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REMOTE SENSING FOR LAND & RESOURCES    2017, Vol. 29 Issue (2) : 181-186     DOI: 10.6046/gtzyyg.2017.02.26
Contents |
An analysis of spatial distribution characteristics of monthly mean NDVI in the past ten years in China
YAO Zhenhai1, QIU Xinfa2, SHI Guoping3, ZHANG Xiliang4
1. Anhui Public Meteorological Service Center, Hefei 230011, China;
2. College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China;
3. School of Geography and Remote Sensing GIS department,Nanjing University of Information Science and Technology, Nanjing 210044, China;
4. Huzhou Meteorology Bureau of Zhejiang Province, Huzhou 313000, China
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Abstract  

In order to study the spatial distribution characteristics of monthly mean NDVI during the past ten years in China, the authors used MODIS MOD/MYD13C2 vegetation spectrum to synthesize monthly NDVI and, combined with China’s terrain data, discussed the changing regularity of NDVI with respect to aspect and elevation.The results show that the area ratio of low NDVI value segment [-0.25,0.15)is high in winter and low in summer, suggesting the characteristics of bare soil, deserted land and water.The median segment[0.15, 0.55] shows the "bimodal double-dip" character, and the area ratio is higher in spring and autumn than in winter and summer, implying features of vegetated mixture land cover.The area ratio of high value segment [0.55, 0.95] is high in summer and low in winter, indicating variation of vegetation cover with seasonal change.NDVI change with aspect shows the "bimodal double-dip" distribution, the NDVI values in southeast and northwest aspects are larger than those in southwest and northeast aspects.With increasing elevation , three NDVI decreasing zones are 250~1 250 m, 2 500~3 000m and 3 750~6 000 m, and two NDVI increasing zones are 1 250~2 500 m and 3 000~3 750 m, respectively.The horizontal and vertical distribution differentiations of NDVI are remarkable, which is attributed to the impact of climate and geographical terrain elements in China.Those regularities may be helpful to the research on land surface process.

Keywords GNSS-R      soil moisture      software implementation      MATLAB      model integration     
Issue Date: 03 May 2017
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LI Wei
CHEN Xiuwan
PENG Xuefeng
XIAO Han
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LI Wei,CHEN Xiuwan,PENG Xuefeng, et al. An analysis of spatial distribution characteristics of monthly mean NDVI in the past ten years in China[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(2): 181-186.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2017.02.26     OR     https://www.gtzyyg.com/EN/Y2017/V29/I2/181

[1] 陈渭民,陶国庆,邱新法.全球气候系统卫星遥感导论——气象卫星资料的多学科应用[M].北京:气象出版社,2012:505-507.
Chen W M,Tao G Q,Qiu X F.Global Climate System and Introduction of Satellite Remote Sensing:Multidisciplinary Application of Meteorology Satellite Data[M].Beijing:Meteorological Press,2012:505-507.
[2] 梁顺林,李小文,王锦地.定量遥感:理念与算法[M].北京:科学出版社,2013:321-322.
Liang S L,Li X W,Wang J D.Theories and Algorithms of Quantitative Remote Sensing[M].Beijing:Science Press,2013:321-322.
[3] Huete A R.A soil adjusted vegetation index(SAVI)[J].Remote Sensing of Environment,1988,25(3):295-309.
[4] 盛永伟,陈维英,肖乾广,等.利用气象卫星植被指数进行我国植被的宏观分类[J].科学通报,1995,40(1):68-71.
Sheng Y W,Chen W Y,Xiao Q G,et al.Macro classification of vegetation in China with NOAA/NDVIs[J].Chinese Science Bulletin,1995,40(1):839-844.
[5] 高 磊,覃志豪,卢丽萍.基于植被指数和地表温度特征空间的农业干旱监测模型研究综述[J].国土资源遥感,2007,19(3):1-7.doi:10.6046/gtzyyg.2007.03.01.
