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RSS FeedsRemote Sensing, Vol. 11, Pages 1224: Identification of Natural and Anthropogenic Drivers of Vegetation Change in the Beijing-Tianjin-Hebei Megacity Region (Remote Sensing)

 
 

23 may 2019 18:00:26

 
Remote Sensing, Vol. 11, Pages 1224: Identification of Natural and Anthropogenic Drivers of Vegetation Change in the Beijing-Tianjin-Hebei Megacity Region (Remote Sensing)
 




Identifying the natural and anthropogenic mechanisms of vegetation changes is the basis for adapting to climate change and optimizing human activities. The Beijing-Tianjin-Hebei megacity region, which is characterized by significant geomorphic gradients, was chosen as the case study area. The ordinary least squares (OLS) method was used to calculate the NDVI trends and related factors from 2000 to 2015. A geographic weighted regression (GWR) model of NDVI trends was constructed using 14 elements of seven categories. Combined with the GWR calculation results, the mechanisms of the effects of explanatory variables on NDVI changes were analyzed. The findings suggest that the overall vegetation displayed an increasing trend from 2000 to 2015, with an NDVI increase of ca. 0.005/year. Additionally, the NDVI fluctuations in individual years were closely related to precipitation and temperature anomalies. The spatial pattern of the NDVI change was highly consistent with the gradients of geomorphology, climate, and human activities, which have a tendency to gradually change from northwest to southeast. The dominant climate-driven area accounted for only 5.98% of the total study area. The vegetation improvement areas were regionally concentrated and had various driving factors, and vegetation degradation exhibited strong spatial heterogeneity. The vegetation degradation was mainly caused by human activities. Natural vegetation was improved because of natural factors and reductions in human activities. Moreover, cropland vegetation as well as urban and built-up area improvements were related to increased human actions and decreased natural effects. This study can assist in ecological restoration planning and ecological engineering implementation in the study area.


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27 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 1225: Accuracy of Deformation Rates from Campaign GPS Surveys Considering Extended Observation Session and Antenna Set-Up Errors (Remote Sensing)
Remote Sensing, Vol. 11, Pages 1223: Joint Local Block Grouping with Noise-Adjusted Principal Component Analysis for Hyperspectral Remote-Sensing Imagery Sparse Unmixing (Remote Sensing)
 
 
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