地球信息科学

祁连山MODIS LST时空变化特征及影响因素分析

展开
  • 兰州交通大学测绘与地理信息学院,甘肃 兰州 730700; 

    地理国情监测技术应用国家地方联合工程研究中心,甘肃 兰州 730700;   3 甘肃省地理国情监测工程实验室,甘肃 兰州 730700

邱丽莎(1993-),女,硕士研究生,研究方向为生态环境遥感监测.E-mail:lisa_qiu@lz.acmlife.org

收稿日期: 2020-01-07

  修回日期: 2020-04-03

  网络出版日期: 2020-05-25

基金资助

甘肃省自然科学基金( 17JR5RA095 );兰州交通大学天佑青年托举人才计划;甘肃省教育厅“兰州市主城区地面沉降 InSAR 监测”(2019A-043)资助

Spatiotemporal variation characteristics and influence factors of MODIS LST in Qilian Mountains

Expand
  • Faculty of GeomaticsLanzhou Jiaotong UniversityLanzhou 730700,Gansu,China;

    NationalLocal Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring,Lanzhou 730700,Gansu,China;Gansu Provincial Engineering Laboratory for National Geographic State Monitoring,Lanzhou 730700,Gansu,China

Received date: 2020-01-07

  Revised date: 2020-04-03

  Online published: 2020-05-25

摘要

地表温度(Land Surface TemperatureLST)是研究区域尺度和全球尺度上地表能量和水平衡物理过程中不可缺少的参数。祁连山LST的时空变化规律及其影响因素模式未知。通过采用趋势分析法和相关性分析法,探讨20002017年间祁连山LSTWTBZ〗的时空变化特征及与植被的相互关系,分析各植被类型下地表温度的时空分异特征。结果表明:(1 MODIS LST产品的精度能够满足祁连山地表温度时空变化分析的要求。(2) 祁连山LST时间序列呈 “上升—下降—上升—下降”的波动变化,整体呈小幅上升趋势,以0.17 ℃·(10 a-1的速率波动上升,冬季LST上升趋势最显著(63.37%),变化率为0.22℃·(10 a-1;空间上呈西北降低东南升高的变化趋势,显著上升面积(14.89%)远大于下降面积(0.90%)。(3) 祁连山年均LSTNDVI呈负相关,显著相关区域占22.56%,夏季NDVILST的调控作用较显著(25.45%);荒漠NDVILST的影响大于其他植被类型。(4) 海拔对各植被类型LST有强烈的影响,相关性依次为荒漠>林地>草甸>耕地;然而,夏季LST与海拔的相关性因植被覆盖增加而显著降低。(5)祁连山LST上升是NDVI、海拔以及植被类型综合影响的结果。

本文引用格式

邱丽莎, 何毅, 张立峰, 王文辉, 唐源蔚 .

祁连山MODIS LST时空变化特征及影响因素分析[J]. 干旱区地理, 2020 , 43(3) : 726 -737 . DOI: 10.12118/j.issn.1000-6060.2020.03.19

