Change of surface cover greenness in China between 2000 and 2010

Surface greenness reflects the situation of vegetation cover. Vegetation index calculated from the Red and Near Infrared bands of remote sensing images, whose values indicate the level of photosynthetic activity, is monotonically related to surface greenness when vegetation canopy does not fully cover the background soil. Especially for desert regions, vegetation index is positively correlated with vegetation coverage. Therefore, vegetation index can be used to study the change in greenness of desert areas. This study collected MODIS Normalized Difference Vegetation Index (NDVI) data from 2000 to 2010 and analyzed their change over China in this period. The results showed that an increasing trend of NDVI occurred over 66.84% (OLS fitting) or 64.27% (LAD fitting) of China, indicating that China’s greenness is increasing overall. Meanwhile, desertification of China decreased. Areas showing large increase in greenness are found in Shaanxi, Shanxi, Ningxia, Henan, Shandong, Qinghai, and Gansu while regions with large decrease in greenness are found in Northeast Inner Mongolia, South Tibet, Jiangsu, and Shanghai. Changes of Qinghai, Gansu, Xinjiang and South Tibet could probably be driven by climate factors. Decrease of greenness in Northeast Inner Mongolia was related to agricultural reclamation. Decrease of greenness in Jiangsu and Shanghai was related to rapid urbanization. Climate factors did not exhibit obvious correspondence to the large increase in greenness in Shaanxi, Shanxi, Ningxia and Gansu, indicating that the changes might have been caused by human factors. The reduction of desert areas in China could probably have been caused by human management and protection at the national scale.

[1]  Yuhong He,et al.  Landsat-comparable land cover maps using ASTER and SPOT images: a case study for large-area mapping programmes , 2011 .

[2]  K. Oellers-Frahm,et al.  United Nations Convention to Combat Desertification in Those Countries Experiencing Serious Drought and/or Desertification, Particularly in Africa of June 17, 1994 , 2001 .

[3]  Michel M. Verstraete,et al.  Towards a global drylands observing system: Observational requirements and institutional solutions , 2011 .

[4]  M. Ma,et al.  A statistical analysis of the relationship between climatic factors and the Normalized Difference Vegetation Index in China , 2011 .

[5]  Lu Liang,et al.  China’s urban expansion from 1990 to 2010 determined with satellite remote sensing , 2012 .

[6]  Ruiliang Pu,et al.  Crown closure estimation of oak savannah in a dry season with Landsat TM imagery: Comparison of various indices through correlation analysis , 2003 .

[7]  D. Zhuang,et al.  Multi-scale quantitative assessment of the relative roles of climate change and human activities in desertification – A case study of the Ordos Plateau, China , 2010 .

[8]  R. Stöckli,et al.  European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset , 2004 .

[9]  D. Zhuang,et al.  Assessment of the relative role of climate change and human activities in desertification: A review , 2011 .

[10]  Zhan Yu-lin Wang Chang-yao DU Zi-tao.  THE DYNAMIC MONITORING OF DESERTIFICATION IN HORQIN SANDY LAND ON THE BASIS OF MODIS NDVI , 2009 .

[11]  Jay Gao,et al.  Determination of land degradation causes in Tongyu County, Northeast China via land cover change detection , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[12]  Dafang Zhuang,et al.  Quantitative Assessment of Desertification Using Landsat Data on a Regional Scale – A Case Study in the Ordos Plateau, China , 2009, Sensors.

[13]  Troy Sternberg,et al.  Tracking desertification on the Mongolian steppe through NDVI and field-survey data , 2011, Int. J. Digit. Earth.

[14]  Wu Jianjun,et al.  Theory and methodology on monitoring and assessment of desertification by remote sensing , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[15]  Tim R. McVicar,et al.  Global evaluation of four AVHRR-NDVI data sets: Intercomparison and assessment against Landsat imagery , 2011 .

[16]  Meixue Yang,et al.  Permafrost degradation and its environmental effects on the Tibetan Plateau: A review of recent research , 2010 .

[17]  Lars Eklundh,et al.  Vegetation index trends for the African Sahel 1982–1999 , 2003 .

[18]  Changzhen Yan,et al.  Change trends for desertified lands in the Horqin Sandy Land at the beginning of the twenty-first century , 2010 .

[19]  Cao Xin,et al.  ANALYSIS OF HUMAN-INDUCED STEPPE DEGRADATION BASED ON REMOTE SENSING IN XILIN GOLE,INNER MONGOLIA,CHINA , 2006 .

[20]  Weimin Ju,et al.  Spatial and temporal variations of forest LAI in China during 2000–2010 , 2012 .

[21]  Alfredo Huete,et al.  From AVHRR-NDVI to MODIS-EVI: Advances in vegetation index research , 2003 .

[22]  F. Peng,et al.  Monitoring aeolian desertification process in Hulunbir grassland during 1975–2006, Northern China , 2010, Environmental monitoring and assessment.

[23]  J. J. Zhu,et al.  Environmental impacts of the shelter forests in Horqin Sandy land, northeast China. , 2011, Journal of environmental quality.

[24]  Yuanzhi Zhang,et al.  Change detection of sandy land areas in Minfeng oasis of Xinjiang, China , 2009, Environmental monitoring and assessment.

[25]  Wataru Takeuchi,et al.  Land Cover Classification and Change Analysis in the Horqin Sandy Land From 1975 to 2007 , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[26]  Zhibao Dong,et al.  Has the Three Norths Forest Shelterbelt Program solved the desertification and dust storm problems in arid and semiarid China , 2010 .

[27]  P. Yan,et al.  Precipitation characteristics and its impact on vegetation restoration in Minqin County, Gansu Province, northwest China , 2011 .

[28]  David J. Briggs,et al.  United Nations Environment Program.: Environmental data report (2nd ed.) Oxford: Basil Blackwell, 1989. 547 pp. £45.00 paperback , 1990 .