基于归一化植被指数和地表反照率的土地沙漠化遥感监测研究
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摘要
目的对土地沙漠化状况进行监测和评价,研究土地沙漠化变化及趋势预测,为恢复植被覆盖和改善生态环境提供依据.方法以新疆昌吉为研究区域,采用Landsat遥感影像,经过预处理后通过提取归一化植被指数和地表反照率的空间特征,获取沙漠化差值指数,分析与评价新疆昌吉地区的沙漠化程度.结果新疆昌吉地区2011年沙漠面积为62.29%,裸地面积为26.97%;2013年沙漠面积为59.92%,裸地面积为28.59%;2015年的沙漠面积为77.73%,裸地面积为18.14%.2011—2013年,沙漠化差值指数增大,沙漠面积减少;2013—2015年,沙漠化差值指数显著减小,土地沙漠化面积大幅度增加;沙漠化等级由中度沙漠化演变为轻度沙漠化,又由轻度沙漠化变为重度沙漠化.结论沙漠化差值指数与沙漠化等级呈负相关性,DDI可正确地反映土地沙漠化的变化情况.
To provide the basis for restoring vegetation cover and improving the ecological environment,the desertification status of land was monitored and evaluated to study the desertification change and predict the trend.From the Landsat remote sensing image in Changji and surrounding areas of Xinjiang,the spatial characteristics of normalized vegetation index(NDVI)and surface albedo(Albedo)were extracted to obtain the desertification difference index(DDI)which is used to analysis and evaluate its desertification.As a result,in 2011 the desert area was 62.29% and the bare land area is 26.97%;in 2013 the desert area is 59.92% and the bare land area is 28.59%;in 2015 the desert area is 77.73%,and the bare land area is 18.14%.From 2011 to 2013,the desertification difference index increased and the desert area is reduced;from 2013 to 2015,the desertification difference index has decreased significantly and the desertification area of ?land has increased significantly.The desertification grade changed from moderate desertification to mild desertification,and from mild desertification to severe desertification.The desertification difference index(DDI)is negatively correlated with desertification grade,and DDI can correctly reflect the change of land desertification.
To provide the basis for restoring vegetation cover and improving the ecological environment,the desertification status of land was monitored and evaluated to study the desertification change and predict the trend.From the Landsat remote sensing image in Changji and surrounding areas of Xinjiang,the spatial characteristics of normalized vegetation index(NDVI)and surface albedo(Albedo)were extracted to obtain the desertification difference index(DDI)which is used to analysis and evaluate its desertification.As a result,in 2011 the desert area was 62.29% and the bare land area is 26.97%;in 2013 the desert area is 59.92% and the bare land area is 28.59%;in 2015 the desert area is 77.73%,and the bare land area is 18.14%.From 2011 to 2013,the desertification difference index increased and the desert area is reduced;from 2013 to 2015,the desertification difference index has decreased significantly and the desertification area of ?land has increased significantly.The desertification grade changed from moderate desertification to mild desertification,and from mild desertification to severe desertification.The desertification difference index(DDI)is negatively correlated with desertification grade,and DDI can correctly reflect the change of land desertification.
引文
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[15] 李苗苗.植被覆盖度的遥感估算方法研究[D].北京:中科院研究生院,2003.(LI Miaomiao.Research on remote sensing estimation methods of vegetation coverage[D].Beijing:Graduate School of Chinese Academy of Sciences,2003.)
[16] 贾树海,王潇雪,杨亮.辽北农牧交错带土地荒漠化及景观格局变化研究[J].中国水土保持,2014,18(5):51-55.(JIA Shuhai,WANG Xiaoxue,YANG Liang.Study on land desertification and landscape pattern change in the farming-Pastoral ecotone of northern Liaoning[J].Soil and water conservation in China,2014,18(5):51-55.)
[17] 侯晓真,张书毕,宁晓刚,等.基于TM影像波段运算的沙漠变化检测分析[J].大地测量与地球动力学,2013(6):145-149.(HOU Xiaozhen,ZHANG Shubi,NING Xiaogang,et al.Desert change detection and analysis based on TM image band operation[J].Journal of geodesy and geodynamics,2013(6):145-149.)
[18] 曾永年,向南平,冯兆东,等.Albedo-NDVI特征空间及沙漠化遥感监测指数研究[J].地理科学,2006,26(1):75-81.(ZENG Yongnian,XIANG Nanping,FENG Zhaodong,et al.Albedo-NDVI space and remote sensing synthesis index models for desertification monitoring[J].Scientia geographica sinica,2006,26(1):75-81.)
[2] 陈佳楠,邓芳,乌恩图,等.浑善达克典型区域沙化土地十年遥感监测分析[J].中国农学通报,2015,31(29):227-234.(CHEN Jianan,DENG Fang,WU Entu,et al.10 years remote sensing monitoring analysis of desertification land of representative region in Hunshandake[J].Chinese agricultural science bulletin,2015,31(29):227-234.)
