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2020 , Vol. 43 >Issue 4: 1023 - 1032

DOI: https://doi.org/10.12118/j.issn.1000-6060.2020.04.17

地球信息科学

基于多时相Landsat影像的中亚地区植被覆盖遥感监测

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  • 1 西藏林芝市气象局,西藏 林芝 860000;
    2 南京农业大学资源与环境科学学院,江苏 南京 210095;
    3 南京大学地理与海洋科学学院,江苏 南京 210023
王华（1989–）,女,四川犍为人,在读硕士,工程师,研究方向为植被遥感监测. E-mail：825222166@qq.com

收稿日期: 2019-06-19

  修回日期: 2020-03-20

  网络出版日期: 2020-11-18

基金资助

西藏自治区科技计划项目（XZ201801-GB-12）; 国家自然科学基金项目（41472207,41631176）资助

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Vegetation coverage monitoring in the Central Asian countries using multi-temporal Landsat images

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  • 1 Nyingchi meteorological service. Nyingchi 860000,Xizang,China;
    2 College of Resources and Environmental Sciences,Nanjing Agricultural University,Nanjing 210095,Jiangsu,China;
    3 School of Geography and Ocean Science,Nanjing University,Nanjing 210023,Jiangsu,China

Received date: 2019-06-19

  Revised date: 2020-03-20

  Online published: 2020-11-18

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摘要

针对中亚地区的强生态脆弱性、高敏感性特征,有必要开展广域、长期的植被覆盖监测以匹配“绿色丝绸之路”的可持续发展目标。鉴于此,联合Landsat 5和Landsat 8卫星数据集,利用Google Earth Engine（GEE）地理空间数据云计算平台,估算了中亚地区1993—2018年间共12期的植被覆盖度。结果表明：（1）中亚地区植被覆盖总体水平较低,但也具有较为显著的空间异质性。（2）中亚地区1993—2018年间多数区域植被覆盖趋势较为稳定,哈萨克斯坦丘陵、费尔干纳盆地等区域植被覆盖度呈增加趋势,乌拉尔河流域和锡尔河流域等区域植被覆盖趋势为负。（3）植被覆盖度时序特征上,中亚地区1993—2018年间总体植被覆盖度累积增加3%,其中吉尔吉斯斯坦和塔吉克斯坦植被覆盖分别增加3.96%和5.86%。（4）裸土区呈退缩趋势,面积总计减少25.9×104 km2,低植被覆盖区、中植被覆盖区和高植被覆盖区范围在呈现出的振荡式增加。研究结合遥感大数据和地理云计算对中亚地区进行区域尺度的植被覆盖动态监测,能对中亚地区生态评估和演替分析提供技术支持和定量数据。

关键词： 植被覆盖监测; 中亚地区; GEE; 多时相Landsat影像; 归一化植被指数

本文引用格式

王华, 杨乾鹏, 田云杰, 郭山川, 唐鹏飞 . 基于多时相Landsat影像的中亚地区植被覆盖遥感监测[J]. 干旱区地理, 2020 , 43(4) : 1023 -1032 . DOI: 10.12118/j.issn.1000-6060.2020.04.17

