用传统研究植被生物量实测的方法不仅耗时费力, 而且由于影响因子不易确定会导致预估精度不高。 选择永定河流域河北——北京段为研究区域, 以该地区2009年7月20日的TM影像数据为数据源, 结合当地分辨率为30米的数字高程模型(digital elevation model, DEM)数据和其他相关辅助解译资料, 并借助全站仪等高精度测量仪器进行外业调查, 归纳出永定河地区遥感因子与植被生物量可能存在的函数关系, 通过多元线性回归分析遥感影像因子并建立反演模型, 最后将反演模型进行精度分析。 通过将实测值和预测值分析对比, 得出反演模型总体相对误差为-0.025%, 平均相对误差为-0.016%, 总体预估精度高达84.56%。 模型的建立可对大范围流域生态环境因子进行及时、 快速、 准确地调查, 为永定河生态环境问题诊断提供实验数据。

Researching on vegetation biomass using the traditional measurement method is time-consuming and hard sledding, and prediction precision of biomass is always not good because of uncertain influencing factors. The present article aims at the current situation of Hebei-Beijing reach along Yongding River, using the Thematic Mapper data in this place on 20th July 2009 as source data, with the 30 meters Digital Elevation Model data in Beijing and other auxiliary information, meanwhile through field observation data, to find out the possible functional relationship along vegetation biomass and remote sensing image factor. The authros sorted out the vegetation biomass and remote sensing image factor on the sample plot, then set up an inverse model through multiple linear regression analysis, and analyzed the precision of inverse model. After calculating the measured value and predicted value, the authors got the global relative error is -0.025%, the average relative error is -0.016%, and the general predictive precision is 84.56%. The establishment of this model is able to investigate eco-environmental factors on large range timely, quickly and accurately, also can provide the experimental base for the eco-environmental survey on river basin, and make the foundation for the problem diagnosis of ecological environment and the research on ecosystem degradation mechanism of Yongding River.