Ecological footprint analysis for urban agglomeration sustainability in the middle stream of the Yangtze River

Gu, Qian-Ping; Wang, Hongqi; Zheng, Yinan; Zhu, Jingwen; Li, Xiaoke

doi:10.1016/j.ecolmodel.2015.07.022

Cited by 65 publications

(21 citation statements)

References 44 publications

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“…There are a number of lakes and reservoirs, including the two largest freshwater lakes in China: Dongting Lake and Poyang Lake [46]. The region is rich in biodiversity with 11,770 km 2 nature reserves [50], over 400 species of fish and over 7000 species of vegetation. The large population and rapid economic development in the MYRB have led to drastic changes in surface water.…”

Section: Study Areamentioning

confidence: 99%

Long-Term Surface Water Dynamics Analysis Based on Landsat Imagery and the Google Earth Engine Platform: A Case Study in the Middle Yangtze River Basin

et al. 2018

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Dynamics of surface water is of great significance to understand the impacts of global changes and human activities on water resources. Remote sensing provides many advantages in monitoring surface water; however, in large scale, the efficiency of traditional remote sensing methods is extremely low because these methods consume a high amount of manpower, storage, and computing resources. In this paper, we propose a new method for quickly determining what the annual maximal and minimal surface water extent is. The maximal and minimal water extent in the year of 1990, 2000, 2010 and 2017 in the Middle Yangtze River Basin in China were calculated on the Google Earth Engine platform. This approach takes full advantage of the data and computing advantages of the Google Earth Engine’s cloud platform, processed 2343 scenes of Landsat images. Firstly, based on the estimated value of cloud cover for each pixel, the high cloud covered pixels were removed to eliminate the cloud interference and improve the calculation efficiency. Secondly, the annual greenest and wettest images were mosaiced based on vegetation index and surface water index, then the minimum and maximum surface water extents were obtained by the Random Forest Classification. Results showed that (1) the yearly minimal surface water extents were 14,751.23 km2, 14,403.48 km2, 13,601.48 km2, and 15,697.42 km2, in the year of 1990, 2000, 2010, and 2017, respectively. (2) The yearly maximal surface water extents were 18,174.76 km2, 20,671.83 km2, 19,097.73 km2, and 18,235.95 km2, in the year of 1990, 2000, 2010, and 2017, respectively. (3) The accuracies of surface water classification ranged from 86% to 93%. Additionally, the causes of these changes were analyzed. The accuracy evaluation and comparison with other research results show that this method is reliable, novel, and fast in terms of calculating the maximal and minimal surface water extent. In addition, the proposed method can easily be implemented in other regions worldwide.

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Section: Study Areamentioning

confidence: 99%

Long-Term Surface Water Dynamics Analysis Based on Landsat Imagery and the Google Earth Engine Platform: A Case Study in the Middle Yangtze River Basin

et al. 2018

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“…As the most important hub of Chinese transportation and the focal point of the economy, culture, education, and technology in central China, the study area consists of 31 cities of different sizes covering a total land area of 317,000 km 2 , with a population of 121 million, and a gross domestic product (GDP) of 980,552.38 million US$ in 2014, accounting for 3.3%, 8.8% and 8.8% of the whole country, respectively [39]. The region is rich in biodiversity with a total area of biodiversity reserves of 11,770 km 2 [40], and the climate is humid continental and characterized by hot, humid summers and cold winters. …”

Section: Study Areamentioning

confidence: 99%

Satellite Monitoring of Urban Land Change in the Middle Yangtze River Basin Urban Agglomeration, China between 2000 and 2016

Liu

Chen

2017

Remote Sensing

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Detailed studies on the spatiotemporal patterns of urban agglomeration in the Middle Yangtze River Basin (MYRB) are rare. This paper analyzed the spatiotemporal patterns of urbanization in the MYRB using multi-temporal remote sensing data circa 2000, 2008 and 2016 integrated with geographic information system (GIS) techniques and landscape analysis approaches. A multi-level analysis of the rate and intensity, type as well as the landscape changes of urban expansion at regional, prefectural and inner-city levels was performed. Results show that the MYRB experienced rapid urban expansion with an annual expansion rate of 3.199%, especially in the Chang-Zhu-Tan and Poyang Lake metropolitan areas. The small and medium cities presented faster urban expansion than the larger cities with annual growth rates three times the average level. Urban expansion within the three capital cities was further analyzed in detail. It is found that outlying expansion and edge-expansion were the dominant growth patterns at all the three levels. Although urbanization in the MYRB has a remarkable increase in the past sixteen years, its annual growth rate of urban land expansion has fallen behind the three other large urban agglomerations in China as a result. Finally, the spatial evolution of the socioeconomic structure of the MYRB was further explored. It indicated that urban land was distributed mainly along the "northwest-southeast" direction and that the economic spatial interactions among cities showed a pattern of "multi-polarization and fragmentation", which illustrates the weak radiative driving forces of the central cities. The MYRB urban agglomeration faces a great challenge to manage trades-offs between narrowing the intra-regional disparity and maintaining synergetic development among cities.

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“…Only 5.9% of articles (17) during 2007-2010 focused on water footprint modeling, but the proportion rose to 11.0% (48 articles) during 2011-2014 and 14% (103 articles) during 2015-2018. The computer program for irrigation planning and management CROPWAT (FAO, Rome, Italy) [50] of the Food and Agriculture Organization; Stochastic Impact by Regression on Population, Affluence and Technology (STIRPAT) [51]; Logarithmic Mean Divisia Index (LMDI) decomposition model [11]; computable general equilibrium (CGE) model [52]; and ecological footprint model [53] are commonly used in water footprint research. Among them, the CROPWAT model calculates the reference evapotranspiration and crop water and irrigation requirements and distinguishes between the use of blue water and green water.…”

Section: Research Methods and Toolsmentioning

confidence: 99%

A Bibliometrics Review of Water Footprint Research in China: 2003–2018

et al. 2019

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As water security becomes an increasingly important issue, the analysis of the conflict between water supply and demand has gained significance in China. This paper details a bibliometric review of papers published between 2003 and 2018 on the water footprint in China, one of the global hotspots of water resource research. The tendencies and key points of water footprint research were systematically analyzed based on 1564 articles, comprising 1170 original publications in Chinese from the China National Knowledge Infrastructure database and 394 publications in English from the Web of Science database. The results show that the literature associated with water footprint research has expanded significantly. The number of papers published increased from 104 in 2003-2006 to 735 in 2015-2018. Water footprint research has been applied to agricultural, industrial, and regional water resource management to quantify the impact of human activities on water resources and the environment. Water footprint metrics were extracted for regional comparisons. There are obvious regional characteristics of the water footprint in China, but the uncertainty of results makes further investigation necessary. Further water footprint modeling and field experimental research is needed to explore the water-ecological environment under complex systems.

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Ecological footprint analysis for urban agglomeration sustainability in the middle stream of the Yangtze River

Cited by 65 publications

References 44 publications

Long-Term Surface Water Dynamics Analysis Based on Landsat Imagery and the Google Earth Engine Platform: A Case Study in the Middle Yangtze River Basin

Long-Term Surface Water Dynamics Analysis Based on Landsat Imagery and the Google Earth Engine Platform: A Case Study in the Middle Yangtze River Basin

Satellite Monitoring of Urban Land Change in the Middle Yangtze River Basin Urban Agglomeration, China between 2000 and 2016

A Bibliometrics Review of Water Footprint Research in China: 2003–2018

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