[3] 韩刚.基于多尺度遥感数据的荒漠化草原土壤含水率监测研究[D].呼和浩特:内蒙古农业大学,2017.(HAN Gang.Study on monitoring soil moisture content ofdesertifiedgrassland based on multi-scale remote sensing data[D].Hohhot:Inner Mongolia Agricultural University,2017.)
[4] 潘竟虎,秦晓娟.基于植被指数-反照率特征空间的沙漠化信息遥感提取:以张掖绿洲及其附近区域为例[J].测绘科学,2010,32(3):193-195.(PAN Jinghu,QIN Xiaojuan.Extracting desertification from landsat imagery using a feature space composed of vegetation index and albedo:a case study of Zhangye oasis and its adjacent areas[J].Science of surveying and mapping,2010,32(3):193-195.)
[5] 曾永年,冯兆东.黄河源区土地沙漠化时空变化遥感分析[J].地理学报,2007,62(5):529-536.(ZENG Yongnian,FENG Zhaodong.Spatial and temporal changes of desertification in the headwater area of the Yellow River using remote sensing[J].Acta geographica sinica,2007,62(5):529-536.)
[6] 官雨薇,何彬彬.基于遥感影像的全球沙漠化指数构建及趋势分析[D].成都:电子科技大学,2015.(GUAN Yuwei,HE Binbin.Construction and trend analysis of global desertification index based on remote sensing image[D].Chengdu:University of Electronic Science and Technology of China,2015.)
[7] 陶安琪.被动微波遥感纳木错湖冰变化研究[D].南京:南京大学,2014.(TAO Anqi.Research on the variation of Namco Lakeice by passive microwave remote sensing[D].Nanjing:Nanjing University,2014.)
[8] 顾余庆.基于遥感与GIS的基本农田调整方法研究:以东海县为例[D].南京:南京师范大学,2014.(GU Yuqing.Research on demarcate method of basic farmland based on RS and GIS:a case of donghai county[D].Nanjing:Nanjing Normal University,2014.)
[9] 庄晨辉,陈铭潮,李峥.遥感技术在土地沙化监测中的应用[J].福建林学院学报,2006,26(4):324-327.(ZHUANG Chenhui,CHEN Mingchao,LI Zheng.Application of remote sensing technology in land desertification monitoring[J].Journal of Fujian college of forest,2006,26(4):324-327.)
[10] 彭立.岷江上游生态水信息指标参数遥感反演与变化监测[D].成都:成都理工大学,2016.(PENG Li.Remote sensing inversion and change monitoring of ecological water information index parameters in the upper reaches of MinjiangRiver[D].Chengdu:Chengdu University of Technology,2016.)
[11] 程洪.基于数字图像处理的玉米品种识别研究[D].保定:河北农业大学,2007.(CHENG Hong.Study on corn species identification based on digital image processing[D].Baoding:Hebei Agricultural University,2007.)
[12] 郁斢兰.海上交通枢纽建设的悬浮泥沙数值模拟与遥感监测研究:以大连海上机场为例[D].大连:大连海事大学,2015.(YU Yulan.Remote sensing and numerical simulation of suspended sediment pollution caused by offshore transportation hub construction:the background of Dalian offshore airport[D].Dalian:Dalian Maritime University,2015.)
[13] LIANG S.Nanowband to broadband conversions of land surface albedo:algorithms[J].Remote sensing of environment,2001,76(2):213-238.
[14] 袁宏波.黄河源区玛曲县草地沙化动态监测及区域景观结构分析研究[D].兰州:甘肃农业大学,2006.(YUAN Hongbo.Grassland sandification dynamic monitoring and landscape pattern analysis of MaquCounty in sourceregion of yellow river[D].Lanzhou:Gansu Agricultural University,2006.)
[15] 李苗苗.植被覆盖度的遥感估算方法研究[D].北京:中科院研究生院,2003.(LI Miaomiao.Research on remote sensing estimation methods of vegetation coverage[D].Beijing:Graduate School of Chinese Academy of Sciences,2003.)
[16] 贾树海,王潇雪,杨亮.辽北农牧交错带土地荒漠化及景观格局变化研究[J].中国水土保持,2014,18(5):51-55.(JIA Shuhai,WANG Xiaoxue,YANG Liang.Study on land desertification and landscape pattern change in the farming-Pastoral ecotone of northern Liaoning[J].Soil and water conservation in China,2014,18(5):51-55.)
[17] 侯晓真,张书毕,宁晓刚,等.基于TM影像波段运算的沙漠变化检测分析[J].大地测量与地球动力学,2013(6):145-149.(HOU Xiaozhen,ZHANG Shubi,NING Xiaogang,et al.Desert change detection and analysis based on TM image band operation[J].Journal of geodesy and geodynamics,2013(6):145-149.)
[18] 曾永年,向南平,冯兆东,等.Albedo-NDVI特征空间及沙漠化遥感监测指数研究[J].地理科学,2006,26(1):75-81.(ZENG Yongnian,XIANG Nanping,FENG Zhaodong,et al.Albedo-NDVI space and remote sensing synthesis index models for desertification monitoring[J].Scientia geographica sinica,2006,26(1):75-81.)