Abstract

Land surface temperature (LST) is an important variable in the surface energy budget,significantly affecting the global agriculture,natural disastershydrology,and ecological environment.With global climate change,quantitative research on LST and its related factors become critical in both regional and global scales.The Qilian Mountains in Qinghai and Gansu Province,China,as the boundary between the Qinghai-Tibetan Plateau and Northern Hinterland,is influenced by the continental climate and the climate of the QinghaiTibetan Plateau.It belongs to the temperate semi-arid climate zone and is an important geographical and climatic boundary line in China.The study of LST in the Qilian Mountains is essential for understanding the hydrothermal cycle in the northwest and improving the fragile ecological environment.The climate pattern,vegetation,and different land-use of the Qilian Mountains have been studied comprehensively.However,the spatiotemporal variability characteristics of LST and its response mode to terrain are not yet clear.Besides,the impact of different vegetation types on LST changes need to be discussed.Based on the MODIS LST data from 2000 to 2017,this study used a linear trend method to analyze the temporal and spatial variation of LST in the Qilian Mountains and used Pearson correlation analysis to discuss the regulation of LST by different types of vegetation and the influence of altitude on its change.The results are as follows: (1) the accuracy of MODIS LST products can meet the requirements of temporalspatial variation analysis of surface temperature in the Qilian Mountains.(2) LST of the Qilian Mountains increased at a rate of 0.17 ℃·(10 a)-1with two rising periods in 2000-2003 (1.83 ℃·(10 a)-1) and 2004-2017 (0.14 ℃·(10 a)-1).The annual average WTBXLSTWTBZ increased from SouthWest to NorthEast,and the significant rising area accounts for 77.26% of the total area.The extremely significant rising areas were mainly distributed in the middle and low altitudes below 3 500 m.In addition,the winter change rate was the highest (0.22 ℃·(10 a)-1),and the warmer area reached 98.23%.The winter warming had the greatest contribution to the increase of LST in the Qilian Mountains.(3) vegetation had a significant impact on LST changes,cultivated lands had a better inhibitory effect on LST rise,and vegetation in the desert had a stronger regulatory effect on LST.Except for summerthe NDVI and LST were positively correlated in the rest of the seasonand the positively correlated areas were mainly concentrated in the highaltitude forest land.(4) the effect of altitude on LST was significantly weak during the summer due to conditions such as vegetation cover changes.The LST in the desert showed the strongest response to altitude,with strong annual fluctuations between 2 500 and 3 500 m.Meanwhile,vegetation degradation and human activities at low and medium altitudes may be the main factors accelerating the increase in LST.

