastal mosaic (i.e., Modified Soil-adjusted Vegetation Index 2—MSAVI2, Normalized Difference Water Index 2—NDWI2 and Brightness Index 2—BI2). We identified seven land cover classes with high levels of accuracy, highlighting different covariates as the most important in differentiating them. The proposed framework proved effective in mapping a highly seasonal and heterogeneous landscape such as that of coastal dunes, highlighting Rao’s Q index as a sound base for natural cover monitoring and mapping. The applicability of the proposed framework on updated satellite images emphasizes the procedure as a reliable and replicable tool for coastal ecosystems monitoring. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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28 pages, 11086 KiB

Open AccessArticle

Land Cover Changes and Flows in the Polish Baltic Coastal Zone: A Qualitative and Quantitative Approach

by Elzbieta Bielecka, Agnieszka Jenerowicz, Krzysztof Pokonieczny and Sylwia Borkowska

Remote Sens. 2020, 12(13), 2088; https://doi.org/10.3390/rs12132088 - 29 Jun 2020

Cited by 16 | Viewed by 2754

Abstract

Detecting land cover changes requires timely and accurate information, which can be assured by using remotely sensed data and Geographic Information System(GIS). This paper examines spatiotemporal trends in land cover changes in the Polish Baltic coastal zone, especially the urbanisation, loss of agricultural [...] Read more.

Detecting land cover changes requires timely and accurate information, which can be assured by using remotely sensed data and Geographic Information System(GIS). This paper examines spatiotemporal trends in land cover changes in the Polish Baltic coastal zone, especially the urbanisation, loss of agricultural land, afforestation, and deforestation. The dynamics of land cover change and its impact were discussed as the major findings. The analysis revealed that land cover changes on the Polish Baltic coast have been consistent throughout the 1990–2018 period, and in the consecutive inventories of land cover, they have changed faster. As shown in the research, the area of agricultural land was subject to significant change, i.e., about 40% of the initial 8% of the land area in heterogeneous agriculture was either developed or abandoned at about equal rates. Next, the steady growth of the forest and semi-natural area also changed the land cover. The enlargement of the artificial surface was the third observed trend of land cover changes. However, the pace of land cover changes on the Baltic coast is slightly slower than in the rest of Poland and the European average. The region is very diverse both in terms of land cover, types of land transformation, and the pace of change. Hence, the Polish national authorities classified the Baltic coast as an area of strategic intervention requiring additional action to achieve territorial cohesion and the goals of sustainable development. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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24 pages, 27250 KiB

Open AccessArticle

Measuring Surface Moisture on a Sandy Beach based on Corrected Intensity Data of a Mobile Terrestrial LiDAR

by Junling Jin, Lars De Sloover, Jeffrey Verbeurgt, Cornelis Stal, Greet Deruyter, Anne-Lise Montreuil, Philippe De Maeyer and Alain De Wulf

Remote Sens. 2020, 12(2), 209; https://doi.org/10.3390/rs12020209 - 08 Jan 2020

Cited by 16 | Viewed by 3703

Abstract

Surface moisture plays a key role in limiting the aeolian transport on sandy beaches. However, the existing measurement techniques cannot adequately characterize the spatial and temporal distribution of the beach surface moisture. In this study, a mobile terrestrial LiDAR (MTL) is demonstrated as [...] Read more.

