基于MODIS产品的秦岭地区NDVI、地表温度和蒸散变化关系分析
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摘要
秦岭是我国自然环境的天然分界区,是我国中部重要的生态屏障,也是南水北调重要的水源涵养区。为了更好地服务于生态环境建设,选取MODIS植被指数NDVI、地表温度及地表蒸散数据产品,针对秦岭地区生态环境建设以来2001-2013年植被及水热条件发生的变化以及空间分布规律进行分析。结果表明,从区域平均情况来看,只有NDVI有显著升高的变化趋势,耕地区NDVI变化趋势大于林草区域。林草区NDVI、蒸散平均值高于耕地区,而地表温度在耕地区高于林草区。从各像元的空间分布图来看,NDVI、地表温度和蒸散的空间分布都有明显的山体脉络。NDVI随高度的增加而增大,2 000 m左右开始略微下降。地表温度随高度的升高呈极显著的线性下降趋势,海拔每升高100 m温度下降0.51℃。蒸散随海拔高度先是增高,在海拔800～1 800 m变化趋于平缓,随后随海拔的升高而降低。NDVI、地表温度和蒸散都在低海拔地区变化明显。2001-2013年秦岭地区NDVI呈显著增加趋势,与陕西开展的生态环境建设工程密不可分。在全球增温的背景下,地表温度没有明显变化,与植被的调节作用有一定关系。蒸散的增加趋势与NDVI的上升引起蒸腾作用加大有关,而蒸散的减小趋势与太阳辐射的减小有关。
The Qinling Mountains is not only the natural boundary of southern and northern China,but also is a significant ecological barrier in the middle of China,and an important water source conservation area of South-to-North Water Transfer Project.In order to serve the ecological environment construction with scientific and accurate information,NDVI(normailized difference vegetation index),LST(land surface temperature) and ET(evapotranspiration) of MODIS datasets were used to analyze the spatiotemporal variation laws and change relations of vegetation cover and hydrothermal condition after developing ecological environment construction in the Qinling Mountains area(2001-2013).It was found that generally,only NDVI presented extremely significant increasing trend in volatility,and in farmland it was more significant than in forest-grassland.NDVI and ET in forest-grassland were higher than in farmland,but LST in farmland was higher than in forest-grassland.From the point of the spatial distribution,spatial variations of NDVI,LST and ET presented mountainous features.NDVI increased with the increase of altitude,began to decline slightly at about 2 000 m.LST presented extremely significant linear downward trend with altitude.In addition,LST dropped 0.51℃ as altitude increased for every 100 m.With the increase of altitude,ET started to increase below 800 m and later flattened at 800-1 800 m,and then decreased in the end.NDVI,LST and ET changed obviously in low altitude.From 2001 to 2013,the improvement of NDVI in the Qinling Mountains area was the interactive effect of implementation of a series of ecological construction projects such as closing hill for forestation and restoring farmland into forestland and grassland.Under the background of global warming,no obvious change in LST,indicating a certain correlation with the regulation function of vegetation.The increase trend of ET caused by the improvement of NDVI,and the decrease trend of ET was associated with the decrease of solar radiation.
The Qinling Mountains is not only the natural boundary of southern and northern China,but also is a significant ecological barrier in the middle of China,and an important water source conservation area of South-to-North Water Transfer Project.In order to serve the ecological environment construction with scientific and accurate information,NDVI(normailized difference vegetation index),LST(land surface temperature) and ET(evapotranspiration) of MODIS datasets were used to analyze the spatiotemporal variation laws and change relations of vegetation cover and hydrothermal condition after developing ecological environment construction in the Qinling Mountains area(2001-2013).It was found that generally,only NDVI presented extremely significant increasing trend in volatility,and in farmland it was more significant than in forest-grassland.NDVI and ET in forest-grassland were higher than in farmland,but LST in farmland was higher than in forest-grassland.From the point of the spatial distribution,spatial variations of NDVI,LST and ET presented mountainous features.NDVI increased with the increase of altitude,began to decline slightly at about 2 000 m.LST presented extremely significant linear downward trend with altitude.In addition,LST dropped 0.51℃ as altitude increased for every 100 m.With the increase of altitude,ET started to increase below 800 m and later flattened at 800-1 800 m,and then decreased in the end.NDVI,LST and ET changed obviously in low altitude.From 2001 to 2013,the improvement of NDVI in the Qinling Mountains area was the interactive effect of implementation of a series of ecological construction projects such as closing hill for forestation and restoring farmland into forestland and grassland.Under the background of global warming,no obvious change in LST,indicating a certain correlation with the regulation function of vegetation.The increase trend of ET caused by the improvement of NDVI,and the decrease trend of ET was associated with the decrease of solar radiation.
引文
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[16] NETELER M.Estimating daily land surface temperatures in mountainous environments by reconstructed MODIS LST data[J].Remote Sensing,2010,2(1):333-351.
[17] MU Q Z,HEINSCH F A,ZHAO M S et al.Development of a global evapotranspiration algorithm based on MODIS and global meteorology data[J].Remote Sensing of Environment,2007,111:519-536.
[18] MU Q Z,ZHAO M S,RUNNING S W.Improvements to a MODIS global terrestrial evapotranspiration algorithm[J].Remote Sensing of Environment,2011,115:1781-1800.
[19] 吴桂平,刘元波,赵晓松,等.基于 MOD16 产品的鄱阳湖流域地表蒸散量时空分布特征[J].地理研究,2013,32(4):617-627.
[20] 范建忠,李登科,高茂盛.基于 MOD16 的陕西省蒸散量时空分布特征[J].生态环境学报,2014,23(9):1536-1543.
