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适于ALOS图像植被信息提取的新植被指数

DOI: 10.6046/gtzyyg.2013.04.08, PP. 48-52

Keywords: ALOS,植被指数,基于植被样本的植被指数(VSVI),植被覆盖度

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Abstract:

针对现有植被指数不适用于ALOS图像植被信息提取的问题,从分析植被的光谱特征入手,提出了一种基于植被样本的植被指数(vegetationsample-basedvegetationindex,VSVI),并通过数学公式推导证明了VSVI仅与植被的光谱信息有关,与土壤背景无关,具有一定的消除土壤背景影响的能力。利用该植被指数和采用阈值分割方法提取了南京市某区域ALOS图像中的植被信息,并与差值植被指数,比值植被指数、归一化差值植被指数及土壤调节植被指数等其他植被指数的植被信息提取结果进行了比较。研究结果表明,该文提出的VSVI植被指数能够克服其他植被指数的缺点,植被信息提取精度分别提高了21.7%,27.5%,14%和9.5%。

References

[1]  王树根.日本ALOS卫星简介[J].测绘信息与工程,2000(1):45-46. Wang S G.The profile of Japans ALOS satellite[J].Journal of Geomatics,2000(1):45-46.
[2]  熊金国,王世新,周艺.不同指数模型提取ALOS AVNIR-2影像中水体的敏感性和精度分析[J].国土资源遥感,2010,22(4):46-50. Xiong J G,Wang S X,Zhou Y.A sensitivity analysis and accuracy assessment of different water extraction index models based on ALOS AVNIR - 2 data[J].Remote Sensing for Land and Resources,2010,22(4):46-50.
[3]  何宇华,谢俊奇,刘顺喜.ALOS卫星遥感数据影像特征分析及应用精度评价[J].地理与地理信息科学,2008,24(2):23-26. He Y H,Xie J Q,Liu S X.Image characteristics analysis and application accuracy assessment of ALOS data[J].Geography and Geo-Information Science,2008,24(2):23-26.
[4]  邵晓敏,刘勇.基于纹理的乌兰布和沙漠地区植被信息提取[J].遥感技术与应用,2010,25(5):687-693. Shao X M,Liu Y.Deriving vegetation information in Ulan Buh desert based on texture[J].Remote Sensing Technology and Application,2010,25(5):687-693.
[5]  李玲,王红,刘庆生,等.基于纹理特征和支持向量机的ALOS图像土地覆被分类[J].国土资源遥感,2011,23(4):58-63. Li L,Wang H,Liu Q S,et al.Land cover classification using ALOS image based on textural features and support vector machine[J].Remote Sensing for Land and Resources,2011,23(4):58-63.
[6]  伍蓝.基于ALOS等数据的盐城湿地植被分类及土地覆盖时 空变化研究[D].南京:南京师范大学,2008. Wu L.Fine classification of vegetation and land-cover change analysis of wetlands based on ALOS and other image data in Yancheng[D].Nanjing:Nanjing Normal University,2008.
[7]  黄铁栏,苏华,王云鹏.NDVI/NDWI/DEM决策树方法在东 莞ALOS影像土地利用分类中的应用[J].华南师范大学学报:自然科学版,2012,44(1):134-139. Huang T L,Su H,Wang Y P.Decision tree method on NDVI/NDWI/DEM for land use classification of ALOS image in Dongguan City[J].Journal of South China Normal University: Natural Science Edition,2012,44(1):134-139.
[8]  徐爽,沈润平,杨晓月.利用不同植被指数估算植被覆盖度的比较研究[J].国土资源遥感,2012,24(4):95-100. Xu S,Shen R P,Yang X Y.A comparative study of different vegetation indices for estimating vegetation coverage based on the dimidiate pixel model[J].Remote Sensing for Land and Resources,2012,24(4):95-100.
[9]  Richardson A J,Wiegand C L.Distinguishing vegetation from soil background information[J].Photogrammetric Engineering and Remote Sensing,1977,43(12):1541-1552.
[10]  Jordan C F.Derivation of leaf area index from quality of light on the foresr floor[J].Ecology,1969,50(4):663-666.
[11]  Rouse J W,Haas R H,Schell J A,et al.Monitoring vegetation systems in the great plains with ERTS[C]//Proceedings of third earth resources technology satellite-1 symposium,Greenbelt NASASP - 351,1974:310-317.
[12]  Huete A R.A soil-adjusted vegetation index(SAVI)[J].Remote Sensing of Environment,1988,25(3):295- 309.
[13]  Pinty B,Verstraete M M.GEMI:A non-linear index to monitor global vegetation from satellites[J].Vegetation,1992,101(1):15-20.
[14]  唐世浩,朱启疆,王锦地,等.三波段梯度差植被指数的理论基础及其应用[J].中国科学:D缉,2003,33(11):1094-1102. Tang S H,Zhu Q J,Wang J D,et al.Theoretical basis of the tri-band gradient difference vegetation index and its application[J].Science in China:Series D,2003,33(11):1094-1102.

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