Article

Journal of Geographical Sciences

, Volume 21, Issue 1, pp 135-149

Analysis of vegetation response to rainfall with satellite images in Dongting Lake

  • Weiguo JiangAffiliated withState Key Laboratory of Earth Process and Resource Ecology, Beijing Normal UniversityAcademy of Disaster Reduction and Emergency Management, Beijing Normal University
  • , Peng HouAffiliated withState Key Laboratory of Earth Process and Resource Ecology, Beijing Normal UniversitySatellite Environment Center, MEP Email author 
  • , Xiaohua ZhuAffiliated withInstitute of Geographic Sciences and Natural Resources Research, CAS
  • , Guangzhen CaoAffiliated withKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration
  • , Xiaoman LiuAffiliated withSatellite Environment Center, MEPInstitute of Geographic Sciences and Natural Resources Research, CAS
  • , Ruyin CaoAffiliated withState Key Laboratory of Earth Process and Resource Ecology, Beijing Normal University

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Abstract

We analyzed the Normalized Difference Vegetation Index (NDVI) from satellite images and precipitation data from meteorological stations from 1998 to 2007 in the Dongting Lake wetland watershed to better understand the eco-hydrological effect of atmospheric precipitation and its relationship with vegetation. First, we analyzed its general spatio-temporal distribution using its mean, standard deviation and linear trend. Then, we used the Empirical Orthogonal Functions (EOF) method to decompose the NDVI and precipitation data into spatial and temporal modes. We selected four leading modes based on North and Scree test rules and analyzed the synchronous seasonal and inter-annual variability between the vegetation index and precipitation, distinguishing time-lagged correlations between EOF modes with the correlative degree analysis method. According to our detailed analyses, the vegetation index and precipitation exhibit a prominent correlation in spatial distribution and seasonal variation. At the 90% confidence level, the time lag is around 110 to 140 days, which matches well with the seasonal variation.

Keywords

eco-hydrology precipitation vegetation remote sensing wetland Dongting Lake