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Trade-off and Synergy Relationships of Ecosystem Services and driving force analysis based on Land Cover Change in Altay Prefecture

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Journal of Resources and Ecology 2021年第6期12卷 777-790页

作者： LIU Hao SHU Chang ZHOU Tingting LIU Peng Chinese Research Academy of Environmental Sciences Beijing 100012China

Altay Prefecture plays a vital role as an ecological barrier in Northwest *** the ecosystem service value is of great significance for promoting regional green high-quality development and maintaining ecological *** on Global ESA land cover data from 2000 to 2015,the trade-off and synergy relationships and driving force factors between ecosystem services in Altay Prefecture were analyzed in this *** analysis produced four main results.(1)The ecosystem service value in Altay Prefecture continued to increase from 113.521×10^(9) yuan in 2000 to 115.777×10^(9) yuan in 2015,for an increase of about 1.98%.(2)The distribution of ecosystem service value had obvious spatial agglomeration characteristics,with hot spot areas mainly concentrated in the"two rivers and one lake"and the mountainous areas in the northwest,while the cold spot areas were mainly the forest and grass-covered areas in the northern mountainous areas and within Jimunai County.(3)The trade-off and synergy relationship among ecosystem services was mainly synergistic,with a total of 77.78% of ecosystem service relative relationships showing a significant positive correlation at the 0.01 level.(4)Economic factors and industrial structure are important factors affecting ecosystem service value in Altay *** service value is positively correlated with per capita GDP and the output value of the tertiary industry,but negatively correlated with the output value of the secondary industry.

关键词： ecosystem service trade-off and synergy relationships Altay Prefecture driving force analysis

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Spatiotemporal dynamics of population density in China using nighttime light and geographic weighted regression method

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International Journal of Digital Earth 2023年第1期16卷 2704-2723页

作者： Wei Guo Jinke Liu Xuesheng Zhao Wei Hou Yunxuan Zhao Yongxing Li Wenbin Sun Deqin Fan College of Geoscience and Surveying Engineering China University of Mining and TechnologyBeijingPeople’s Republic of China Chinese Academy of Surveying&Mapping BeijingPeople’s Republic of China

The distribution and dynamic changes of regional or national population data with long time series are very important for regional planning,resource allocation,government decision-making,disaster assessment,ecological protection,and other sustainability ***,the existing population datasets such as LandScan and WorldPop all provide data from 2000 with limited time series,while GHS-POP only utilizes land use data with limited *** view of the limited remote sensing images of long time series,it is necessary to combine existing multi-source remote sensing data for population spatialization *** this research,we developed a nighttime light desaturation index(NTLDI).Through the cross-sensor calibration model based on an autoencoder convolutional neural network,the NTLDl was calibrated with the same period Visible Infrared Imaging Radiometer Suite Day/Night Band(VIRS-DNB)***,the geographically weighted regression method is used to determine the population density of China from 1990 to 2020 based on the long time series ***,the change characteristics and the driving factors of China's population spatial distribution are *** large-scale,long-term population spatialization results obtained in this study are of great significance in government planning and decision-making,disaster assessment,resource allocation,and other aspects.

关键词： Nighttime light Population density Geographically weighted regression Population spatialization driving force analysis

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The driving force of water resource stress change based on the STIRPAT model:take Zhangye City as a case study

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Research in Cold and Arid Regions 2021年第4期13卷 337-348页

作者： Xia Tang XinYuan Wang Lei Feng Key Laboratory of Ecohydrology of Inland River Basin Chinese Academy of SciencesLanzhouGansu 730000China Northwest Institute of Eco-Environment and Resources Chinese Academy of SciencesLanzhouGansu 730000China Ecological Environmental Supervision and Administration Bureau of Gansu Province LanzhouGansu 730020China Gansu Computing Center LanzhouGansu 730030China

A prominent contradiction between supply and demand of water resources has restricted local development in social and economic aspects of Zhangye City,located in a typical arid region of *** study quantified the Water Resource Stress Index(WRSI)from 2003 to 2017 and examined the factors of population,urbanization level,GDP per capita,Engel coefficient,and water consumption per unit of GDP by using the extended stochastic impact by regression on population,affluence and technology(STIRPAT)model to find the key factors that impact WRSI of Zhangye City to relieve the pressure on water *** ridge regression method is applied to improve this model to eliminate multicollinearity *** WRSI system was developed from the following three aspects:water resources utilization(WR),regional economic development water use(WU),and water environment stress(WE).Results show that the WRSI index has fallen from 0.81(2003)to 0.17(2017),with an average annual decreased rate of 9.8%.Moreover,the absolute values of normalized coefficients demonstrate that the Engel coefficient has the largest positive contribution to increase WRSI with an elastic coefficient of 0.2709,followed by water consumption per unit of GDP and population with elastic coefficients of 0.0971 and 0.0387,*** contrast,the urbanization level and GDP per capita can decrease WRSI by−0.2449 and−0.089,*** decline of WRSI was attributed to water-saving society construction which included the improvement of water saving technology and the adjustment of agricultural planting ***,this study demonstrated the feasibility of evaluating the driving forces affecting WRSI by using the STIRPAT model and ridge regression analysis.

关键词： water resource stress index STIRPAT model driving force analysis water scarcity

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Temporal and Spatial Variations of Eco-asset Patterns and the Factors driving Change in the Wanjiang Demonstration Area

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Journal of Resources and Ecology 2019年第3期10卷 282-288页

作者： CAO Yuhong CHEN Chen LIU Chonggang LI Lulu LIU Meiyun College of Environmental Science and Engineering Anhui Normal University Wuhu Anhui 241003 China

With the rapid development of the society and the economy, people are paying more attention to the value of natural resources and the benefits of the ecological environment. Evaluating the value of eco-assets has become a focus of concern. Quantitative remote sensing measurements, land data and other auxiliary data were used to measure the eco-assets in 46 regions of the Wanjiang Demonstration Area from 1990 to 2013. This paper analyzes temporal and spatial variations of eco-assets’ distribution, composition, change patterns and the factors driving variations. The results show that the distribution of eco-assets in the regions is very uneven, the central region has higher ecological assets than other regions, and it declined first and then rose during the period 1990-2013. The total amount of eco-assets increased by 3.05%. The change in the amount of ecological assets was not large, but it is important that the amount of assets was basically stable, and increases in the proportion of degraded areas was small. Grassland and water body eco-assets decreased by 11.19% and 0.66%, respectively, and that of cultivated land decreased by 15.54%, but forest land increased by 6.42%. As for the change pattern of ecological assets, the per capita assets of Hefei had the largest reduction, and those of Xuancheng the second largest. The spatial and temporal changes of ecological assets in the Wanjiang Demonstration Area include natural factors and human factors. The government’s macro-control and economic policies are the main driving factors for the spatial and temporal changes of the ecological assets pattern.

关键词： eco-assets landscape pattern temporal and spatial variation driving force analysis

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