Comparison of thresholding methods for shoreline extraction from Sentinel-2 and Landsat-8 imagery: Extreme Lake Salda, track of Mars on Earth

Karaman, Muhittin

doi:10.1016/j.jenvman.2021.113481

Cited by 29 publications

(8 citation statements)

References 70 publications

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“…Seasonal variability in shallow and phreatogenic systems such as La Punta and La Brava lakes is typically related to precipitation behavior, both in situ recharges and the activation of surface flows that run off into the lagoons ( 27 – 29 ), even in arid and hyperarid zones ( 30 , 31 ). This also highlights the effect of evaporation as the main natural discharge of the system ( 4 , 6 ).…”

Section: Discussionmentioning

confidence: 99%

Compositional Changes in Sediment Microbiota Are Associated with Seasonal Variation of the Water Column in High-Altitude Hyperarid Andean Lake Systems

et al. 2023

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In this study, we analyzed the persistence of the water column through satellite images and physicochemical characterization to investigate the composition and diversity in High Andean Lake Systems in a hyperarid environment. In addition to the persistence of the water column, this approach can be used to analyze changes in the morphology of saline accumulations and persistence of snow or ice; for example, for establishing variable plant cover over time and evaluating the microbiota associated with soils with seasonal changes in plants.

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Section: Discussionmentioning

confidence: 99%

Compositional Changes in Sediment Microbiota Are Associated with Seasonal Variation of the Water Column in High-Altitude Hyperarid Andean Lake Systems

et al. 2023

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“…Most previous studies extracted instantaneous waterlines as a common coastline indicator. The most common coastline extraction technique for extracting instantaneous waterlines is remote sensing indices such as the Normalized Difference Water Index (NDWI) [58], modified NDWI (MNDWI) [10,17,61], and Automatic Water Extrac- In satellite images, instantaneous water lines, wet/dry lines, vegetation limits, artificial limits, and morphological lines can be extracted as coastline indicators to discern coastal features. Most previous studies extracted instantaneous waterlines as a common coastline indicator.…”

Section: Coastline Indicatorsmentioning

confidence: 99%

“…Airborne remote sensing data have certain limitations in both time and space coverage, and the emergence of Earth observation (EO) systems has revolutionized how we observe the landscape [15]. Satellite-based imagery, including hyperspectral imaging (HSI), multispectral imaging (MSI) [16,17], SAR [18], and LiDAR [19,20], has been used for the visual analysis of water/land information [15]. With freely available data, the extraction of coastlines from satellite data has been updated with the newest technological developments in remote sensing satellites, such as NASA's Landsat (which revisits every 16 days) and Sentinel-2 (5-10 days of revisit time) launched by ESA.…”

Section: Introductionmentioning

confidence: 99%

An Overview of Coastline Extraction from Remote Sensing Data

Zhou,

Wang,

Zheng

et al. 2023

Remote Sensing

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The coastal zone represents a unique interface between land and sea, and addressing the ecological crisis it faces is of global significance. One of the most fundamental and effective measures is to extract the coastline’s location on a large scale, dynamically, and accurately. Remote sensing technology has been widely employed in coastline extraction due to its temporal, spatial, and sensor diversity advantages. Substantial progress has been made in coastline extraction with diversifying data types and information extraction methods. This paper focuses on discussing the research progress related to data sources and extraction methods for remote sensing-based coastline extraction. We summarize the suitability of data and some extraction algorithms for several specific coastline types, including rocky coastlines, sandy coastlines, muddy coastlines, biological coastlines, and artificial coastlines. We also discuss the significant challenges and prospects of coastline dataset construction, remotely sensed data selection, and the applicability of the extraction method. In particular, we propose the idea of extracting coastlines based on the coastline scene knowledge map (CSKG) semantic segmentation method. This review serves as a comprehensive reference for future development and research pertaining to coastal exploitation and management.

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“…The extraction of coastline from optical images can be performed automatically by means of various methods developed in recent decades. Supervised [15] and unsupervised [16,17] image classification methods, specific tools (Automatic Coastal Extraction Tool [18]) and suitable indices [19] can be used. In the latter approach, many indices are available to detect the coastline in an easy way using satellite images [20][21][22][23][24][25].…”

Section: Of 22mentioning

confidence: 99%

High-Resolution Real-Time Coastline Detection Using GNSS RTK, Optical, and Thermal SfM Photogrammetric Data in the Po River Delta, Italy

Fabris,

Balin,

Monego

2023

Remote Sensing

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High-resolution coastline detection and monitoring are challenging on a global scale, especially in flat areas where natural events, sea level rise, and anthropic activities constantly modify the coastal environment. While the coastline related to the 0-level contour line can be extracted from accurate Digital Terrain Models (DTMs), the detection of the real-time, instantaneous coastline, especially at low tide, is a challenge that warrants further study and evaluation. In order to investigate an efficient combination of methods that allows to contribute to the knowledge in this field, this work uses topographic total station measurements, Global Navigation Satellite System Real-Time Kinematic (GNSS RTK) technique, and the Structure from Motion (SfM) approach (using a low-cost drone equipped with optical and thermal cameras). All the data were acquired at the beginning of 2022 and refer to the areas of Boccasette and Barricata, in the Po River Delta (Northeastern of Italy). The real-time coastline obtained from the GNSS data was validated using the topographic total station measurements; the correspondent polylines obtained from the photogrammetric data (using both automatic extraction and manual restitutions by visual inspection of orhophotos) were compared with the GNSS data to evaluate the performances of the different techniques. The results provided good agreement between the real-time coastlines obtained from different approaches. However, using the optical images, the accuracy was strictly connected with the radiometric changes in the photos and using thermal images, both manual and automatic polylines provided differences in the order of 1–2 m. Multi-temporal comparison of the 0-level coastline with those obtained from a LiDAR survey performed in 2018 provided the detection of the erosion and accretion areas in the period 2018–2022. The investigation on the two case studies showed a better accuracy of the GNSS RTK method in the real-time coastline detection. It can be considered as reliable ground-truth reference for the evaluation of the photogrammetric coastlines. While GNSS RTK proved to be more productive and efficient, optical and thermal SfM provided better results in terms of morphological completeness of the data.

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Comparison of thresholding methods for shoreline extraction from Sentinel-2 and Landsat-8 imagery: Extreme Lake Salda, track of Mars on Earth

Cited by 29 publications

References 70 publications

Compositional Changes in Sediment Microbiota Are Associated with Seasonal Variation of the Water Column in High-Altitude Hyperarid Andean Lake Systems

Compositional Changes in Sediment Microbiota Are Associated with Seasonal Variation of the Water Column in High-Altitude Hyperarid Andean Lake Systems

An Overview of Coastline Extraction from Remote Sensing Data

High-Resolution Real-Time Coastline Detection Using GNSS RTK, Optical, and Thermal SfM Photogrammetric Data in the Po River Delta, Italy

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