参考文献

[1]FREY C,CLAUDIA K.Landsurface temperature dynamics in the upper Mekong basin derived from MODIS time series[J].International Journal of Remote Sensing,2014,35(8):2780-2798. [2]薛亚永,梁海斌,张园,等.黄土高原地表温度变化的时空格局[J].地球与环境,2017,45(5):500-507. [ XUE Yayong,LIANG Haibin,ZHANG Yuan,et al.Spatial and temporal variations of land surface temperature of the Loess Plateau[J].Earth and Environment,2017,45(5):500-507.] [3]YAN Denghua,XU Ting,GIRMA Able,et al.Regional correlation between precipitation and vegetation in the Huang-Huai-Hai River Basin,China[J]. Water,2017,9(8):557-572. [4]SONG Yi,JIN Long,WANG Haibo.Vegetation changes along the QinghaiTibet Plateau engineering corridor since 2000 induced by climate change and human activities[J]. Remote Sensing,2018,10(2):95-116. [5]乔丽,吴林荣,张高健. 中国近50 a地表温度时空变化特征分析[J].水土保持通报,2015, 35(5):323-326.[QIAO Li,WU Linrong,ZHANG Gaojian.Temporal and spatial changes of land surface temperature in China in recent 50 years[J].Bulletin of Soil and Water Conservation,2015,35(5):323-326.] [6]冉津江,季明霞,黄建平,等.中国干旱半干旱地区的冷季快速增温[J].高原气象,2014,33(4):947-956.[RAN Jinjiang,JI Mingxia,HUANG Jianpin,et al.Enhanced cold season warming in arid and semi-arid regions of China[J].Plateau Meteorology,2014,33(4):947-956.] [7]黄清瀚,陈海山,华文剑.近30 a来中国干旱生态区增暖放大现象及其与植被覆盖的联系[J].气候与环境研究,2018,23(1):72-82.[HUANG Qinghan,CHEN Haishan,HUA Wenjian.Stronger warming amplification over arid ecoregions and its relationship to vegetation cover in China since 1982[J].Climatic and Environmental Research,2018,23(1):72-82.] [8]ZHOU Liming,CHEN Haishan,HUA Wenjian,et al. Mechanisms for stronger warming over drier ecoregions observed since 1979[J].Springer Berlin Heidelberg,2016,47(9):2955-2974. [9]王明娜.21世纪初中国北方半干旱区土地利用变化对地表温度的影响[J].气候与环境研究2016,21(1):65-77.[WANG Mingna. Impact of land use and cover change in the semi-arid regions of China on the temperature in the early 21st century[J].Climatic and Environmental Research,2016,21(1):65-77.] [10]热伊莱•卡得尔,玉苏甫•买买提,玉素甫江•如素力,等.伊犁河谷2001—2014年地表温度时空分异特征[J].中国沙漠, 2018,38(3):196-203.[KADEER Reyilai,MAIMAITI Yusufu,RUSULI Yusufujiang,et al.Spatial-temporal variation of land surface temperature in the Ili River Valley during 2001-2014[J].Journal of Desert Research,2018,38(3):196-203.] [11]武正丽,贾文雄,赵珍,等.2000—2012年祁连山植被覆盖变化及其与气候因子的相关性[J].干旱区地理,2015,38(6):1241-1252.[WU Zhengli,JIA Wenxiong,ZHAO Zhen,et al.Spatial-temporal variations of vegetation and its correlation with climatic factors in Qilian Mountains from 2000 to 2012[J].Arid Land Geography,2015,38(6):1241-1252.] [12]巩宁刚,孙美平,闫露露,等.1979—2016年祁连山地区大气水汽含量时空特征及其与降水的关系[J]. 干旱区地理,2017,40(4):762-771. [GONG Ninggang,SUN Meiping,YAN Lulu,et al. Temporal and spatial characteristics of atmospheric water vapor and its relationship with precipitation in Qilian Mountains during 1979-2016[J]. Arid Land Geography,2017,40(4):762-771.] [13]徐浩杰,杨太保,曾彪.2000—2010年祁连山植被MODIS 〖WTBX〗NDVI〖WTBZ〗的时空变化及影响因素[J].干旱区资源与环境,2012,26(11):87-91.[XU Haojie,YANG Taibao,ZENG Biao.Spatial-temporal changes of vegetation in Qilian Mountains from 2000 to 2010 based on MODIS NDVI data and its affecting factors[J].Journal of Arid Land Resources and Environment,2012,26(11):87-91.] [14]蒋友严,杜文涛,黄进,等.2000—2015年祁连山植被变化分析[J].冰川冻土,2017,39(5):1130-1136. [JIANG Youyan,DU Wentao,HUANG Jin,et al. Analysis of vegetation changes in the Qilian Mountains during 2000-2015[J]. Journal of Glaciology and Geocryology,2017,39(5):1130-1136.] [15]贾文雄,赵珍,俎佳星,等.祁连山不同植被类型的物候变化及其对气候的响应 [J].生态学报,2016,36(23):7826-7840. [JIA Wenxiong,ZHAO Zhen,ZU Jiaxing,et al. Phenological variation in different vegetation types and their response to climate change in the Qilian Mountains,China,1982-2014[J].Acta Ecologica Sinica,2016,36(23):7826-7840.] [16]戴声佩,张勃,王海军,等.1999—2007年祁连山区植被指数时空变化[J].干旱区研究,2010,27(4):585-591.[DAI Shengpei,ZHANG Bo,WANG Haijun,et al. Spatialtemporal variation of vegetation NDVI in the Qilian Mountains during the period from 1999 to 2007[J].Arid Zone Research,2010,27(4):585-591.] [17]刘亚荣,贾文雄,黄玫,等.