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Large-scale detection of vegetation dynamics and their potential drivers using MODIS images and BFAST: A case study in Quebec, Canada

文献类型：期刊论文

作者Fang, Xiuqin1,4; Zhu, Qiuan2; Ren, Liliang3; Chen, Huai5; Wang, Kai1; Peng, Changhui2,4
刊名REMOTE SENSING OF ENVIRONMENT
出版日期2018-03-01
卷号206期号:2018页码:391-402
关键词Vegetation dynamics MODIS NDVI BFAST Quebec Canada Vegetation disturbances
ISSN号0034-4257
DOI10.1016/j.rse.2017.11.017
产权排序5
文献子类Article
英文摘要Monitoring vegetation dynamics at global scale is equally important in the context of terrestrial ecosystem carbon exchange and climate-biosphere, interactions. The Breaks For Additive Seasonal and Trend (BFAST) method and Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day Normalized Difference Vegetation Index (NDVI) at a spatial resolution of 250 m were used to detect vegetation dynamics in Quebec during 2000-2011. The overall agreement between BFAST detected breaks and observed disturbances was about 64% with the highest agreement up to 80% for "Fire" disturbance. The results presented in this study indicated that 25.7% of the total study area experienced NDVI trend changes with one or more breaks during 2000-2011, most of which were detected in the Boreal Shield eco-zone along the coastline of the Gulf of St. Lawrence. Abrupt vegetation changes barely varied under different eco-zones while considerably varied with different land cover types. The abrupt changes areas in 2002 and 2009 were the two greatest, with area percentages of 17.4% and 29.1% of the whole area, respectively. The area percentages of years with abrupt trend changes indicated that abrupt vegetation greening occurred in 2008 and 2009, especially in 2009, with 58.3% of the overall abrupt greening. Abrupt vegetation browning occurred in 2002, 2003, 2005 and 2007, especially in 2002, with 28.2% of the overall abrupt browning. Moreover, our results indicated that the detected vegetation trends varied temporally and spatially. Disturbances from existing field observations or remotely sensed images could only interpret < 40% of the vegetation changes. The impact of climate change on vegetation dynamic is particularly worth being investigated in the future work. To our knowledge, this study is one of the few attempting to explore large-scale detection of vegetation dynamics and their potential drivers in eastern Canada.
学科主题Earth Sciences
URL标识查看原文
WOS关键词LANDSAT TIME-SERIES ; FOREST DISTURBANCE ; CLIMATE VARIABILITY ; SOUTHERN QUEBEC ; BOREAL FORESTS ; TREND ANALYSIS ; NDVI ; COVER ; PHENOLOGY ; DROUGHT
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000427342700029
出版者ELSEVIER SCIENCE INC
源URL[http://210.75.237.14/handle/351003/29764]  
专题生物多样性与生态系统服务领域_生态研究
成都生物研究所_生态研究
生物多样性与生态系统服务领域_中国科学院山地生态恢复与生物资源利用重点实验室
生物多样性与生态系统服务领域_生态系统恢复与生物多样性保育四川省重点实验室
作者单位1.School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China;
2.Laboratory for Ecological Forecasting and Global Change, College of Forestry, Northwest Agriculture and Forest University, Yanglin 712100, China;
3.State Key Laboratory of Hydrology – Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China;
4.Institute of Environment Sciences, Department of Biology Sciences, University of Quebec at Montreal, Montreal, QC H3C 3P8, Canada ;
5.Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration Biodiversity Conservation Key Laboratory of Sichuan Province,Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China
推荐引用方式
GB/T 7714		 Fang, Xiuqin,Zhu, Qiuan,Ren, Liliang,et al. Large-scale detection of vegetation dynamics and their potential drivers using MODIS images and BFAST: A case study in Quebec, Canada[J]. REMOTE SENSING OF ENVIRONMENT,2018,206(2018):391-402.
APA Fang, Xiuqin,Zhu, Qiuan,Ren, Liliang,Chen, Huai,Wang, Kai,&Peng, Changhui.(2018).Large-scale detection of vegetation dynamics and their potential drivers using MODIS images and BFAST: A case study in Quebec, Canada.REMOTE SENSING OF ENVIRONMENT,206(2018),391-402.
MLA Fang, Xiuqin,et al."Large-scale detection of vegetation dynamics and their potential drivers using MODIS images and BFAST: A case study in Quebec, Canada".REMOTE SENSING OF ENVIRONMENT 206.2018(2018):391-402.

入库方式： OAI收割

来源：成都生物研究所

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