Dynamic Monitoring and Analysis of Ecological Quality of Pingtan Comprehensive Experimental Zone, a New Type of Sea Island City, Based on RSEI

Abstract

Islands face increasingly prominent environmental problems with rapid urbanization. Hence, timely and objective monitoring and evaluation of island ecology is of great significance. This study took the Pingtan Comprehensive Experimental Zone (PZ) in the east sea of Fujian Province of China as the research object. Based on remote sensing technology, four Landsat images from 2007 to 2017 and the remote sensing ecological index (RSEI) were used to explore the ecological status and space-time change. The results showed that from 2007 to 2011, the average RSEI decreased from 0.519 to 0.506, indicating that the ecological quality generally showed a slight downward trend, mainly due to large-scale development brought by the construction; by 2014, although the ecology of the original area improved, the overall ecology was still declining with 0.502 mean RSEI mainly because of large-scale reclamation projects; by 2017, the average RSEI rebounded to 0.523, which was attributed to the fact that ecological construction and protection were emphasized in the construction of PZ, especially in reclamation areas. In conclusion, the increase of large area bare soil will lead to the decline of regional ecology, but the implementation of scientific ecological planning is conducive to ecological restoration and construction.

Studying the Eco-Environmental Quality Variations of Jing-Jin-Ji Urban Agglomeration and Its Driving Factors in Different Ecosystem Service Regions From 2001 to 2015

“…EEQ assessment is a useful tool to help decision-makers fully understand the natural and anthropogenic effects on the regional eco-environment and provide them with valuable information to formulate corresponding measures [7]. Till now, numerous researches have been conducted to evaluate the regional ecoenvironment at various scales, such as farmland [8], province [6], [9] prefecture-level city [10], urban agglomeration [5], river basin [7], [11], island [12], open pits [13], and tableland [14]. However, based on existing studies, it can be found that few studies have performed at the urban agglomeration scale.…”

“…Under such background, integrating with remote sensing datasets and geographical information system technology to evaluate the regional ecoenvironment has attracted the attention of scholars all over the world [19]. Currently, remote sensing with its advantages of rapid, real-time, and large-scale monitoring has made much progress in land use classification [20]- [23], eco-environment evaluation [12]. For example, the normalized difference vegetation index (NDVI) has been widely used to monitor the regional vegetation situation [24]; the land surface temperature (LST) retrieved from thermal images is applied to evaluate the urban heat island [25].…”

“…For example, the normalized difference vegetation index (NDVI) has been widely used to monitor the regional vegetation situation [24]; the land surface temperature (LST) retrieved from thermal images is applied to evaluate the urban heat island [25]. However, the eco-environment is one complicated system; one single index can hardly evaluate it comprehensively [12], [19]. Therefore, it is common practice to construct one index system to evaluate the regional eco-environment [19].…”

“…To sum up, existing researches mostly more or less selected some indicators which are cumbersome or difficult to obtain. Besides, some studies included too much subjectivity in the EEQ assessment, especially in the indicator weight setting aspect [12]. To make up for these shortcomings, one comprehensive aggregated index, remote sensing ecological index (RSEI) proposed by Xu [31], has made progress.…”

“…To make up for these shortcomings, one comprehensive aggregated index, remote sensing ecological index (RSEI) proposed by Xu [31], has made progress. This index integrated four aspects (greenness, heat, wetness, and dryness), which could reflect the intuitive eco-environment [12]. What is more, the weight of each indicator was set objectively based on the spatial principal component analysis method (SPCA).…”