Abstract

Central Asian regions with a typical temperate desert as well as grassland environment experience several ecological environmental problems such as water shortages and land degradation. Particularly in recent decades,the ecological disturbances caused by climate change and human activity have led to more consideration being given to environmental protection. As the most essential producer of an ecosystem,vegetation coverage status can directly affect an ecosystem’s function and structure. Therefore,to align with the sustainable development goal of the “Green Silk Road” ,there is a need to conduct vegetation coverage monitoring with wide-range and long-term abilities. In view of this,12 periods of vegetation coverage in the Central Asian regions from 1993 to 2018 were estimated using the Google Earth Engine geospatial data cloud computing platform from Landsat 5 together with Landsat 8 remote sensing data sets. To start,the research area boundary was used as the selected condition to filter the Landsat images. Through data preprocessing,including a cloud mask,filter,and split,we acquired 12 high-quality remote sensing images over the Central Asian regions. Then,we calculated the normalized difference vegetation index using the NIR and RED bands of the selected images. The dimidiate pixel model was used to estimate the vegetation coverage,followed by a linear regression analysis. The results showed as follows：（1） The overall level of vegetation coverage in Central Asia was low but had significant spatial heterogeneity. （2） The vegetation coverage change trend of most regions in Central Asia between 1993 and 2018 was relatively stable. The vegetation coverage over the Kazakhstan Hills and Fergana Valley areas showed an increasing trend,while the vegetation coverage in the Ural River Basin and Syr Darya River Basin areas showed a negative trend. （3） In terms of the time series characteristics of the vegetation coverage,the total vegetation coverage increased by 3% in the Central Asian regions between 1993 and 2018,during which the vegetation coverage in Kyrgyzstan and Tajikistan increased by 3.96% and 5.86%,respectively. （4） The bare soil area showed a retreating trend,and its total area decreased by 259 000 km2. （5） Lastly,the low vegetation,middle vegetation,and high vegetation cover areas showed an oscillatory increase. Overall,this study combined remote sensing data with geographical cloud computing to monitor vegetation coverage on a regional scale in Central Asia to provide technical support and quantitative data for ecological assessment and succession analysis in Central Asia.

Key words： vegetation coverage monitoring; the Central Asian Regions; Google Earth Engine; multi-temporal Landsat images; NDVI