Surface moisture plays a key role in limiting the aeolian transport on sandy beaches. However, the existing measurement techniques cannot adequately characterize the spatial and temporal distribution of the beach surface moisture. In this study, a mobile terrestrial LiDAR (MTL) is demonstrated as a promising method to detect the beach surface moisture using a phase-based Z&F/Leica HDS6100 laser scanner mounted on an all-terrain vehicle. Firstly, two sets of indoor calibration experiments were conducted so as to comprehensively investigate the effect of distance, incidence angle and sand moisture contents on the backscattered intensity by means of sand samples with an average grain diameter of 0.12 mm. A moisture estimation model was developed which eliminated the effects of the incidence angle and distance (it only relates to the target surface reflectance). The experimental results reveal both the distance and incidence angle influencing the backscattered intensity of the sand samples. The standard error of the moisture model amounts to 2.0% moisture, which is considerably lower than the results of the photographic method. Moreover, a field measurement was conducted using the MTL system on a sandy beach in Belgium. The accuracy and robustness of the beach surface moisture derived from the MTL data was evaluated. The results show that the MTL is a highly suitable technique to accurately and robustly measure the surface moisture variations on a sandy beach with an ultra-high spatial resolution (centimeter-level) in a short time span (12 × 200 m per minute). Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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21 pages, 15926 KiB

Open AccessArticle

Combining Satellite Imagery and Numerical Modelling to Study the Occurrence of Warm Upwellings in the Southern Baltic Sea in Winter

by Halina Kowalewska-Kalkowska and Marek Kowalewski

Remote Sens. 2019, 11(24), 2982; https://doi.org/10.3390/rs11242982 - 12 Dec 2019

Cited by 12 | Viewed by 3639

Abstract

Coastal upwelling involves an upward movement of deeper, usually colder, water to the surface. Satellite sea surface temperature (SST) observations and simulations with a hydrodynamic model show, however, that the coastal upwelling in the Baltic Sea in winter can bring warmer water to [...] Read more.

Coastal upwelling involves an upward movement of deeper, usually colder, water to the surface. Satellite sea surface temperature (SST) observations and simulations with a hydrodynamic model show, however, that the coastal upwelling in the Baltic Sea in winter can bring warmer water to the surface. In this study, the satellite SST data collected by the advanced very high resolution radiometer (AVHRR) and the moderate-resolution imaging spectroradiometer (MODIS), as well as simulations with the Parallel Model 3D (PM3D) were used to identify upwelling events in the southern Baltic Sea during the 2010–2017 winter seasons. The PM3D is a three-dimensional hydrodynamic model of the Baltic Sea developed at the Institute of Oceanography, University of Gdańsk, Poland, in which parallel calculations enable high-resolution modelling. A validation of the model results with in situ observations and satellite-derived SST data showed the PM3D to adequately represent thermal conditions in upwelling areas in winter (91.5% agreement). Analysis of the frequency of warm upwellings in 12 areas of the southern Baltic Sea showed a high variability in January and February. In those months, the upwelling was most frequent, both in satellite imagery and in model results, off the Hel Peninsula (38% and 43% frequency, respectively). Upwelling was also frequent off the Vistula Spit, west of the Island of Rügen, and off the eastern coast of Skåne, where the upwelling frequency estimated from satellite images exceeded 26%. As determined by the PM3D, the upwelling frequency off VS and R was at least 25%, while off the eastern coast of Skåne, it reached 17%. The faithful simulation of SST variability in the winters of 2010–2017 by the high-resolution model used was shown to be a reliable tool with which to identify warm upwellings in the southern Baltic Sea. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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16 pages, 3219 KiB

Open AccessArticle

Multi-Temporal Cliff Erosion Analysis Using Airborne Laser Scanning Surveys

by Dagmara Zelaya Wziątek, Paweł Terefenko and Apoloniusz Kurylczyk

Remote Sens. 2019, 11(22), 2666; https://doi.org/10.3390/rs11222666 - 14 Nov 2019

Cited by 17 | Viewed by 3834

Abstract

Rock cliffs are a significant component of world coastal zones. However, rocky coasts and factors contributing to their erosion have not received as much attention as soft cliffs. In this study, two rocky-cliff systems in the southern Baltic Sea were analyzed with Airborne [...] Read more.

