T355 What Can You Do with Geoinformatics? (Posters)

Wednesday, 25 October 2017
9:00 AM - 6:30 PM
Halls 4EF

REVEALING VEGETATION COVER CHANGES IN BEIJING AND INFLUENTIAL FACTORS DURING 2000-2015 WITH GEOINFORMATICS

Paper number: T355-12
Program: Technical Sessions
Time: 9:00 AM – 6:30 PM

Authors

  • Meichen Jiang Presenting Author
    China University of Geosciences, Beijing, Beijing
  • Yuexin He
    Key Laboratory of Wetland Ecology and Environment, Changchun
  • Yuexin He
    University of Chinese Academy of Sciences, Beijing

Abstract

For centuries, the rapid development of human society has already made human activity the dominant factor in the terrestrial ecosystem. As the city of greatest importance in China, Beijing has experienced eco-environmental changes during past decades, along with the rapid development of the population and the economy. To better understand the ecological transition and its correlations in Beijing, Landsat satellite TM and OLI images were used to investigate vegetation coverage changes using a dimidiate pixel model on ENVI and ArcGIS platforms. Bivariate-partial correlation analysis and factor analysis were applied to the probing of the relationship between vegetation changes and climatic/human-induced factors. The results showed that from 2000 to 2005, 2005 to 2010, and 2010 to 2015, Beijing has experienced both restoration (6.33%, 10.08%, and 12.81%) and degradation (13.62%, 9.35%, and 9.49%). The correlation analysis results between climate and vegetation changes demonstrated that from 2000 to 2015, both temperature (r = −0.819, p < 0.01) and precipitation (r = 0.653, p < 0.05) had significantly correlated relationships with vegetation change. However, human activity is a more significant factor in impacting and explaining vegetation changes. The Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) has shown beneficial spatial effects on vegetation restoration; the total effectiveness in conservation areas (84.94) was much better than non-BTSSCP areas (34.34). The most contributory socioeconomic factors were the population (contribution = 54.356%) and GDP (contribution = 30.677%). The population showed a significantly negative correlation with the overall vegetation coverage (r = -0.684, p < 0.05). The GDP was significantly negatively correlated with vegetation in Tongzhou, Daxing, Central city, Fangshan, Shunyi, and Changping (r = -0.601,p < 0.01), while positively related in Huairou, Miyun, Pinggu, Mentougou and Yanqing (r = 0.614,p < 0.01). Compared with the traditional methods of investigation, remote sensing technology shows its all sidedness, direct viewing and accuracy in environmental change monitoring. It can provide important insights into options for harmonizing climate, human and eco-environment both inside China and around the world, combined with geoinformatics.

Geological Society of America Abstracts with Programs. Vol. 49, No. 6

doi: 10.1130/abs/2017AM-294006

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