参考文献

[1] 杨莲梅,关学锋,张迎新. 亚洲中部干旱区降水异常的大气环流特征[J]. 干旱区研究,2018,35(2):249–259.
[YANG Lianmei,GUAN Xuefeng,ZHANG Yinxing.Study on atmospheric circulation characteristics of precipitation anomalies in arid region of Central Asia[J]. Arid Zone Research,2018,35(2):249–259.]
[2] 刘玉芝,吴楚樵,贾瑞,等. 大气环流对中东亚干旱半干旱区气候影响研究进展[J]. 中国科学:(地球科学),2018,48(9):1141–1152.
[LIU Yuzhi,WU Chuqiao,JIA Rui,et al.An overview of the influence of atmospheric circulation on the climate in arid and semi-arid region of Central and East Asia[J]. Science China (Earth Sciences), 2018,61(9):1183–1194.]
[3] 胡汝骥,姜逢清,王亚俊,等. 中亚(五国)干旱生态地理环境特征[J]. 干旱区研究,2014, 31(1):1–12.
[HU Ruji,JIANG Fengqing,WANG Yajun,et al.Arid ecological and geographical conditions in five countries of Central Asia[J]. Arid Zone Research, 2014, 31(1) :1–12.]
[4] 陈文倩,丁建丽,谭娇,等. 基于DPM-SPOT的2000—2015年中亚荒漠化变化分析[J]. 干旱区地理, 2018, 41(1):119–126.
[CHEN Wenqian,DING Jianli,TAN Jiao,et al.Desertification change in Central Asia based on DPM-SPOT from 2000 to 2015[J]. Arid Land Geography, 2018, 41(1):119–126.]
[5] 郑佳佳. 基于多源卫星数据的中亚地区湖泊水量变化监测研究[D]. 南京:南京大学,2017.
[ZHENG Jiajia.Monitering and analysis of lake water storage changes in Central Asia using multi-mission satellite date[D]. Nanjing: Nanjing University,2017.]
[6] 殷刚,孟现勇,王浩,等. 1982—2012年中亚地区植被时空变化特征及其与气候变化的相关分析[J]. 生态学报,2017,37(9):3149–3163.
[YIN Gang,MENG Xianyong,WANG Hao,et al.Spatial-temporal variation of vegetation and its correlation with climate change in Central Asia during the period of 1982–2012[J]. Acta Ecologica Sinica,2017,37(9):3149–3163.]
[7] 曾向红. “通”中之重:“丝绸之路经济带”建设在中亚[J]. 当代世界,2019,39(2):74–78.
[ZENG Xianghong.Priorities in interconnection: Silk Road Economic Belt in Central Asia[J]. Contemporary World,2019,39(2):74–78.]
[8] 蒋宇宁,王雅莉. “一带一路”倡议下中国与中亚地区贸易合作的竞争性与互补性研究[J]. 内蒙古社会科学,2018,39(5):128–135.
[JANG Yuning,WANG Yali.Research of the competitiveness and complementarity of trade cooperation between China and Central Asia under the Initiative of Belt and Road[J]. Inner Mongolia Social Sciences, 2018,39(05):128–135.]
[9] 盛任,万鲁河. 乌伊岭国家级自然保护区植被覆盖演变及其对气候突变的响应[J]. 生态学报,2019,39(9):3243–3256.
[SHENG Ren,WAN Luhe.Evolution of vegetation coverage and its response to abrupt climate change in the Wuyi Mountains National Nature Reserve[J]. Acta Ecologica Sinica, 2019,39(9):3243–3256.]
[10] PRAVALIE R,SIRODOEV I,PEPTENATU D.Detecting climate change effects on forest ecosystems in Southwestern Romania using Landsat TM NDVI data[J]. Journal of Geographical Sciences, 2014, 24(5):815–832.
[11] 刘斌,孙艳玲,王永财,等. 基于SPOT/NDVI华北地区植被变化动态监测与评价[J]. 干旱区资源与环境,2013,27(9):98–103.
[LIU Bin,SUN Yanling,WANG Yongcai,et al.Monitoring and assessment of vegetation variation in North China based on SPOT/NDVI[J]. Journal of Arid Land Resources and Environment,2013,27(9):98–103.]
[12] 郭铌. 植被指数及其研究进展[J]. 干旱气象,2003,21(4):71–75.
[GUO Ni.Vegetation Index and Its Advances[J]. Journal of Arid Meteorology, 2003,21(4):71–75.]
[13] 李云鹏,格根图,娜日苏,等. MERSI资料在内蒙古草原牧草产量估测中的应用研究[J]. 干旱区资源与环境,2012,26(9):154–159.
[LI Yunpeng,GE Gentu,NA Risu,et al.The applied research on estimating the yield of forage in Inner Mongolia grasslands using MERSI Data[J]. Journal of Arid Land Resources and Environment, 2012,26(9):154–159.]
[14] 廖清飞,张鑫,马全,等. 青海省东部农业区植被覆盖时空演变遥感监测与分析[J]. 生态学报,2014,34(20):5936–5943.
[LIAO Qingfei,ZHANG Xin,MA Quan,et al.Spatiotemporal variation of fractional vegetation cover and remote sensing monitoring in the eastern agricultural region of Qinghai Province[J]. Acta Ecologica Sinica,2014,34(20):5936–5943.]
[15] 贺振,贺俊平. 基于NOAA-NDVI的河南省冬小麦遥感估产[J]. 干旱区资源与环境,2013,27(5):46–52.
