Using long time series of Landsat data to monitor impervious surface dynamics: a case study in the Zhoushan Islands

Abstract

Abstract. Islands are an important part of the marine ecosystem. Increasing impervious surfaces in the Zhoushan Islands due to new development and increased population have an ecological impact on the runoff and water quality. Based on time-series classification and the complement of vegetation fraction in urban regions, Landsat thematic mapper and other high-resolution satellite images were applied to monitor the dynamics of impervious surface area (ISA) in the Zhoushan Islands from 1986 to 2011. Landsat-derived ISA results were validated by the high-resolution Worldview-2 and aerial photographs. The validation shows that mean relative errors of these ISA maps are < 15 %. The results reveal that the ISA in the Zhoushan Islands increased from 19.2 km 2 in 1986 to 86.5 km 2 in 2011, and the period from 2006 to 2011 had the fastest expansion rate of 5.59 km 2 per year. The major land conversions to high densities of ISA were from the tidal zone and arable lands. The expansions of ISA were unevenly distributed and most of them were located along the periphery of these islands. Time-series maps revealed that ISA expansions happened continuously over the last 25 years. Our analysis indicated that the policy and the topography were the dominant factors controlling the spatial patterns of ISA and its expansions in the Zhoushan Islands. With continuous urbanization processes, the rapid ISA expansions may not be stopped in the near feature.

Evaluation of Coastline Changes under Human Intervention Using Multi-Temporal High-Resolution Images: A Case Study of the Zhoushan Islands, China

“…Relative to the islands that functioned as marine tourism and marine research, the islands functioning as port logistics or harbor industry might have suffered from faster development under human influence. Due to differences in location, geomorphology, and population among these islands, they had different urban expansions [24]. In the late 1980s, the Chinese government proposed and started to organize the National Marine Functional Zoning Plan.…”

“…During the past few decades, the Zhoushan coast has been subject to rapid changes under quickened urbanization process [23,24]. At the same time, the rate of sea-level rise along the Zhoushan coast had reached 2.8 mm/year during 1980 and 2010, and is projected to rise by 20-40 cm by the year 2050, considering that the elevation along the Zhoushan coast is only 1.5-5.0 m [25].…”

Influence of Data Source and Training Size on Impervious Surface Areas Classification Using VHR Satellite and Aerial Imagery Through an Object-Based Approach

“…ISAs lead to impacts on the environment by means of influencing hydrological and energy balances, affect the biological composition and functioning of ecosystems, and change the thermal properties of the soil [1], [2]. Therefore, the classification and monitoring of ISAs provide essential information needed in order to understand natural changes in ecosystems, especially in urban areas [3], [4]. Additionally, since ISAs constitute a good indicator of the degree of urbanization for a certain area, its classification in coastal areas is crucial to evaluate the effect of "coastal squeeze" (caused by artificially stabilized seafronts on sedimentary coastlines that inhibit the natural behavior of the coastal sedimentary processes) on coastal erosion processes.…”

Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine

“…Utilizing the open and dense Landsat archive data for the land cover studies has been attracting lots of attention (DeVries, Verbesselt, Kooistra, & Herold, 2015; Dong et al, 2015; Schroeder et al, 2014; Schroeder, Wulder, Healey, & Moisen, 2011; Zhu, Woodcock, Holden, & Yang, 2015). For example, time series Landsat data have been used for separating cropland and pasture (Müller, Rufin, Griffiths, Barros Siqueira, & Hostert, 2015), forest disturbance (Masek et al, 2013; Zhu, Woodcock, & Olofsson, 2012), impervious surface dynamics (Zhang, Pan, Chen, Zhan, & Mao, 2013), glacier extent changes (Yavaşlı, Tucker, & Melocik, 2015), and paddy rice dynamics (Dong et al, 2015; Kontgis, Schneider, & Ozdogan, 2015). Although these efforts have greatly improved the previous land cover and land use change efforts from spatial and temporal domains, these studies all focus on local or limited study areas due to the intensive amount of data processing.…”