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REMOTE SENSING FOR LAND & RESOURCES    2011, Vol. 23 Issue (4) : 42-45     DOI: 10.6046/gtzyyg.2011.04.08
Technology and Methodology |
The Construction of the Remote Sensing Estimation Models for Reed Biomass in the Lower Reaches of the Tarim River
NIU Ting1,2, LI Xia1, LIN Hai-jun1, ZHAO Zhao1, DONG Dao-rui1
1. College of Grass and Environment, Xinjiang Agricutural University, Urumqi 830052, China;
2. Survey and Design Institute of Water Conservancy and Hydroelectric Power of Xinjiang, Urumqi 830000, China
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Abstract  

The remote sensing estimation models for reed biomass were established by using TM data and the field investigation of reed biomass around the Daxihaizi reservoir in the lower reaches of Tarim river. The results show that the gray values of TM1~5 and TM7,the perpendicular vegetation index(PVI),the brightness vegetation index(BVI) and the normalized difference vegetation index(NDVI)are significantly related to the measured values of Phragmites australis biomass, the fitting precision of the nonlinear regression model is higher than that of the linear regression model,and NDVI has the highest precision in the regression models but TM4 has the lowest precision. The multiple stepwise regression has a higher fitting precision than ordinary regressions. The ordinary linear regressions based on PVI and NDVI and the ordinary nonlinear regression based on TM1 are the best options due to the characteristics of simplicity,reliability and convenience.

Keywords Ecosystem      Soil conservation capacities      Value of soil conservation      Northern Hebei     
:  TP 751.1  
  X 171.4  
Issue Date: 16 December 2011
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XU Xu
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HAN Nian-long
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XU Xu,LI Xiao-bing,HAN Nian-long. The Construction of the Remote Sensing Estimation Models for Reed Biomass in the Lower Reaches of the Tarim River[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(4): 42-45.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2011.04.08     OR     https://www.gtzyyg.com/EN/Y2011/V23/I4/42



[1] 李霞,侯平,董新光,等.新疆塔里木河下游应急输水植被恢复阶段分析[J].生态学杂志,2005,24(12):1449-1453.





[2] 张宏锋,陈亚宁,陈亚鹏,等.塔里木河下游植物群落的物种数量变化与生态系统动态研究[J]生态学杂志,2004,23(4):21-24.





[3] 杜自强,王建,沈宇丹.山丹县草地地上生物量遥感估算模型[J].遥感技术与应用,2006,21(4):338-343.





[4] 李聪,肖继东,曹占洲,等.应用MODIS数据估算草地生物量[J].干旱区研究,2007,24(3):386-391.





[5] 王正兴,刘闯,赵冰茹,等.利用MODIS增强型植被指数反演草地地上生物量[J].兰州大学学报:自然科学版,2005,41(2):10-16.





[6] 徐多,姬秋梅,德吉央宗,等.利用EOS/MODIS数据估算西藏藏北高原地表草地生物量[J].气象学报,2007,65(4):612-621.





[7] 邓铭江.塔里木河下游生态输水及植被恢复遥感监测评价[J].冰川冻土,2007,29(3):380-386.





[8] 李霞,侯平,杨鹏年.塔里木河下游胡杨对水分条件变化的响应[J].干旱区研究,2006,23(1):26-31.





[9] 牛婷,李霞.塔里木河下游植被恢复遥感模型建立[J].国土资源遥感,2008(2):79-83.





[10] 李霞,侯平,董新光.塔里木河下游断流区胡杨密度调查与分析[J].新疆农业大学学报,2003,26(4):41-44.

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