Accuracy evaluation for coastline extraction from Pléiades imagery based on NDWI and IHS pan-sharpening application

Alcaras, Emanuele; Falchi, Ugo; Parente, Claudio; Vallario, Andrea

doi:10.1007/s12518-021-00411-1

Cited by 20 publications

(12 citation statements)

References 36 publications

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“…Seven periods of high-resolution panchromatic and multispectral historical archived data (Table 1) were collected to ensure comprehensive coverage and accuracy. Subsequently, the panchromatic and multispectral images were fused, radiometrically calibrated, and atmospherically corrected using ENVI 5.3 [47]. The main processing steps involved were as follows:…”

Section: Data Collectionmentioning

confidence: 99%

Changes in the Hydrological Characteristics of the Attabad Landslide-Dammed Lake on the Karakoram Highway

Li,

Yang,

et al. 2024

Water

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Understanding the evolving hydrological characteristics of landslide-induced barrier lakes is crucial for flood control, forecasting, early warning, and safety measures in reservoir areas. This study examines the changes in the hydrological characteristics of the Attabad landslide-dammed lake over the past decade after the occurrence of the landslide, focusing on lake area dynamics and sediment concentration. High-resolution satellite images from QuickBird, Pleiades, and WorldView2 over seven periods were analyzed. The findings indicate that the lake area has gradually decreased, with the center of mass shifting towards the lake dam, indicating a trend towards stability. The suspended sediment in the barrier lake is distributed in a strip running from north to south, then northeast to southwest, with the sediment concentration decreasing from the lake entrance to the dam and from the lake bank to the center. Over time, the average sediment concentration has decreased from 2010 to 2020, with higher concentrations in summer than in winter. Notably, during the 2017–2020 period, the lower-middle parts of the lake experienced a higher sediment concentration, while the dam area witnessed lower concentrations, thereby reducing the sediment impact on the dam. Furthermore, the sediment content in the middle of the dammed lake is relatively high, which may lead to the formation of a new dammed dam in the middle and the division of the original dammed lake into two smaller lakes, which will affect the stability of the dammed lake.

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Section: Data Collectionmentioning

confidence: 99%

Changes in the Hydrological Characteristics of the Attabad Landslide-Dammed Lake on the Karakoram Highway

Li,

Yang,

et al. 2024

Water

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“…NDWIs can be used in the identification of changes in water bodies in coastal areas (Alcaras et al, 2022;Wu et al, 2022). The NDWI formula can be seen in Equation 1.…”

Section: Ndwi Calculation and Change Schemementioning

confidence: 99%

Monitoring Coastal Areas Using Ndwi From Landsat Image Data From 1985 Based on Cloud Computation Google Earth Engine and Apps

Ihsan,

Harto,

Sakti

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The coastal area is an area that has a dense population with a lot of human activities that occur there. Due to environmental changes and human activities, changes often occur in coastal areas ranging from erosion and sedimentation. Changes must continuously be monitored to plan countermeasures due to the occurring phenomena. This study aims to create a website-based application to monitor coastal areas. This study will use Landsat data 5,7,8, and 9 to see changes in coastal areas. The analysis can be provided from 1985 until recent data by integrating four Landsat satellites. The NDWI index (Normalized Difference Wetness Index) analyzes changes occurring in coastal areas and differentiates between water and land area. The analysis is not only in the form of changes that occur in coastal areas but also in time series analysis, and trends that occur at a point can be analyzed using land trend analysis. The resulting website based on Cloud Computation in Google Earth Engine can be seen at the link https://bit.ly/MonitoringPesisir. This website can automatically update, and users can choose the location to monitor. This research is expected to be used by policymakers to monitor and plan the development and regulation of coastal areas.

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“…Due to its advantages, pansharpening has become a more prominent technique in recent years, particularly with the increase in the availability of high-spatial resolution satellite imagery. It has been used in a diverse array of applications, including vegetation monitoring, 3 wetland mapping, 4 change detection in natural ecosystems, 5 object detection, 6 land use mapping, 7 electric vehicle detection from remotely-sensed images, 8 coastline extraction, 9 etc.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of deep learning-based pansharpening methods for improved image classification accuracy

Yilmaz,

Asikoglu

2023

J. Appl. Rem. Sens.

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.Pansharpened images are frequently utilized as base data in image classification applications. Nonetheless, the accuracy of image classification heavily relies on the efficiency of the pansharpening strategy applied. With numerous existing pansharpening approaches available, it becomes challenging for analysts to select the one that yields the best outcome. Recently, the deep learning (DL)-based pansharpening approaches have become popular due to their capabilities. Thus, this study aims at examining the image classification performance of pansharpened images generated by several commonly used DL-based pansharpening algorithms that rely on pre-trained models and comparing them with those of several traditional pansharpening algorithms. The experiments that were conducted in two test sites indicated that the DL-based pansharpening algorithms could be used in various circumstances. It can also be inferred that the DL-based pansharpening algorithms enhanced the image classification accuracy more effectively than many other traditional algorithms. The use of pre-trained models led to robust pansharpening results and, therefore, superior classification accuracies in most cases.

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Accuracy evaluation for coastline extraction from Pléiades imagery based on NDWI and IHS pan-sharpening application

Cited by 20 publications

References 36 publications

Changes in the Hydrological Characteristics of the Attabad Landslide-Dammed Lake on the Karakoram Highway

Changes in the Hydrological Characteristics of the Attabad Landslide-Dammed Lake on the Karakoram Highway

Monitoring Coastal Areas Using Ndwi From Landsat Image Data From 1985 Based on Cloud Computation Google Earth Engine and Apps

Comparative analysis of deep learning-based pansharpening methods for improved image classification accuracy

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