Rock cliffs are a significant component of world coastal zones. However, rocky coasts and factors contributing to their erosion have not received as much attention as soft cliffs. In this study, two rocky-cliff systems in the southern Baltic Sea were analyzed with Airborne Laser Scanners (ALS) to track changes in cliff morphology. The present contribution aimed to study the volumetric changes in cliff profiles, spatial distribution of erosion, and rate of cliff retreat corresponding to the cliff exposure and rock resistance of the Jasmund National Park chalk cliffs in Rugen, Germany. The study combined multi-temporal Light Detection and Ranging (LiDAR) data analyses, rock sampling, laboratory analyses of chemical and mechanical resistance, and along-shore wave power flux estimation. The spatial distribution of the active erosion areas appear to follow the cliff exposure variations; however, that trend is weaker for the sections of the coastline in which structural changes occurred. The rate of retreat for each cliff–beach profile, including the cliff crest, vertical cliff base, and cliff base with talus material, indicates that wave action is the dominant erosive force in areas in which the cliff was eroded quickly at equal rates along the cliff profile. However, the erosion proceeded with different rates in favor of cliff toe erosion. The effects of chemical and mechanical rock resistance are shown to be less prominent than the wave action owing to very small differences in the measured values, which proves the homogeneous structure of the cliff. The rock resistance did not follow the trends of cliff erosion revealed by volume changes during the period of analysis. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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29 pages, 9117 KiB

Open AccessArticle

Quantifying Spatiotemporal Patterns and Major Explanatory Factors of Urban Expansion in Miami Metropolitan Area During 1992–2016

by Shaikh Abdullah Al Rifat and Weibo Liu

Remote Sens. 2019, 11(21), 2493; https://doi.org/10.3390/rs11212493 - 25 Oct 2019

Cited by 27 | Viewed by 4377

Abstract

Urban expansion is one of the most dramatic forms of land transformation in the world and it is one of the greatest challenges in achieving sustainable development in the 21^st century. Previous studies analyzed urbanization patterns in areas with rapid urban expansion [...] Read more.

Urban expansion is one of the most dramatic forms of land transformation in the world and it is one of the greatest challenges in achieving sustainable development in the 21^st century. Previous studies analyzed urbanization patterns in areas with rapid urban expansion while urban areas with low to moderate expansion have been overlooked, especially in developed countries. In this study, we examined the spatiotemporal dynamics of urban expansion patterns in South Florida, United States (US) over the last 25 years (1992–2016) using Remote Sensing and GIS techniques. The main goal of this paper was to investigate the degree and spatiotemporal patterns of urban expansion at different administrative level in the study area and how spatiotemporal variance in different explanatory factors influence urban expansion in this region. More specifically, this research quantifies the rates, types, intensity, and landscape metrics of urban expansion in Miami-Fort Lauderdale-Palm Beach, Florida Metropolitan Statistical Area (Miami MSA) which is the 7th largest MSA and 4th largest urbanized area in the US using remote sensing (satellite imageries) data from National Land Cover Datasets (NLCD) and Coastal Change Analysis Program (C-CAP) at 30 m spatial resolution. We further investigated the urban growth patterns at the county and city areas that are located within this MSA to portray the local ‘picture’ of urban growth in this region. Urban expansion in this region can be divided into two time periods: pre-2001 and post-2001 where the former experienced rapid urban expansion and the later had comparatively slow urban expansion. Results suggest that infilling was the dominant type of urban expansion followed by edge-expansion and outlying. Results from landscape metrics represent that newly developed urban lands became more aggregated and simplified in form as the time progressed in the study region. Also, new urban lands were generated away from the east coast and historic cities which eventually created new urban cores. We also used correlation analysis and multiple linear stepwise regression to address major explanatory factors of spatiotemporal change in urban expansion during the study period. Although the influence of factors on urban expansion varied temporally, Population and Distance to Coast were the strongest variables followed by Distance to Roads and Median Income that influence overall urban expansion in the study area. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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21 pages, 8688 KiB

Open AccessArticle

The Reduction Method of Bathymetric Datasets that Preserves True Geodata

by Marta Wlodarczyk-Sielicka, Andrzej Stateczny and Jacek Lubczonek

Remote Sens. 2019, 11(13), 1610; https://doi.org/10.3390/rs11131610 - 06 Jul 2019

Cited by 9 | Viewed by 3781

Abstract

Water areas occupy over 70 percent of the Earth’s surface and are constantly subject to research and analysis. Often, hydrographic remote sensors are used for such research, which allow for the collection of information on the shape of the water area bottom and [...] Read more.

