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Spatio-Temporal Change Detection of Ningbo Coastline Using Landsat Time-Series Images during 1976–2015

TLDR
Observations indicate that forces of nature and human activities were the two important influential factors for the observed coastline change of the Ningbo coast.
Abstract
Ningbo City in Zhejiang Province is one of the largest port cities in China and has achieved high economic development during the past decades. The port construction, land reclamation, urban development and silt deposition in the Ningbo coastal zone have resulted in extensive coastline change. In this study, the spatio-temporal change of the Ningbo coastlines during 1976–2015 was detected and analysed using Landsat time-series images from different sensors, including Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI). Fourteen individual scenes (covering seven phases) of cloud-free Landsat images within the required tidal range of ±63 cm were collected. The ZiYuan-3 (ZY-3) image of 2015 was used to extract the reference coastline for the accuracy assessment. The normalised difference water index (NDWI) and the modified normalized difference water index (MNDWI) were applied to discriminate surface water and land features, respectively. The on-screen digitising approach was then used to further refine the extracted time-series coastlines in the period from 1976 to 2015. Six relevant indices, length, length change, annual length change, fractal dimension (FD), average net shoreline movement (NSM) and average annual NSM, were calculated to analyse and explore the spatio-temporal change features of Ningbo coastlines. Results show that the length of the Ningbo coastlines increased from 910 km to 986 km, and the value of FD increased from 1.09 to 1.12, and the coastline morphology changed from sinuous to straight. The average NSM increased from 187 m to 298 m and the average annual NSM reached 85 m/year, indicating the advance of coastlines towards the sea at a high level. The spatio-temporal change patterns also varied in different areas. In Hangzhou Bay, significant advancement along the coastlines was experienced since 2001 mainly because of urban construction and land reclamation. In Xiangshan Bay, the forces of nature played a major role in coastline dynamics before 2008, whilst port construction, urban construction and island link projections moved the coastlines towards the sea. The coastline changes of Sanmen Bay were affected by the interaction of nature and human activities. All these observations indicate that forces of nature and human activities were the two important influential factors for the observed coastline change. In this case, the coastline complexity variation was considered responsible for various coastline patterns change of the Ningbo coast. In addition, erosion and accretion occurred in turn because of forces of nature and human activities, such as urban development and agricultural exploitation.

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Citations
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Evaluation of Water Indices for Surface Water Extraction in a Landsat 8 Scene of Nepal.

TL;DR: Not a single method was able to extract surface water in the entire scene with better accuracy and the overall accuracy (OA) and kappa coefficient (kappa) was improved, but not satisfactory.
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Combination of Aerial, Satellite, and UAV Photogrammetry for Mapping the Diachronic Coastline Evolution: The Case of Lefkada Island

TL;DR: The results indicated that the southwest shoreline of Lefkada Island is under dynamic equilibrium, which is strongly controlled by geological parameters, such as subsidence of the studied shoreline during co-seismic deformation and mass wasting.
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Analysis of Coastline Extraction from Landsat-8 OLI Imagery

TL;DR: In this paper, Wu et al. proposed three strategies: (1) Strategy 1 uses the traditional water index method to extract coastline directly from original 30 m Landsat-8 multispectral (MS) image; (2) Strategy 2 extracts coastlines from 15 m fused MS images generated by integrating 15 m panchromatic (PAN) band and 30 m MS image with ten pansharpening algorithms; (3) Strategy 3 first downscales the PAN band to a finer spatial resolution (e.g., 7.5 m) band, and then
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Integration of multi-parametric fuzzy analytic hierarchy process and GIS along the UNESCO World Heritage: a flood hazard index, Mombasa County, Kenya

TL;DR: In this paper, a framework of multi-criteria analysis incorporating geographic information system, fuzzy analytic hierarchy process, and bivariate statistics-based methods was developed for flood hazard index determination.
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Examining Land Cover and Greenness Dynamics in Hangzhou Bay in 1985–2016 Using Landsat Time-Series Data

TL;DR: Coastal reclamation did not alleviate local cropland occupation, but prompted the vegetation greenness of the reclaimed area, and most of the inland area showed a browning trend.
References
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Journal ArticleDOI

The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features

TL;DR: The Normalized Difference Water Index (NDWI) as mentioned in this paper is a new method that has been developed to delineate open water features and enhance their presence in remotely-sensed digital imagery.
Journal ArticleDOI

Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery

TL;DR: In this paper, the normalized difference water index (NDWI) was modified by substitution of a middle infrared band such as Landsat TM band 5 for the near infrared band used in the NDWI.
Journal Article

A global analysis of human settlement in coastal zones

TL;DR: In this article, the authors combine the updated Gridded Population of the World (GPW2) population distribution estimate for 1990 and lighted settlement imagery with a global digital elevation model (DEM) and a high resolution vector coastline.
Journal ArticleDOI

Shoreline Definition and Detection: A Review

TL;DR: Recently, a third category of shoreline indicators has begun to be reported in the literature, based on the application of imageprocessing techniques to extract proxy shoreline features from digital coastal images that are not necessarily visible to the human eye as mentioned in this paper.
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