Continuously Tracking the Annual Changes of the Hengsha and Changxing Islands at the Yangtze River Estuary from 1987 to 2016 Using Landsat Imagery

Abstract

Abstract:The evolution of estuarine islands is potentially controlled by sediment discharge, tidal currents, sea level rise, and intensive human activities. An understanding of the spatial and temporal changes of estuarine islands is needed for environmental change monitoring and assessment in estuarine and coastal areas. Such information can also help us better understand how estuarine islands respond to sea level rise in the context of global warming. The temporal changes of two estuarine islands in Shanghai near the Yangtze River Estuary were obtained using Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper) images from 1987 to 2016 on an annual scale. First, a composite image was generated by using the multi-temporal Landsat images for each year. Then, a modified normalized difference water index (MNDWI) was applied to the annual estuarine island maps using a threshold segmentation method. Finally, we obtained the temporal changes of the estuarine islands in Shanghai during the period 1987-2016. The results suggest that (1) Landsat TM/ETM+ images can be used for estuarine island mapping and change detection; (2) the two estuarine islands have expanded significantly during the past three decades; (3) human activities are the main driving factor that caused the expansion of the estuarine islands; and (4) the sea level can also partly explain the change in the estuarine islands. This study demonstrates that Landsat data are useful for determining the annual variations in the land area of two estuarine islands in Shanghai during the past 30 years. In the future, other factors and their contributions to estuarine island changes should be further investigated.

Integrating a Three-Level GIS Framework and a Graph Model to Track, Represent, and Analyze the Dynamic Activities of Tidal Flats

“…Based on water body identification results, many efforts have been spent on delineating tidal flats from the satellite images. The conventional methods include linear regression [36], Gaussian function [37], Otsu thresholding [38,39], and frequency thresh-olding [29,40,41]. Compared with the above conventional methods, the RF could classify the cells with respect to multiple indices and their statistical distributions and provide higher robustness [42].…”

Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data

“…In particular, Google Earth Engine (GEE) provides access to large satellite image archives from different sensors in both optical and nonoptical wavelengths, environmental variables, land-cover datasets, topographic and socio-economic datasets and an application programming interface that can be used to access the information contained within the large datasets with high-performance computing resources (Gorelick et al, 2017). GEE has been applied to mapping global water occurrence, global distribution and trajectory of tidal flats, human settlement, urbanization and land-cover changes (Gerben Hagenaars, 2017;Jean-François Pekel, Gorelick, & Belward, 2016;Linli Cui, 2012;Murray et al, 2019;Nan & Lei Ding, 2018;Ran Goldblatt, 2016). To assess shoreline changes, GEE has been used to map the sandy beaches in the world (Arjen Luijendijk et al, 2018).…”

“…Some studies have used pixel-based supervised classification to assess the status of global sandy beaches (Arjen Luijendijk et al, 2018). Long-term analysis of satellite imagery revealed the link between erosion and sediment load in the two islands in the Yangtze River estuarine (Nan & Lei Ding, 2018). Recently, the Tasseled Cap Wetness-Greenness Difference (TCWGD) index has been used within GEE for detecting inundation in wetlands in Landsat imagery (Tang et al, 2016).…”

Continuous Expansions of Yangtze River Islands after The Three Gorges Dam tracked by Landsat data based on Google Earth Engine

“…The GEE platform provides a good opportunity to obtain more insight into the longterm changes in the surfaces land of river islands. A simple cloud score function was applied to avoid the effect of clouds/shadows of Landsat data [27]. A reduction function provided by the GEE was used to generate the annual Landsat images over 1986-2017.…”

“…Actually, some other factors can also influence the observation result of Yangtze River island changes [50]. Extensive human activities such as reclamation and water conservation projects, can alter morphologies of Yangtze islands, such as Chongming Island and Changxing Island [27]. Although sea level rise has been observed around the Yangtze River delta, those coastal islands exhibited expansions owing to coastal reclamations [27]- [31].…”