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

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.

Coastline Zone Extraction Using Landsat-8 Oli Imagery, Case Study: Bodrum Peninsula, Turkey

“…Density slicing methods for coastline delineation using single band Landsat TM; multiband methods to extract the water area (Du., Z., et al 2012;Mc Feeter, 1996;Xu, 2006;Wang et al, 2017;Feyisa et al, 2014) band rationing (Alesheikh et al, 2007;Niya et al, 2013) classification (Gurglia et al 2006Ekercin 2007;Garcia et al, 2015) on screen digitizing (Goksel et al, 2001;Sameh et al, 2017;Niya et al, 2013) are methods to identify coastline from multispectral satellite images. This study investigates extraction coastline of Bodrum Peninsula with using three commonly used techniques; Automatic Water Extraction Index (AWEI) (Feyisa et al, 2014;Xia et al, 2018;Liu et al, 2017) Iterative Self-Organizing Data Analysis Technique (ISODATA) unsupervised classification technique (Papakonstantinou et al, 2016) and on screen digitizing method in order to determine land-sea boundary line and its length, and area of the Bodrum Peninsula.…”

Analysis of Coastline Extraction from Landsat-8 OLI Imagery

“…The MS image of ZY-3 has a spatial resolution of 5.8 m. The fine spatial resolution ZY-3 MS image was acquired at 2:45 a.m. (UTC) on 12 March 2015, which is really close to the acquisition time of Landsat-8 OLI imagery shown in Figure 1. In this case, tide difference can, therefore, be ignored for similar tide levels between Landsat-8 OLI and ZY-3 MS images [20]. Further information about the specifications of ZY-3 MS image is listed in Table 1.…”

“…is an important port of international economic and cultural exchanges [42]. The increasing connection with the world has pushed the urban development of Ningbo, resulting in rapid coastline position changes during the past decades [20]. The types of Ningbo coast mainly contain bedrock coast, artificial coast and flat sandy coast.…”

“…Previous studies [20,[36][37][38][39][40] have proved that water index method has advantages of universality, user friendliness and low computation cost in coastline extraction, and the common used water index is the normalized difference water index (NDWI) proposed by McFeeters [39]. In this paper, downscaling, pansharpening and water index approaches were used to extract coastlines from Landsat-8 OLI imagery.…”

“…Lira and Taborda [17] summarized the advances of coastline extraction from available free-access satellite imagery, and showed that the Landsat imagery offers the best compromise between potential and availability to understand coastal dynamic features. Chen et al [18] used Landsat MSS and TM MS images to monitor coastline changes in Lingding Bay, and the coastline extends on a coastal stretch of approximately 6 km; Ekercin [19] collected Landsat MSS, TM and ETM+ images between 1975 and 2001 to perform coastline change analysis in a part of the Aegean Sea; Wang et al [20] used Landsat MSS, TM, ETM+ and OLI images for coastline detection along Ningbo City from 1976 to 2015; Pardo-Pascual et al [21] evaluated how the storms impact the sandy beaches and the beach recovery process by describing the coastline positions obtained from Landsat TM and ETM+. Coastlines with special characteristics, such as deltas, exhibit less change in position, and they could be monitored by low resolution of Landsat images, while the coastline of sandy areas with small beaches is difficult to be monitored by low resolution images.…”