Vegetation coverage change of the demonstration area of ecologically friendly development in the Yangtze River Delta, China based on GEE and BRT during 1984-2019.

The demonstration area of ecologically friendly development in the Yangtze River Delta is a major national strategy area, and thus eco-environmental protection should be a priority for the sustainable development. Exploring the spatial-temporal variations of franctional vegetation coverage (FVC) is conducive to accurate assessing the ecological quality of environment, which is of great significance to regional sustainable development. In this study, the characteristics and trends of spatial-temporal variation of vegetation cover during 1984-2019 in the demonstration area were analyzed based on Google Earth Engine (GEE). The effects of different ecological factors on FVC were quantified by the boosted regression tree (BRT). Results showed that,the changing trend of FVC in the study area shifted from decreasing to increasing trend from 1984 to 2019. The spatial distribution of FVC in the study area varied with both stages and regions. FVC was mainly degraded. Compared with the year 1984, the area of vegetation degradation and improvement in 2019 accounted for 49.8% and 12.8%, respectively. The vegetation degradation mainly occurred in the north of Wujiang, south of Jiashan, and northeast of Qingpu. Human activities severely weakened the influence of natural factors on FVC. Our findings suggested that the GEE is an effective tool for monitoring the dynamics of vegetation coverage.

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Vertical expansion makes the structure and pattern of the city more complicated. Traditional two-dimensional landscape pattern cannot completely reflect the ecological structure and functional characteristics of urban landscape. In this study, we used the three-dimensional landscape pattern metrics to quantify the regional three-dimensional landscape pattern, and used boosted regression tree (BRT) machine learning algorithms to comprehensively analyze the interaction between social-environmental factors and urban landscape patterns in the central part of Shanghai. Results showed that high building ratio, mean architecture height, and architecture height standard deviation had higher values in the surrounding area of the inner ring. The number of buildings and landscape shape index were higher in the outer ring than those in other area. Building coverage ratio, floor area ratio and Shannon's diversity index had higher values in the central part, with the metrics of Puxi being generally higher than those of Pudong. Population density and normalized vegetation index (NDVI) interacted most significantly with the three-dimensional landscape pattern, with GDP as the least influential factor. Within a certain range, the three-dimensional landscape pattern metrics increased with larger population density in the social factors, and decreased with lower rate of NDVI and water surface ratio in the environmental factors. Our results demonstrated that the BRT method was effective in quantifying the interaction between landscape pattern and social-environmental factors. Our results help improve the understanding of the relationship between ecological environment and human well-being in the central part of Shanghai and provide a scientific basis for the urban three-dimensional expansion planning.

[Surface water change characteristics of Taihu Lake from 1984-2018 based on Google Earth Engine]. / 基于Google Earth Engine平台的1984­2018年太湖水域变化特征.

Lakes are important fresh water resources. Accurate understanding of lake dynamic changes benefits the sustainable development of water resources and socio-economic development. Based on the Google Earth Engine (GEE), we analyzed the dynamics of Taihu Lake from 1984 to 2018 by adopting the dataset of Joint Research Centre's Global Surface Water and Landsat imagery. The modified normalized difference water index (MNDWI) was used to explore the changes in the area of Taihu Lake in recent 35 years. The results showed that the area of Taihu Lake increased during 1984-2018, with a total increase of 45.31 km2. The area in spring and winter was larger than that in summer. Eastern Taihu Lake was the main part of Taihu Lake showing area change. Compared with 1984, 88.9% of the water area of Taihu Lake in 2018 did not change, and 0.3% of the water area disappeared permanently. Lake area changes were affected by both natural and anthropogenic factors. Agricultural irrigation, fish farming, reclamation of surrounding lakes, water conservancy engineering facilities, and the transformation of land-use types caused the reduction in lake area. Increased annual precipitation and the implementation of environmental protection policies were the main factors for the increases in lake area. The results provide reference for effective sustainable water resource management and verify the feasibility of monitoring long-term surface water change based on the GEE platform.

[A river stretch scale assessment of urban river habitat in the Taihu Lake Basin]. / 基于河段尺度的太湖流域城市河流生境评价.

Under the background of rapid urbanization, the degradation of urban river water environment and ecological function in the Taihu Lake Basin has become increasingly prominent. Consequently, it is particularly important to systematically assess urban river habitat. This study referred to and corrected the British Urban River Survey evaluation system. Based on the characte-ristics of urban rivers in the Taihu Lake Basin, we established the evaluation system of stretch habitat quality index (SHQI) of urban river stretches and analyzed the urban river habitat status and spatial variation in the Taihu Lake Basin. The results showed that the SHQI values of the 50 river stretches ranged between 8 and 21, with 3 river stretches classified as "excellent" habitat level, 6 as "good", 27 as "moderate", 9 as "poor", and 5 as "very poor". The vegetation index in urban river habitats in the Taihu Lake Basin was good, whereas that of the physical habitat and material index were bad. The overall ranking of habitats was Zhenjiang: Huzhou: Hangzhou: Jiaxing: Suzhou: Wuxi: Changzhou. There were significant differences in physical habitats, material indices and pollution indices among different cities. The main stream and the tributary section significantly differed in the material index and pollution index, but not significant for SHQI. The evaluation system constructed in this study reflected the current situation of urban river habitats in the Taihu Lake Basin, and could provide guidance for ecological restoration of urban rivers.