Gao L,Qin Z H,Lu L P.An overview on agricultural drought monitoring models based on vegetation index and surface temperature feature space[J].Remote Sensing for Land and Resources,2007,19(3):1-7.doi:10.6046/gtzyyg.2007.03.01.
[6] 孙雷刚,刘剑锋,徐全洪.河北坝上地区植被覆盖变化遥感时空分析[J].国土资源遥感,2014,26(1):167-172.doi:10.6046/gtzyyg.2014.01.28.
Sun L G,Liu J F,Xu Q H.Remote sensing based temporal and spatial analysis of vegetation cover changes in Bashang Area of Hebei province[J].Remote Sensing for Land and Resources,2014,26(1):167-172.doi:10.6046/gtzyyg.2014.01.28.
[7] 夏照华.基于NDVI时间序列的植被动态变化研究[D].北京:北京林业大学,2007.
Xia Z H.The Studies on Dynamic of Vegetation Based on NDVI Time Series[D].Beijing:Beijing Forestry University,2007.
[8] 赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003:387-398.
Zhao Y S.Application Analysis Theories and Methods of Remote Sensing[M].Beijing:Science Press,2003:387-398.
[9] 陈云浩,李晓兵,史培军.1983—1992年中国陆地NDVI变化的气候因子驱动分析[J].植物生态学报,2001,25(6):716-720.
Chen Y H,Li X B,Shi P J.Variation in NDVI driven by climate factors across China,1983—1992[J].Acta Phytoecologica Sinica,2001,25(6):716-720.
[10] 王 娟,李宝林,余万里.近30年内蒙古自治区植被变化趋势及影响因素分析[J].干旱区资源与环境,2012,26(2):132-138.
Wang J,Li B L,Yu W L.Analysis of vegetation trend and their causes during recent 30 years in Inner Mongolia Autonomous Region[J].Journal of Arid Land Resources and Environment,2012,26(2):132-138.
[11] 姚 晨,黄 微,李先华.地形复杂区域的典型植被指数评估[J].遥感技术与应用,2009,24(4):496-501.
Yao C,Huang W,Li X H.Evaluation of topographical influence on vegetation indices of rugged terrain[J].Remote Sensing Technology and Application,2009,24(4):496-501.
[12] 朱高龙,柳艺博,居为民,等.4种常用植被指数的地形效应评估[J].遥感学报,2013,17(1):210-234.
Zhu G L,Liu Y B,Ju W M,et al.Evaluation of topographic effects on four commonly used vegetation indices[J].Journal of Remote Sensing,2013,17(1):210-234.
[13] 廖钰冰,陈新芳,陈 喜,等.地形校正对叶面积指数遥感估算的影响[J].遥感信息,2011(5):47-51,64.
Liao Y B,Chen X F,Chen X,et al.Effect of topographic correction on the estimation of leaf area index based on Landsat TM[J].Remote Sensing Information,2011(5):47-51,64.
[14] 毕如田,武俊娴,曹 毅,等.涑水河流域地形因子对植被指数变化的影响[J].中国农业通报,2012,28(35):257-263.
Bi R T,Wu J X,Cao Y,et al.The influence of terrain factors on vegetation index in Sushui river basin[J].Chinese Agricultural Science Bulletin,2012,28(35):257-263.
[15] 瓮耐义,刘 康,王纪伟.基于GIS的高原植被空间格局与地形因子相关关系研究[J].水土保持通报,2014,34(1):232-236.
Weng N Y,Liu K,Wang J W.A study of relationship between spatial vegetation pattern and terrain factors based on GIS techniques[J].Bulletin of Soil and Water Conservation,2014,34(1):232-236.
[16] 梁顺林.定量遥感[M].范闻捷,译.北京:科学出版社,2009:181-182.
Liang S L.Quantitative Remote Sensing of Land Surfaces[M].Translated by Fan W J.Beijing:Science Press,2009:181-182.
[17] 刘绿柳,肖风劲.黄河流域植被NDVI与温度、降水关系的时空变化[J].生态学杂志,2006,25(5):477-481.
