Assessing the impact of urbanization on net primary productivity using multi-scale remote sensing data: a case study of Xuzhou, China

Kun TAN, Songyang ZHOU, Erzhu LI, Peijun DU

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Front. Earth Sci. ›› 2015, Vol. 9 ›› Issue (2) : 319-329. DOI: 10.1007/s11707-014-0454-7
RESEARCH ARTICLE
RESEARCH ARTICLE

Assessing the impact of urbanization on net primary productivity using multi-scale remote sensing data: a case study of Xuzhou, China

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Abstract

An improved Carnegie Ames Stanford Approach (CASA) model based on two kinds of remote sensing (RS) data, Landsat Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS), and climate variables were applied to estimate the Net Primary Productivity (NPP) of Xuzhou in June of each year from 2001 to 2010. The NPP of the study area decreased as the spatial scale increased. The average NPP of terrestrial vegetation in Xuzhou showed a decreasing trend in recent years, likely due to changes in climate and environment. The study area was divided into four sub-regions, designated as highest, moderately high, moderately low, and lowest in NPP. The area designated as the lowest sub-region in NPP increased with expanding scale, indicating that the NPP distribution varied with different spatial scales. The NPP of different vegetation types was also significantly influenced by scale. In particular, the NPP of urban woodland produced lower estimates because of mixed pixels. Similar trends in NPP were observed with different RS data. In addition, expansion of residential areas and reduction of vegetated areas were the major reasons for NPP change. Land cover changes in urban areas reduced NPP, which could chiefly be attributed to human-induced disturbance.

Keywords

multi-scale remote sensing / net primary productivity / improved Carnegie Ames Stanford approach model / urbanization

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Kun TAN, Songyang ZHOU, Erzhu LI, Peijun DU. Assessing the impact of urbanization on net primary productivity using multi-scale remote sensing data: a case study of Xuzhou, China. Front. Earth Sci., 2015, 9(2): 319‒329 https://doi.org/10.1007/s11707-014-0454-7

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Acknowledgments

This research is partially supported by the National Natural Science Foundation of China (Grant No. 41101423), Jiangsu Provincial Natural Science Foundation under Grant BK2012018, Jiangsu Key Laboratory of Coal-based CO2 Capture and Geological Storage (2011KF06), China Postdoctoral Science Foundation (2011M500128 and 2012T50499), Jiangsu Planned Projects for Postdoctoral Research Funds (1102080C), Fundamental Research Funds for the Central Universities (2014QNA33, 2014ZDPY14), and Priority Academic Program Development of Jiangsu Higher Education Institutions.

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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