globalchange  > 过去全球变化的重建
DOI: 10.3390/rs11101159
WOS记录号: WOS:000480524800017
论文题名:
Estimating Relations of Vegetation, Climate Change, and Human Activity: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone, China
作者: Li, Yang1,2,3; Xie, Zhixiang1,2,3; Qin, Yaochen1,2,3; Zheng, Zhicheng1,2,3
通讯作者: Qin, Yaochen
刊名: REMOTE SENSING
EISSN: 2072-4292
出版年: 2019
卷: 11, 期:10
语种: 英语
英文关键词: vegetation ; climate change ; human activity ; GIMMS NDVI3g ; 400-mm annual precipitation fluctuation zone
WOS关键词: LOESS PLATEAU ; TIME-SERIES ; LAND-USE ; SPATIOTEMPORAL CHANGES ; COVER CHANGE ; IMPACTS ; NDVI ; PROVINCE ; TRENDS ; CARBON
WOS学科分类: Remote Sensing
WOS研究方向: Remote Sensing
英文摘要:

The 400 mm annual precipitation fluctuation zone (75 degrees 55 '-127 degrees 6 ' E and 26 degrees 55 '-53 degrees 6 ' N) is located in central and western China, which is a transition area from traditional agricultural to animal husbandry. It is extremely sensitive to climatic changes. The corresponding changes of the ecosystem, represented by vegetation, under the dual influences of climate change and human activities are important issues in the study of the regional ecological environment. Based on the Savitzky-Golay (S-G) filtering method, the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Differential Vegetation Index (NDVI) dataset (NDVI3g) was reconstructed in this paper. Sen's slope estimation, Mann-Kendall (M-K), multiple regression residual analysis, and the Hurst index were used to quantify the impacts of climate change and human activities on vegetation; in addition, the future persistence characteristics of the vegetation changes trend were analyzed. Vegetation changes in the study area had an obvious spatio-temporal heterogeneity. On an annual scale, the vegetation increased considerably, with a growth rate of 0.50%/10a. The multi-year mean value of NDVI and growth rate of cultivated land were the highest, followed by the forest land and grassland. On a seasonal scale, the vegetation cover increased most significantly in autumn, followed by spring and summer. In the southeastern and central parts of the study area, the vegetation cover increased significantly (P < 0.05), while it decreased significantly in the northeastern and southwestern parts. In summer, the NDVI value of all vegetation types (cultivated land, forest land and grassland) reached the maximum. The change rate of NDVI value for cultivated land reached the highest in autumn (1.57%/10a), forest land reached the highest in spring (1.15%/10a), and grassland reached the highest in autumn (0.49%/10a). The NDVI of cultivated land increased in all seasons, while forest land (-0.31%/10a) and grassland (-0.009%/10a) decreased in winter. Partial correlation analysis between vegetation and precipitation, temperature found that the areas with positive correlation accounted for 66.29% and 55.05% of the total area, respectively. Under the influence of climate change alone, 62.79% of the study area showed an increasing tendency, among which 46.79% showed a significant upward trend (P < 0.05). The NDVI decreased in 37.21% of the regions and decreased significantly in 14.88% of the regions (P < 0.05). Under the influence of human activities alone, the vegetation in the study area showed an upward trend in 59.61%, with a significant increase in 41.35% (P < 0.05), a downward trend in 40.39%, and a significant downward trend in 7.95% (P < 0.05). Vegetation growth is highly unstable and prone to drastic changes, depending on the environmental conditions.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/138075
Appears in Collections:过去全球变化的重建

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作者单位: 1.Henan Univ, Coll Environm & Planning, Kaifeng 475004, Peoples R China
2.Key Lab Geospatial Technol Middle & Lower Yellow, Kaifeng 475004, Peoples R China
3.Collaborat Innovat Ctr Urban Rural Coordinated De, Zhengzhou 450046, Henan, Peoples R China

Recommended Citation:
Li, Yang,Xie, Zhixiang,Qin, Yaochen,et al. Estimating Relations of Vegetation, Climate Change, and Human Activity: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone, China[J]. REMOTE SENSING,2019-01-01,11(10)
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