基于MODIS-Landsat时空融合的陕北黄土高原植被覆盖变化研究
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摘要
陕北黄土高原地形复杂,水土流失现象较为严重,精确监测植被的时空变化对于该区域的生态环境建设具有重要意义。文中基于ESTARFM时空分辨率融合模型,利用MODIS和Landsat数据获取2008—2016年6～8月陕北黄土高原的Landsat NDVI时序数据,分析陕北黄土高原植被覆盖的时空变化情况及对气候因子的响应。结论:①运用ESTARFM融合模型得到的Landsat NDVI数据与真实Landsat NDVI数据在植被信息的表达方面具有较高的相关性,融合结果可以应用于后续植被覆盖度的估算。②2008—2016年陕北黄土高原地区植被覆盖呈现较为明显的增加趋势;空间分布上呈现由东南向西北逐渐递减的特点,植被覆盖等级结构好转;研究区78%的地区植被改善效果良好;各土地利用类型植被覆盖度均呈波动增加趋势。③整体上植被覆盖度与同期气温和降水的相关性呈现较为明显的空间分异,其中植被覆盖度对降水因子的响应更为敏感。ESTARFM算法综合了高空间分辨率数据的空间细节表达力和高时间分辨率数据的快速时序变化能力,为陕北黄土高原高精度的植被动态监测研究提供了有效依据。
The loess plateau in Northern Shaanxi has complex topography and the soil erosion is serious. Thus,the rapid and accurate monitor of the spatial and temporal changes of vegetation can provide scientific reference for the study of soil and water conservation and analyzing regional ecological environment. Based on MODIS and Landsat data,this study used ESTARFM to simulate Landsat NDVI data that from Loess Plateau in Northern Shaanxi Province from june to august between of 2008 and 2016,then to analyze the spatial and temporal variation of vegetation cover of Loess Plateau in Northern Shaanxi Province from 2008 to 2016 and its response to climatic factors. Conclusions: ①The Landsat-NDVI data acquired by ESTARFM was consistent to the real Landsat data in terms of the expression of vegetation information,the fusion results can be applied to the estimation of subsequent vegetation coverage. ②The vegetation coverage in the whole region showed an increasing trend from 2008 to 2016. The spatial distribution shows a gradual decline from southeast to northwest and the vegetation coverage structure is improved. The proportion of the area with an increasing trend was 78% and the vegetation coverage of all land use types showed a trend of fluctuation and increase. ③On the whole,the correlation between vegetation coverage and temperature and precipitation were obviously different in different regions. The vegetation growth is sensitive to precipitation. By spatial and temporal data fusion to combine the spatial detail expression of high spatial resolution data and the ability of rapid time series change of high temporal resolution data,it can provide an effective basis for high-precision vegetation dynamic monitoring and research in the Loess Plateau in Northern Shaanxi Province.
The loess plateau in Northern Shaanxi has complex topography and the soil erosion is serious. Thus,the rapid and accurate monitor of the spatial and temporal changes of vegetation can provide scientific reference for the study of soil and water conservation and analyzing regional ecological environment. Based on MODIS and Landsat data,this study used ESTARFM to simulate Landsat NDVI data that from Loess Plateau in Northern Shaanxi Province from june to august between of 2008 and 2016,then to analyze the spatial and temporal variation of vegetation cover of Loess Plateau in Northern Shaanxi Province from 2008 to 2016 and its response to climatic factors. Conclusions: ①The Landsat-NDVI data acquired by ESTARFM was consistent to the real Landsat data in terms of the expression of vegetation information,the fusion results can be applied to the estimation of subsequent vegetation coverage. ②The vegetation coverage in the whole region showed an increasing trend from 2008 to 2016. The spatial distribution shows a gradual decline from southeast to northwest and the vegetation coverage structure is improved. The proportion of the area with an increasing trend was 78% and the vegetation coverage of all land use types showed a trend of fluctuation and increase. ③On the whole,the correlation between vegetation coverage and temperature and precipitation were obviously different in different regions. The vegetation growth is sensitive to precipitation. By spatial and temporal data fusion to combine the spatial detail expression of high spatial resolution data and the ability of rapid time series change of high temporal resolution data,it can provide an effective basis for high-precision vegetation dynamic monitoring and research in the Loess Plateau in Northern Shaanxi Province.
引文
[1]张含玉,方怒放,史志华,等.黄土高原植被覆盖时空变化及其对气候因子的响应[J].生态学报,2016,36(13):3960-3968.
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[14]王涛,于冬雪,杨强.陕北黄土高原地区降水时空变化特征[J].水资源与水工程学报,2014,25(6):24-28.
[15]李双双,延军平,万佳,近10年陕甘宁黄土高原区植被覆盖时空变化特征[J].地理学报,2012,67(7):961-968.
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[17]JARIHANI A A,MCVICAR T R,VAN NIEL T G,et al.Blending landsat and MODIS data to generate multispectral indices:A comparison of"Index-then-Blend"and"Blend-then-Index"approaches[J].Remote Sensing,2014,6(10):9213-9238.
[18]赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003.
[19]刘宪锋,杨勇,任志远,等.2000-2009年黄土高原地区植被覆盖度时空变化[J].中国沙漠,2013,33(4):1244-1249.
[20]杜灵通,田庆久.宁夏植被覆盖动态变化及与气候因子的关系[J].中国沙漠,2012,32(5):1479-1484.
