首页|Monitoring vegetation cover in Chongqing between 2001 and 2010 using remote sensing data

Monitoring vegetation cover in Chongqing between 2001 and 2010 using remote sensing data

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  • NETL
  • NSTL
  • Springer Nature
In this study, we applied asymmetric Gaussian function fitting to reconstruct a high-qualityMODIS normalized difference vegetation index (NDVI) time series dataset. Following this, we retrieved vegetation cover data from the Chongqing area between 2001 and 2010 using this dataset, applying a dimidiate pixel method. We then used several analytical indices to analyze spatial and temporal changes and trends related to these changes. We determined that a reconstruction of the MODIS NDVI dataset using asymmetric Gaussian fitting in conjunction with a data quality weight coefficient improved data quality and created a foundation for accurate estimations of vegetation cover. We also determined that vegetation cover in the Chongqing area decreased gradually from east to west. During the 10-year study period, vegetation cover in the Chongqing area generally increased, changing from low to high coverage. This increase in vegetation cover was mainly the result of ecological protection policies and improving climate conditions. We also found that changes in vegetation cover were mainly the result of urban construction and afforestation initiatives, but vegetation cover improved overall.

TIMESATDimidiate pixel modelVegetation coverDynamic change analysis

Xiao, Qiang、Tao, Jianping、Xiao, Yang、Qian, Feng

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Southwest Univ, Key Lab Ecoenvironm Gorges Reservoir Reg 3, Chongqing Key Lab Plant Ecol & Resources Res Gorg, Minist Educ,Sch Life Sci, Chongqing 400715, Peoples R China|Chongqing Coll Arts & Sci, Chongqing 402160, Peoples R China

Southwest Univ, Key Lab Ecoenvironm Gorges Reservoir Reg 3, Chongqing Key Lab Plant Ecol & Resources Res Gorg, Minist Educ,Sch Life Sci, Chongqing 400715, Peoples R China

Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China

2017

10.1007/s10661-017-6210-1

Environmental Monitoring and Assessment

Environmental Monitoring and Assessment

EI
ISSN：0167-6369
年,卷(期)：2017.189(10)
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