[21] IPCC.Working group Ⅰ contribution to the IPCC fifth assessment report (AR5).climate change 2013:the physical science basis[J].Final Draft Underlying Scientific-Technical Assessment,2013.
[2] 李登科,范建忠,王娟.陕西省植被覆盖度变化特征及其成因 [J].应用生态学报,2010,21(11):2896-2903.LI D K,FAN J Z,WANG J.Change characteristics and their causes of fractional vegetation coverage (FVC) in Shaanxi Province[J].Chinese Journal of Applied Ecology,2010,21(11):2896-2903.(in Chinese)
[3] 董金芳,袁媛,何慧娟,等.基于MODIS的陕西省叶面积指数时空变化特征分析[J].西北林学院学报,2016,31(3):79-85.DONG J F,YUAN Y,HE H J,et al.Analyses of spatial-temporal changes of leaf area index in Shaanxi Province based on MODIS[J].Journal of Northwest Forestry University,2016,31(3):79-85.(in Chinese)
[4] 王娟,卓静,何慧娟,等.2000-2013年秦岭林区植被净初级生产力时空分布特征及其驱动因素[J].西北林学院学报,2016,31(5):238-245.WANG J,ZHUO J,HE H J,et al.Changes of vegetation net primary productivity and its driving factors from 2000 to 2013 in Qinling Mountainous[J].Journal of Northwest Forestry University,2016,31(5):238-245.(in Chinese)
[5] BONAN G B.Ecological Climatology:Concepts and Applications[M].Cambridge:Cambridge University Press,2002.
[6] 朱晓勤,刘康,李建国,等.GIS 支持下的秦岭山地植被分布与环境梯度关系研究[J].水土保持研究,2009,16(2):169-175.ZHU X Q,LIU K,LI J G,et al.Analysis on vegetation-environment gradient correlation in Qinling Mountain based on GIS[J].Research of Soil and Water Conservation,2009,16(2):169-175.(in Chinese)
[7] 池秀莲,唐志尧.面积、温度及分布区限制对物种丰富度海拔格局的影响:以秦岭太白山为例[J].植物生态学报,2011,35(4):362-370.
[8] SELLERS P J.Biophysical models of land surface processes[C]//TRENBERTH K E.Climate System Modeling.Cambridge:Cambridge University Press,1992:451-490.
[9] LEAN J,ROWNTREE P R.Understanding the sensitivity of a GCM simulation of Amazonian deforestation to the specification of vegetation and soil characteristics[J].J Climate,1997,10(6):1216-1235.
[10] 崔晓临,白红英,王涛.秦岭地区植被 NDVI 海拔梯度差异及其气温响应[J].资源科学,2013,35(3):618-626.
[11] 麻坤,赵鹏祥,季菲菲,等.基于植被指数的秦岭森林健康评价方法研究[J].西北林学院学报,2013,28(6):145-150.MA K,ZHAO P X,JI F F,et al.Forest health assessment method in Qinling Mountains based on the vegetation indices[J].Journal of Northwest Forestry University,2013,28(6):145-150.(in Chinese)
[12] 杜乐山,关潇,李俊生,等.秦岭高山林线区域温度变化研究[J].西北林学院学报,2017,32(2):43-47.DU L S,GUAN X,LI J S,et al.Temperature variation in the timberline area of Qinling Mountains[J].Journal of Northwest Forestry University,2017,32(2):43-47.(in Chinese)
[13] 蒋冲,王飞,喻小勇,等.秦岭南北近地面水汽时空变化特征[J].生态学报,2013,33(12):3805-3815.JIANG C,WANG F,YU X Y,et al.Spatial and temporal variation of surface water vapor over Northern and Southern regions of Qinling Mountains[J].Acta Ecologica Sinica,2013,33(12):3805-3815.(in Chinese)
[14] 蒋冲,王飞,刘思洁,等.“蒸发悖论”在秦岭南北地区的探讨[J].生态学报,2013,33(3):0844-0855.JIANG C,WANG F,LIU S J,et al.Evaporation paradox in the Northern and Southern regions of the Qinling Mountains[J].Acta Ecologica Sinica,2013,33(3):0844-0855.(in Chinese)
[15] BHANDARI S,PHINN S,GILL T.Assessing viewing and illumination geometry effects on the MODIS vegetation index (MOD13Q1) time series:implications for monitoring phenology and disturbances in forest communities in Queensland,Australia[J].International Journal of Remote Sensing,2011,32(22):7513-7538.
[16] NETELER M.Estimating daily land surface temperatures in mountainous environments by reconstructed MODIS LST data[J].Remote Sensing,2010,2(1):333-351.
[17] MU Q Z,HEINSCH F A,ZHAO M S et al.Development of a global evapotranspiration algorithm based on MODIS and global meteorology data[J].Remote Sensing of Environment,2007,111:519-536.
[18] MU Q Z,ZHAO M S,RUNNING S W.Improvements to a MODIS global terrestrial evapotranspiration algorithm[J].Remote Sensing of Environment,2011,115:1781-1800.
[19] 吴桂平,刘元波,赵晓松,等.基于 MOD16 产品的鄱阳湖流域地表蒸散量时空分布特征[J].地理研究,2013,32(4):617-627.
[20] 范建忠,李登科,高茂盛.基于 MOD16 的陕西省蒸散量时空分布特征[J].生态环境学报,2014,23(9):1536-1543.
[21] IPCC.Working group Ⅰ contribution to the IPCC fifth assessment report (AR5).climate change 2013:the physical science basis[J].Final Draft Underlying Scientific-Technical Assessment,2013.