Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.3390/rs12162612 |
Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors | |
Bashir, Barjeece; Cao, Chunxiang; Naeem, Shahid; Joharestani, Mehdi Zamani; Bo, Xie; Afzal, Huma; Jamal, Kashif; Mumtaz, Faisal | |
通讯作者 | Cao, CX |
来源期刊 | REMOTE SENSING
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EISSN | 2072-4292 |
出版年 | 2020 |
卷号 | 12期号:16 |
英文摘要 | Land degradation reflected by vegetation is a commonly used practice to monitor desertification. To retrieve important information for ecosystem management accurate assessment of desertification is necessary. The major factors that drive vegetation dynamics in arid and semi-arid regions are climate and anthropogenic activities. Progression of desertification is expected to exacerbate under future climate change scenarios, through precipitation variability, increased drought frequency and persistence of dry conditions. This study examined spatiotemporal vegetation dynamics in arid regions of Sindh, Pakistan, using annual and growing season Normalized Difference Vegetation Index (NDVI) data from 2000 to 2017, and explored the climatic and anthropogenic effects on vegetation. Results showed an overall upward trend (annual 86.71% and growing season 82.7%) and partial downward trend (annual 13.28% and growing season 17.3%) in the study area. NDVI showed the highest significant increase in cropland region during annual, whereas during growing season the highest significant increase was observed in savannas. Overall high consistency in future vegetation trends in arid regions of Sindh province is observed. Stable and steady development region (annual 48.45% and growing 42.80%) dominates the future vegetation trends. Based on the Hurst exponent and vegetation dynamics of the past, improvement in vegetation cover is predicted for a large area (annual 44.49% and growing 30.77%), and a small area is predicted to have decline in vegetation activity (annual 0.09% and growing 3.04%). Results revealed that vegetation growth in the study area is a combined result of climatic and anthropogenic factors; however, in the future multi-controls are expected to have a slightly larger impact on annual positive development than climate whereas positive development in growing season is more likely to continue in future under the control of climate variability. |
英文关键词 | vegetation dynamic trend Hurst exponent MODIS climate variability remote sensing |
类型 | Article |
语种 | 英语 |
开放获取类型 | DOAJ Gold |
收录类别 | SCI-E |
WOS记录号 | WOS:000565449300001 |
WOS关键词 | HURST EXPONENT ; TREND ANALYSIS ; TIME-SERIES ; LAND DEGRADATION ; MODIS ; INDEX ; DESERTIFICATION ; VARIABILITY ; REGION ; SAHEL |
WOS类目 | Remote Sensing |
WOS研究方向 | Remote Sensing |
来源机构 | 中国科学院地理科学与资源研究所 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/325994 |
作者单位 | [Bashir, Barjeece; Cao, Chunxiang; Joharestani, Mehdi Zamani; Bo, Xie; Mumtaz, Faisal] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China; [Bashir, Barjeece; Cao, Chunxiang; Naeem, Shahid; Joharestani, Mehdi Zamani; Bo, Xie; Jamal, Kashif] Univ Chinese Acad Sci, Beijing 100094, Peoples R China; [Naeem, Shahid] Inst Geog Sci & Nat Resources Res IGSNRR, Beijing 100101, Peoples R China; [Afzal, Huma] Govt Degree Coll Women Sahianwala, Dept Geog, Faisalabad 37701, Pakistan; [Jamal, Kashif] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing & Geospatial Sci, Lanzhou 730000, Peoples R China |
推荐引用方式 GB/T 7714 | Bashir, Barjeece,Cao, Chunxiang,Naeem, Shahid,et al. Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors[J]. 中国科学院地理科学与资源研究所,2020,12(16). |
APA | Bashir, Barjeece.,Cao, Chunxiang.,Naeem, Shahid.,Joharestani, Mehdi Zamani.,Bo, Xie.,...&Mumtaz, Faisal.(2020).Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors.REMOTE SENSING,12(16). |
MLA | Bashir, Barjeece,et al."Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors".REMOTE SENSING 12.16(2020). |
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