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Remote Sensing for Natural Resources    2022, Vol. 34 Issue (1) : 249-256     DOI: 10.6046/zrzyyg.2021086
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An analysis of the characteristics, causes, and trends of spatio-temporal changes in vegetation in the Nuomuhong alluvial fan based on Google Earth Engine
YAO Jinxi1(), ZHANG Zhi1(), ZHANG Kun2
1. Institute of Geophysics and Geomatics, China University of Geosciences(Wuhan), Wuhan 430074, China
2. Key Laboratory of the Northern Qinghai-Tibet Plateau Geological Processes and Mineral Resources, Xining 810300,China
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Abstract  

Google Earth Engine enables some limitations in the remote sensing monitoring of vegetation to be overcome, including difficult data acquisition, large local storage capacity, and low processing efficiency. Using GEE, the data of satellites Landsat and MODIS (spatial resolution: 30 m and 250 m, respectively), and temperature and precipitation data, this study investigated the spatio-temporal change trends and sustainability of the vegetation in the Nuomuhong alluvial fan in Qinghai Province during 2000—2017. Moreover, this study analyzed the relationships of vegetation between wolfberry plantations and salinized areas on the alluvial fans of different eras and the future changes of the relationships. The results are as follows: ① The average annual maximum synthetic normalized difference vegetation index (NDVI) increased from 0.029 to 0.054 during 2000—2017, with an increased amplitude of 0.025. The average annual enhanced vegetation index (EVI) increased from 0.633 to 0.771 during these years, with an increased amplitude of 0.138. The multiyear average maximum EVI showed that EVI peaks occurred from May to October each year. ② A correlation analysis and a partial correlation analysis were conducted between the average maximum EVI and the temperature and precipitation data. According to the analytical results, the correlation coefficient between the average maximum EVI and temperature was 0.839, indicating a strong positive correlation. Meanwhile, the correlation coefficient between the average maximum EVI and precipitation amount was 0.457, indicating a weak positive correlation. ③ Over 18 years, the vegetation in wolfberry plantations was rapidly improved, while the vegetation in the salinized area degenerated. ④ The future changes in the vegetation in wolfberry planting areas and salinized areas will have strong sustainability. The vegetation growth in wolfberry planting areas will continuously restrict the vegetation in the salinized area to a certain extent in a period in the future.
Keywords Nuomuhong alluvial fan      vegetation change      vegetation index      Hurst index      Google Earth Engine     
ZTFLH:  TP79  
Corresponding Authors: ZHANG Zhi     E-mail: 1812283850@qq.com;171560655@qq.com
Issue Date: 14 March 2022
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Jinxi YAO
Zhi ZHANG
Kun ZHANG
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Jinxi YAO,Zhi ZHANG,Kun ZHANG. An analysis of the characteristics, causes, and trends of spatio-temporal changes in vegetation in the Nuomuhong alluvial fan based on Google Earth Engine[J]. Remote Sensing for Natural Resources, 2022, 34(1): 249-256.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2021086     OR     https://www.gtzyyg.com/EN/Y2022/V34/I1/249
Fig.1  Schematic diagram of the location of Nuomuhong alluvial fans
Fig.2  Technical route
Fig.3  Vegetation coverage of the study area in 2000 and 2017
Fig.4  Inter-annual changes of vegetation in study area from 2000 to 2017
Fig.5  Inter-monthly changes of vegetation in study area from 2000 to 2017
Fig.6  Interannual changes of vegetation coverage in the wolfberry planting area and salinization area
Fig.7  The k value of NDVI change in Nuomuhong alluvial fan wolfberry planting area and salinization area from 2000 to 2017
Fig.8  Hurst exponent distribution in the area of study area
Fig.9  Hurst index distribution of wolfberry planting area and salinization area
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