A dynamic assessment of Ecological Footprint and Biocapacity in Guangzhou using RS and GIS

被引:0
|
作者
Zhou Tao [1 ,2 ]
Wang Yunpeng [1 ]
Wang Fang [2 ]
机构
[1] Chinese Acad Sci, Guangzhou Inst Geochem, SKLOG, Guangzhou 510640, Guangdong, Peoples R China
[2] Guangzhou Univ, Sch Geog Sci, Guangzhou 510006, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The sustainable urban development research is a hot spot in science, economics, society etc. The Ecological Footprint (EF) method, which originally developed by Wackernagel and Rees in the mid-1990s, is a useful approach to detect the sustainability of the city. The Ecological Footprint (EF) is a measure of human demand on the bioproductive land area that is required to support the resource demands of a given population or specific activities. Comparing with Biocapacity (BC), which represents the bioproductive supply, EF provides a valuable tool to evaluate the. carrying capacity of the earth and human appropriation of resources. Till to now, most Ecological Footprint studies have used statistical data and models to calculate EF and BC at one point in time. As both socio-economic systems and ecological systems are dynamic and their interaction changes over time, time series and future forecasting are much more informative for sustainability science than 'snap shots'. This paper proposes solution to overcome the shortcoming of tradition dynamic model, and then demonstrates the usefulness of these methodological advances by calculating Ecological Footprint and Biocapacity time series for Guangzhou city. First, the concept of ecological footprint, biological capacity, ecological remainder and ecological deficit are introduced. Then we made a time-sequence calculation of the ecological footprints of Guangzhou from during the period 1997 to 2007 with the method based on net primary productivity. Secondly, a dynamic model of SPA (Set Pair Analysis) was built to forecast total EF of Guangzhou city during 2008 to 2015. Thirdly, the combination of RS (Remote Sensing) and GIS (Geographic Information System) technologies are applied to calculate the BC. Then, we utilize a land use change model-Cellular automata (CA)-Geograpbic Information System (GIS) based model to predict the conversion of land use types to simulate the change trend of BC in future. According to prediction results, up to 2015, the per capita EF of Guangzhou would reach 15.6735 gha, which is much larger than that of 2007, on the other hand, the Biocapacity will decrease by 4.5%; the urban ecological environmental load could not respond to the socio-economic circumstances promptly. Finally, to avoid deterioration of ecological environment, the authors put forward a series of countermeasures to uphold the urban ecosystem.
引用
收藏
页码:1480 / +
页数:2
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