Journal of Jilin University(Earth Science Edition) ›› 2016, Vol. 46 ›› Issue (2): 617-626.doi: 10.13278/j.cnki.jjuese.201602306

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Mapping Land Use and Land Cover Through MISR Multi-Angle Imagery in the Lower Tarim River

Yang Xuefeng1, Wang Xuemei1,2, Mao Donglei1,2   

  1. 1. College of Geography Science and Tourism, Xinjiang Normal University, Urumqi 830054, China;
    2. Xinjiang Uygur Autonomous Region Key laboratory "Xinjiang Laboratory of Lake Environment and Resources in Arid Zone", Urumqi 830054, China
  • Received:2015-06-08 Published:2016-03-26
  • Supported by:

    Supported by the National Natural Science Foundation of China (41261051) and the Open Funds of Key Laboratory of Xinjiang Uygur Autonomous Region (XJDX0909-2010-08)

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Abstract:

MISR multi-angular data have been built through 9 cameras combination, and the infulence on land use and land cover mapping by multi-angular observing and traditional nadir approach has been explored in the lower Tarim River. In addition, SVM (support vector machine) and conventional MLC (maximum likelihood classification) were respectively implemented to observe the differentiation of Confusion Matrix. The findings are presented as follows:Multi-angular oberservation achieved higher classification accuracy compared to nadir approach no matter MLC or SVM classifiers being used; Although the lower resolution, MISR obtains abundent information, and thus has a great impact on the classification of vegetation;the classification by SVM shows a higher accuracy than that by MLC no matter which data set is used;different cameras lead to different results, but camera C and D paly more important roles than the others.

Key words: MISR, support vector machine, maximum lickelihood classification, lower Tarim River, land use and land cover

CLC Number: 

  • P627

[1] Richardson A J, Wiegand C L. Distinguishing Vegetation from Soil Background Information[J]. Photogram Engi & Remote Sensing, 1977, 43(12):1541-1552.

[2] 阿布都沙拉木·加拉力丁.塔里木河流域胡杨保护区土地覆盖变化研究[J].干旱区资源与环境, 2010, 24(1):154-157. Abdisalam Jalaldin. Study on Land Cover Change of Tarim Poplar Nature Reservation[J]. Journal of Arid Land Resources and Environment, 2010, 24(1):154-157.

[3] Buhe A, Tsuchiya K, Kaneko M, et al. Land Cover of Oases and Forest in Xinjiang, China Retrieved from ASTER Data[J]. Advances in Space Research, 2007, 39(1):39-45.

[4] 黄粤,包安明.间歇性输水影响下的2001-2011年塔里木河下游生态环境变化[J].地理学报, 2013, 9(68):1251-1262. Huang Yue, Bao Anming. Eco-Environmental Change in the Lower Tarim River Under the Influence of Intermittent Water Transport[J]. Acta Geographica Sinica, 2013, 9(68):1251-1262.

[5] 张旭,刘新春.EOS MODIS影像处理在塔里木河下游植被监测中的应用[J].干旱区研究, 2005,22(4):532-536. Zhang Xu, Liu Xinchun. Study on the EOS/MODIS Image Processing and Its Application in Monitoring the Vegetation Change in the Lower Reaches of the Tarim River[J]. Arid Zone Research, 2005, 22(4):532-536.

[6] Diner D J, Beckert J C, Reilly T H. Multi-Angle Imaging Spectroradiometer (MISR) Instrument Description and Experiment Overview[J].IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(4):1072-1087.

[7] Chopping M J, Rango A, Ritchie J C. Improved Semi-Arid Community Type Differentiation with the NOAA AVHRR via Exploitation of the Directional Signal[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(5):1132-1149.

[8] Su L, Chopping M J. Differentiation of Semi-Arid Vegetation Types Based on Multi-Angular Observations from MISR and MODIS[J]. International Journal of Remote Sensing, 2007,6(28):1419-1424.

[9] Jiao Z, Hill M J, Schaaf C B, et al. An Anisotropic Flat Index (AFX) to Derive BRDF Archetypes from MODIS[J]. Remote Sensing of Environment, 2014, 141(4):168-187.

[10] 刘晏良.塔里木河中下游实地踏勘报告[M].北京:中国统计出版社,2000. Liu Yanliang. The Report of Field Survey of Talimu River[M]. Beijing:The Statistics Publishing House of China, 2000.

[11] 张绘芳,李霞.塔里木河下游胡杨种群空间分布格局分析[J].西北植物学报,2006,26(10):2125-2130. Zhang Huifang, Li Xia. Spatial Distribution Pattern of Populuseuphratica Populations in the Lower Reaches of Tarim River[J]. Acta Botanica Boreali-Occidentalia Sinica, 2006,26(10):2125-2130.

[12] Diner D J, Martonchik J V, Borel, et al. Multi-Angle Imaging Spectro-Radiometer Level 2 Surface Retrieval Algorithm Theoretical Basis Document[EB/OL].[2014-12-02]. http://eospso.gsfc.nasa.gov/eos_homepage/for_scientists/atbd/docs/MISR/atbd-misr-10.pdf.

[13] MISR Homepage[EB/OL].[2015-05-15]. http://www.misr.jpl.nasa.gov/.

[14] MISR Data Products Specifications[EB/OL].[2015-05-15]. http://eosweb.larc.nasa.gov/.

[15] Rahman H, Dedieu G. SMAC:A Simplified Method for the Atmospheric Correction of Satellite Measurements in the Solar Spectrum[J]. International Journal of Remote Sensing, 1994,15(1):123-143.

[16] 武红敢,涂琼.WorldView2影像的单株木监测潜力分析:以杭州西山地区为例[J].林业资源管理,2012(6):92-96. Wu Honggan, Tu Qiong. Analysis on Monitoring Potential of Individual Trees Based on WorldView2 Image:A Case Study of West Mountain Areas in Hangzhou City[J]. Forest Resources Management, 2012(6):92-96.

[17] 孙家抦.遥感原理与应用[M].武汉:武汉大学出版社,2003. Sun Jiabing. Principles and Applications of Remote Sensing[M]. Wuhan:Wuhan University Press, 2003.

[18] Exelis. ENVI Homepage[EB/OL].[2014-12-01] http://www.exelisvis.com/.

[19] Vapnik V. The Nature of Statistical Learning Theory[M]. NewYork:Springer-Verlag,1995.

[20] Giorgos Mountrakis, Jungho Im. Support Vector Ma-chines in Remote Sensing:A Review[J]. Journal of Photogrammetry and Remote Sensing, 2011, 66:247-259.

[21] Chang C C, Lin C J. LIBSVM:A Library for Support Vector Machines[EB/OL].[2014-05-01]. http://www.csie.ntu.edu.tw/~cjlin/libsvm.
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