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山丹县草地地上生物量遥感估算模型
引用本文: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.
作者姓名:杜自强  王建  沈宇丹
作者单位:(1. 中国科学院寒区旱区环境与工程研究所, 甘肃兰州 730000; 2. 甘肃农业大学资源与环境学院, 甘肃兰州 730070; 3. 华中农业大学经济管理学院, 武汉 430070)
基金项目:中国科学院“西部之光”人才培养计划(2002407)
摘    要:选择黑河流域草地植被的典型区域-山丹县作为研究区, 利用2003 年8 月野外实测50 个样方的草地地上生物量数据和同期的陆地卫星TM 影像数据, 分析了植被指数与草地地上生物量的相关关系, 进而建立基于遥感植被指数DV I 的草地地上生物量估算模型。结果表明: 在草地地上生物量和TM 影像植被指数之间关系微弱、直接利用TM 影像数据建立估算模型不可行的情况下,用地面实测的草地植被反射光谱数据对遥感影像数据进行校正, 能够弥补传统的“点-面”建模方法的不足, 获得比较理想的估算模型; 植被指数DVI 与草地地上生物量之间存在较好的相关性, 其估算模型为Y = 2477X - 77. 598 (R 2= 0. 7589) , 经实测数据验证, 总体精度达到80% 以上, 基本上能够满足中尺度的草地地上生物量估算。

关 键 词:遥感    植被指数    草地地上生物量  估算模型  
文章编号:1004-0323(2006)04-0338-06
收稿时间:2006-02-15
修稿时间:2006-06-19

EstimatingModel of Grassland Above-ground Biomass Based on Remote Sensed Data in Shandan County
DU Zi-qiang,WANG Jian,SHEN Yu-dan.EstimatingModel of Grassland Above-ground Biomass Based on Remote Sensed Data in Shandan County[J].Remote Sensing Technology and Application,2006,21(4):338-343.
Authors:DU Zi-qiang  WANG Jian  SHEN Yu-dan
Affiliation:(1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Science, Lanzhou 730000, China; 2. College of Resources and Environmental Sciences, Gansu Agricultural University , Lanzhou 730070, China; 3. College of Economy and Management,Huazhong Agricultural University , Wuhan 430070, China)
Abstract:Shandan County is taken as study area which is the typical region of the grassland vegetation in the middle and upper reaches of Heihe River basin and the key region of ecological and environmental construction.First,correlation between vegetation indices and grassland above-ground biomass is analysed based on in situ sampling data acquired in August,2003 and remote sensed image data in the same periods.Then,estimating model of grassland above-ground biomass based on remote sensed data in Shandan County is established.Results show remote sensed data corrected by field sampling data can achieve a close correlation with grassland above-ground biomass.Grassland above-ground estimating biomass model can be expressed by the equation: Y=2477X-77.598(R~2=0.7589).Verified by in situ sampling data,the model has a better estimating result.
Keywords:Estimating model  Grassland above-ground biomass  Remote sensed data
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