近51a来祁连山植被净初级生产力对气候变化的响应[J].西北植物学报,2015,35(3):601-607.[LIU Yarong,JIA Wenxiong,HUANG Mei,et al.Response of vegetation net primary productivity to climate change in the Qilian Mountains since recent 51years[J].Acta Botanica Boreali-Occidentalia Sinica,2015,35(3):601-607.] [18]王强,张勃,戴声佩,等.三北防护林工程区植被覆盖变化与影响因子分析[J].中国环境科学, 2012,32(7):1302-1308.[WANG Qiang,ZHANG Bo,DAI Shengpei,et al.Analysis of the vegetation cover change and relationship with factors in the Three-North Shelter Forest Program[J].China Environmental Science,2012,32(7):1320-1308.] [19]GUO Xiaoyi,ZHANG Hongyan,WANG Yeqiao,et al. Comparison of the spatiotemporal dynamics of vegetation between the Changbai Mountains of eastern Eurasia and the Appalachian Mountains of eastern North America[J]. Journal of Mountain Science,2018,15(1):1-12. [20]马磊,闫浩文,何毅,等.2001—2015年喜马拉雅南麓地区植被变化遥感监测[J].干旱区地理,2017,40(2):405-414. [MA Lei,YAN Haowen,HE Yi,et al.Vegetation changes in south Himalayas areas based on remote sensing monitoring during 2001-2015[J].Arid Land Geography,2017,40(2):405-414.] [21]HU Ling,FAN Wenjie,REN Huazhong,et al. Spatiotemporal dynamics in vegetation GPP over the great Khingan Mountains using GLASS products from 1982 to 2015[J]. Remote Sensing, 2018,10(3):488-500. [22]曹广超,付建新,李玲琴,等.1960—2014年祁连山南坡及其附近地区气温时空变化特征[J].水土保持研究,2018,25(3):88-96.[CAO Guangchao,FU Jianxin,LI Lingqin, et al.Analysis on temporal and spatial variation characteristics of air temperature in the south slope of Qilian Mountains and its nearby regions during the period from 1960 to 2014[J].Research of Soil and Water Conservation,2018,25(3):88-96.] [23]商沙沙,廉丽姝,马婷,等. 近54 a中国西北地区气温和降水的时空变化特征[J].干旱区研究,2018,35(1):68-76.[SHANG Shasha,LIAN Lishu,MA Ting,et al.Spatiotemporal variation of temperature and precipitation in northwest China in recent 54 years[J].Arid Zone Research,2018,35(1):68-76.] [24]李斌,王慧敏,秦明周,等.〖WTBX〗NDVI〖WTBZ〗、NDMI与地表温度关系的对比研究[J].地理科学进展, 2017,36(5):585-596. [LI Bin,WANG Huimin,QIN Mingzhou,et al.Comparative study on the correlations between NDVI,NDMI and LST[J].Progress in Geography,2017,36(5):585-596.] [25]邱丽莎,张立峰,何毅,等.2000—2017年祁连山植被动态变化遥感监测[J].遥感信息,2019,34(4):97-107. [QIU Lisha,ZHANG Lifeng,HE Yi,et al.Vegetation dynamic change of remote sensing monitoring in Qilian Mountain in recent years[J].Remote Sensing Information,2019,34(4):97-107.] [26]付建新,曹广超,李玲琴,等. 1960—2014年祁连山中东段及其附近地区气温时空变化特征[J].干旱区研究,2018,35(3):549-561.[FU Jianxin,CAO Guangchao,LI Lingqin,et al. Spatiotemporal variation of air temperature in the middle and eastern parts of the Qilian Mountains and the nearby regions during the period of 1960-2014[J]. Arid Zone Research,2018,35(3):549-561.] [27]屈创,马金辉,夏燕秋,等. 基于MODIS数据的石羊河流域地表温度空间分布[J].干旱区地理,2014,37(1):125-133.[QU Chuang,MA Jinhui,XIA Yanqiu,et al. Spatial distribution of land surface temperature retrieved from MODIS data in Shiyang River Basin[J].Arid Land Geography,2014,37(1):125-133.] [28]周婷,张寅生,高海峰,等.青藏高原高寒草地植被指数变化与地表温度的相互关系[J].冰川冻土,2015,37(1):58-69.[ZHOU Ting,ZHANG Yinsheng,GAO Haifeng,et al.Relationship between vegetation index and ground surface temperature on the Tibetan Plateau alpine grassland[J].Journal of Glaciology and Geocryology,2015,37(1):58-69.] [29]刘旻霞,赵瑞东,邵鹏,等. 近15 a黄土高原植被覆盖时空变化及驱动力分析[J].干旱区地理,2018,41(1):99-108. [LIU Minxia,ZHAO Ruidong,SHAO Peng,et al. Temporal and spatial variation of vegetation coverage and its driving forces in the Loess Plateau from 2001 to 2015[J].Arid Land Geography,2018,41(1):99-108.] [30]刘振元,张杰,陈立.青藏高原植被退化对高原及周边地区大气环流的影响[J].生态学报,2018,38(1):132-142. [LIU Zhenyuan,ZHANG Jie,CHEN Li.Effects of vegetation degradation on atmospheric circulation over the Tibetan Plateau and its surrounding areas[J].Acta Ecologica Sinica,2018,38(1):132-142.] [31]DANIELA S,MASSIMO A,PIETRO A B. Seasonality of MODIS LST over southern Italy and correlation with land cover, topography and solar radiation[J]. European Journal of Remote Sensing,2014,47(1):133-152.
文章导航

/