[HE Zhen,HE Junping.Estimation of winter wheat yield based on the NOAA–NDVI data[J]. Journal of Arid Land Resources and Environment, 2013,27(5):46–52.]
[16] 毛志春,宋宇,李蒙蒙. 基于MODIS反演数据的河套地区荒漠化研究[J]. 北京大学学报:自然科学版,2015,51(6):1102–1110.
[MAO Zhichun,SONG Yu,LI Mengmeng.Research of the Desertification in Hetao Area Based on MODIS Inversion Data[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2015,51(6):1102–1110.]
[17] PIAO S L, FANG J Y,ZHOU L M, et al.Interannual variations of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999[J]. Journal of Geophysical Research:Atmospheres,2003,108(D14):4401.
[18] ZHOU L M,TUCKER C J,KAUFMANN R K,et al.Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999[J]. Journal of Geophysical Research:Atmospheres,2001,106(D17):20069–20083.
[19] YUAN X L, LI L H, CHEN X,et al.Effects of precipitation intensity and temperature on NDVI-based grass change over northern China during the Period from 1982 to 2011[J]. Remote Sensing, 2015,7(8):10164–10183.
[20] 陈秀妍,付碧宏,时丕龙,等. 2000—2016年中亚天山植被变化及气候分异研究[J]. 干旱区地理,2019,42(1):162–171.
[CHEN Xiuyan,FU Bihong,SHI Pilong,et al.Vegetation dynamics in response to climate change in Tianshan,Central Asia from 2000 to 2016[J]. Arid Land Geography,2019,42(1): 162–171.]
[21] 刘春静,张丽,周宇,等. 中国新疆及中亚五国干旱区草地覆盖度反演与分析[J]. 草业科学,2016,33(5):861–870.
[LIU Chunjing,ZHANG Li,ZHOU Yu,et al.Retrieval and analysis of grassland coverage in arid Xinjiang,China and five countries of Central Asia[J]. Pratacultural Science,2016,33(5):861–870.]
[22] 张晓彤,谭衢霖,董晓峰,等. MODIS卫星数据中亚地区生态承载力评价应用[J]. 遥感信息,2018,33(4):55–63.
[ZHANG Xiaotong,TAN Qulin,DONG Xiaofeng,et al.Application of MODIS satellite fata in evaluating ecological carrying capacity of Central Asia[J]. Remote Sensing Information, 2018,33(4):55–63.]
[23] 夏楠,塔西甫拉提·特依拜,依力亚斯江·努尔麦麦提,等. 新疆准噶尔东部荒漠区植被覆盖度遥感监测与评估[J]. 环境科学与技术,2017,40(1):167–173.
[XIA Nan, TIYIP Tashpolat, NURMEMET Ilyas, et al.Remote sensing monitoring for assessing vegetation coverage in east Juggar Desert of Xinjiang[J]. Environmental Science & Technology, 2017, 40(1):167–173.]
[24] 徐涵秋,唐菲. 新一代Landsat系列卫星:Landsat 8遥感影像新增特征及其生态环境意义[J]. 生态学报,2013,33(11):3249–3257.
[XU Hanqiu,TANG Fei.Analysis of new characteristics of the first Landsat 8 image and their ecoenvironmental significance[J]. Acta Ecologica Sinica,2013,33(11):3249–3257.]
[25] GORELICK N,HANCHER M, DIXON M,et al.Google earth engine: Planetary-scale geospatial analysis for everyone[J]. Remote Sensing of Environment,2017,202(12):18–27.
[26] 郭华东,肖函. “一带一路”的空间观测与“数字丝路”构建[J]. 中国科学院院刊,2016,(5):535–541.
[GUO Huadong,XIAO Han.Earth observation for the Belt-Road and Digital Belt-Road Initiative[J]. Bulletin of Chinese Academy of Sciences,2016, (5):535–541.]
[27] 胡振华. 中亚五国志[M]. 北京:中央民族大学出版社,2006.
[HU Zhenhua.Records of the five Central Asian countries[M]. Beijing:China Minzu University Press,2006.]
[28] HU Z Y,LI Q X,CHEN X,et al.Climate changes in temperature and precipitation extremes in an alpine grassland of Central Asia[J]. Theoretical and Applied Climatology,2016,126(3–4):519–531.
[29] JU J,ROY D P,VERMOTE E,et al.Continental-scale validation of MODIS-based and LEDAPS Landsat ETM+ atmospheric correction methods[J]. Remote Sensing of Environment,2012,122(7):175–184.
[30] ZHU Z,WOODCOCK C E.Object-based cloud and cloud shadow detection in Landsat imagery[J]. Remote Sensing of Environment,2012,118(3):8–94.
[31] 贾坤,姚云军,魏香琴,等. 植被覆盖度遥感估算研究进展[J]. 地球科学进展,2013,28(7):774–782.
[JIA Kun, YAO Yunjun,WEI Xiangqin,et al.A review on fractional vegetation cover estimation using remote sensing[J]. Advances in Earth Science,2013,28(7):774–782.]
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