[21]HERRMANN S M,ANYAMBA A,TUCKER C J.Recent trends in vegetataion dynamics in the African Sahel and their relationship to climate[J].Global Environmental Change,2005,15(4):394-404.
[22]卢响军,周益民,候秀玲,等.基于土地利用/覆盖的干旱绿洲区植被覆盖度变化---以新疆生产建设兵团第八师为例[J].中国生态农业学报,2015,23,(2):247-255.
[23]肖强,陶建平,肖洋,等.黄土高原近10年植被覆盖的动态变化及驱动力[J].生态学报,2016,36(23):7594-7602.
[24]赵安周,张安兵,刘海新,等.退耕还林(草)工程实施前后黄土高原植被覆盖时空变化分析[J].自然资源学报,2017,32(3):449-460.
[25]张玉东,谭红兵.黄土高原典型干旱区退耕还林后植被覆盖变化研究[J].生态科学,2017,36(1):139-146.
[26]郭敏杰,张亭亭,张建军,等.1982-2006年黄土高原地区植被覆盖度对气候变化的响应[J].水土保持研究,2014,21(5):35-40.
[2]朱会利,杨改河,韩磊.延安市退耕过程植被覆盖度变化及其影响因子分析[J].农业机械学报,2015,46(8):273-279.
[3]李钰溦,贾坤,魏香琴,等.中国北方地区植被覆盖度遥感估算及其变化分析[J].国土资源遥感,2015,27(2):112-117.
[4]DAVRANCHE A,LEFEBVRE G,PPULIN B.Wetland monitoringusing classification trees and SPOT5 seasonal time series[J].Remote Sensing of Environment,2010,114(3):552-562.
[5]WU CY,CHEN J M,HUANG N.Predicting gross primaryproduction from the enhanced vegetation index and photosynthetically active radiation:Evaluation and calibration[J].Remote Sensing of Environment,2011,115(12):3424-3435.
[6]李登科.陕北黄土高原丘陵沟壑区植被覆盖变化及其对气候的响应[J].西北植物学报,2009,29(5):0867-0873.
[7]李勇,张建辉,杨俊诚,等.陕北黄土高原陡坡耕地土壤侵蚀变异的空间格局[J].水土保持学报,2000,14(4):17-21.
[8]宋富强,邢开雄,刘阳,等.基于MODIS/NDVI的陕北地区植被动态监测与评价[J].生态学报,2011,31(2):0354-0363.
[9]湛青青,刘咏梅,王雷,等.陕北黄土高原植被覆盖度动态变化分析研究[J].测绘与空间地理信息,2017,40(12):42-46.
[10]孙锐,荣媛,苏红波,等.MODIS和HJ-1 CCD数据时空融合重构NDVI时间序列[J].遥感学报,2016,20(3):361-372.
[11]郝贵斌,吴波,张立福,等.ESTARFM模型在西藏色林错湖面积时空变化中的应用分析(1976-2014年)[J].地球信息科学学报,2016,18(6):833-846.
[12]ZHU X L,CHEN J,GAO F,et al.An enhanced spatial and temporal adaptive reflectance fusion model for cmplex heterogeneous regions[J].Remote Sensing of Environment,2010,114:2610-2623.
[13]邬明全,牛铮,王长耀.多源遥感数据时空融合模型应用分析[J].地球信息科学,2014,16(5):776-782.
[14]王涛,于冬雪,杨强.陕北黄土高原地区降水时空变化特征[J].水资源与水工程学报,2014,25(6):24-28.
[15]李双双,延军平,万佳,近10年陕甘宁黄土高原区植被覆盖时空变化特征[J].地理学报,2012,67(7):961-968.
[16]刘志红,郭伟玲,杨勤科等.近20年黄土高原不同地貌类型区植被覆盖变化及原因分析[J].中国水土保持科学,2011,9(1):16-23.
[17]JARIHANI A A,MCVICAR T R,VAN NIEL T G,et al.Blending landsat and MODIS data to generate multispectral indices:A comparison of"Index-then-Blend"and"Blend-then-Index"approaches[J].Remote Sensing,2014,6(10):9213-9238.
[18]赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003.
[19]刘宪锋,杨勇,任志远,等.2000-2009年黄土高原地区植被覆盖度时空变化[J].中国沙漠,2013,33(4):1244-1249.
[20]杜灵通,田庆久.宁夏植被覆盖动态变化及与气候因子的关系[J].中国沙漠,2012,32(5):1479-1484.
[21]HERRMANN S M,ANYAMBA A,TUCKER C J.Recent trends in vegetataion dynamics in the African Sahel and their relationship to climate[J].Global Environmental Change,2005,15(4):394-404.
[22]卢响军,周益民,候秀玲,等.基于土地利用/覆盖的干旱绿洲区植被覆盖度变化---以新疆生产建设兵团第八师为例[J].中国生态农业学报,2015,23,(2):247-255.
[23]肖强,陶建平,肖洋,等.黄土高原近10年植被覆盖的动态变化及驱动力[J].生态学报,2016,36(23):7594-7602.
[24]赵安周,张安兵,刘海新,等.退耕还林(草)工程实施前后黄土高原植被覆盖时空变化分析[J].自然资源学报,2017,32(3):449-460.
[25]张玉东,谭红兵.黄土高原典型干旱区退耕还林后植被覆盖变化研究[J].生态科学,2017,36(1):139-146.
[26]郭敏杰,张亭亭,张建军,等.1982-2006年黄土高原地区植被覆盖度对气候变化的响应[J].水土保持研究,2014,21(5):35-40.