Water areas occupy over 70 percent of the Earth’s surface and are constantly subject to research and analysis. Often, hydrographic remote sensors are used for such research, which allow for the collection of information on the shape of the water area bottom and the objects located on it. Information about the quality and reliability of the depth data is important, especially during coastal modelling. In-shore areas are liable to continuous transformations and they must be monitored and analyzed. Presently, bathymetric geodata are usually collected via modern hydrographic systems and comprise very large data point sequences that must then be connected using long and laborious processing sequences including reduction. As existing bathymetric data reduction methods utilize interpolated values, there is a clear requirement to search for new solutions. Considering the accuracy of bathymetric maps, a new method is presented here that allows real geodata to be maintained, specifically position and depth. This study presents a description of a developed method for reducing geodata while maintaining true survey values. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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Review

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31 pages, 3092 KiB

Open AccessReview

Advances in Remote Sensing Technology, Machine Learning and Deep Learning for Marine Oil Spill Detection, Prediction and Vulnerability Assessment

by Shamsudeen Temitope Yekeen and Abdul-Lateef Balogun

Remote Sens. 2020, 12(20), 3416; https://doi.org/10.3390/rs12203416 - 18 Oct 2020

Cited by 53 | Viewed by 6806

Abstract

Although advancements in remote sensing technology have facilitated quick capture and identification of the source and location of oil spills in water bodies, the presence of other biogenic elements (lookalikes) with similar visual attributes hinder rapid detection and prompt decision making for emergency [...] Read more.

Although advancements in remote sensing technology have facilitated quick capture and identification of the source and location of oil spills in water bodies, the presence of other biogenic elements (lookalikes) with similar visual attributes hinder rapid detection and prompt decision making for emergency response. To date, different methods have been applied to distinguish oil spills from lookalikes with limited success. In addition, accurately modeling the trajectory of oil spills remains a challenge. Thus, we aim to provide further insights on the multi-faceted problem by undertaking a holistic review of past and current approaches to marine oil spill disaster reduction as well as explore the potentials of emerging digital trends in minimizing oil spill hazards. The scope of previous reviews is extended by covering the inter-related dimensions of detection, discrimination, and trajectory prediction of oil spills for vulnerability assessment. Findings show that both optical and microwave airborne and satellite remote sensors are used for oil spill monitoring with microwave sensors being more widely used due to their ability to operate under any weather condition. However, the accuracy of both sensors is affected by the presence of biogenic elements, leading to false positive depiction of oil spills. Statistical image segmentation has been widely used to discriminate lookalikes from oil spills with varying levels of accuracy but the emergence of digitalization technologies in the fourth industrial revolution (IR 4.0) is enabling the use of Machine learning (ML) and deep learning (DL) models, which are more promising than the statistical methods. The Support Vector Machine (SVM) and Artificial Neural Network (ANN) are the most used machine learning algorithms for oil spill detection, although the restriction of ML models to feed forward image classification without support for the end-to-end trainable framework limits its accuracy. On the other hand, deep learning models’ strong feature extraction and autonomous learning capability enhance their detection accuracy. Also, mathematical models based on lagrangian method have improved oil spill trajectory prediction with higher real time accuracy than the conventional worst case, average and survey-based approaches. However, these newer models are unable to quantify oil droplets and uncertainty in vulnerability prediction. Considering that there is yet no single best remote sensing technique for unambiguous detection and discrimination of oil spills and lookalikes, it is imperative to advance research in the field in order to improve existing technology and develop specialized sensors for accurate oil spill detection and enhanced classification, leveraging emerging geospatial computer vision initiatives. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)

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