Liu L L,Xiao F J.Spatial-temporal correlations of NDVI with precipitation and temperature in Yellow River Basin[J].Chinese Journal of Ecology,2006,25(5):477-481.
[18] 张景华,李英年.青海气候变化趋势及对植被生产力影响的研究[J].干旱区资源与环境,2008,22(2):97-102.
Zhang J H,Li Y N.The research on effect of climate change on vegetation productivity in Qinghai Province[J].Journal of Arid Land Resources and Environment,2008,22(2):97-102.
[19] 刘绿柳,许红梅.黄河流域主要植被类型NDVI变化规律及其与气象因子的关系[J].中国农业气象,2007,28(3):334-337.
Liu L L,Xu H M.Change of NDVI of main vegetations and their relationship with meteorological factors in Yellow River Basin[J].Chinese Journal of Agrometeorology,2007,28(3):334-337.
[20] 崔林丽,史 军,肖风劲,等.中国东部NDVI的变化趋势及其与气候因子的相关分析[J].资源科学,2010,32(1):124-131.
Cui L L,Shi J,Xiao F J,et al.Variation trends in vegetation NDVI and its correlation with climatic factors in Eastern China[J].Resources Science,2010,32(1):124-131.
[21] 王宗明,国志兴,宋开山,等.中国东北地区植被NDVI对气候变化的响应[J].生态学杂志,2009,28(6):1041-1048.
Wang Z M,Guo Z X,Song K S,et al.Responses of vegetation NDVI in Northeast China to climate change[J].Chinese Journal of Ecology,2009,28(6):1041-1048.
[22] 李俊祥,达良俊,王玉洁,等.基于NOAA-AVHRR数据的中国东部地区植被遥感分类研究[J].植物生态学报,2005,29(3):436-443.
Li J X,Da L J,Wang Y J,et al.Vegetation classification of east China using multi-temporal NOAA-AVHRR data[J].Acta Phytoecologica Sinica,2005,29(3):436-443.
[23] 陈效逑,喻 蓉.1982—1999年我国东部暖温带植被生长季节的时空变化[J].地理学报,2007,62(1):41-51.
Chen X Q,Yu R.Spatial and temporal variations of the vegetation growing season in warm-temper ate eastern China during 1982 to 1999[J].Acta Geographica Sinica,2007,62(1):41-51.
[24] 徐 茜,任志远,杨 忍.黄土高原地区归一化植被指数时空动态变化及其与气候因子的关系[J].陕西师范大学学报:自然科学版,2012,40(1):82-87.
Xu X,Ren Z Y,Yang R.The spatial and temporal dynamics of NDVI and its relation with climatic factors in Loess Plateau[J].Journal of Shaanxi Normal University:Natural Science Edition,2012,40(1):82-87.
[25] 曾 燕,邱新法,刘昌明,等.起伏地形下黄河流域太阳直接辐射分布式模式[J].地理学报,2005,60(4):680-688.
Zeng Y,Qiu X F,Liu C M,et al.Distributed modelling of direct solar radiation of rugged terrain over the Yellow River Basin[J].Acta Geographica Sinica,2005,60(4):680-688.
[26] 李秀花,师庆东,常顺利,等.1981—2001年中国西北干旱区NDVI变化分析[J].干旱区地理,2008,31(6):940-945.
Li X H,Shi Q D,Chang S L,et al.Change of NDVI based on NOAA image in northwest arid area of China in 1981—2001[J].Arid Land Geography,2008,31(6):940-945.
[27] 曾 燕,邱新法,何永健,等.复杂地形下黄河流域月平均气温分布式模拟[J].中国科学D辑(地球科学),2009,39(6):774-786.
Zeng Y,Qiu X F,He Y J,et al.Distributed modeling of monthly air temperatures over the rugged terrain of the Yellow River Basin[J].Science in China Series D:Earth Sciences,2009,52(5):694-707.

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