中文摘要：

数码相片属于地面遥感资料的一种,被广泛应用于实地调查中。然而,目前利用数码相片对植被生物量进行推算的研究很少。利用数码相片提取小麦生长期的小麦覆盖度,结合地面实测叶面积指数（LAI）、归一化植被指数（NDVI）和小麦生物量,分析小麦覆盖度与LAI、NDVI,生物量与小麦覆盖度、LAI、NDVI各自的相关系数,建立各自合适的回归模型推算冬小麦的生物量。结果表明,在小麦生长期,小麦覆盖度与LAI、NDVI的相关系数R2分别达到0.765、0.896,生物量与小麦覆盖度、LAI、NDVI的相关系数R2分别为0.774、0.876、0.712,生物量与其小麦覆盖度、LAI、NDVI之间具有很高的相关性,多元回归分析效果更好,系数R2达0.891。结果说明,在不破坏植被生长状态的情况下,基于数码相片可有效地推算小麦的生物量,这为大面积实地测量和遥感监测作物长势及其生物量估算提供了理论参考依据。

英文摘要：

The digital photograph was one of the ground remote sensing data,and was widely used in field survey.However,research on vegetation biomass estimation using digital photographs was rare.In this study,wheat coverage（WC）was firstly extracted at wheat turning green stage using digital photos,leaf area index（LAI）,normalized difference vegetation index（NDVI）,and wheat biomass（WB） were measured respectively in fields.Then the correlation coefficient between wheat vegetation coverage and LAI,NDVI were analyzed respectively,the same method also applied to biomass and wheat vegetation coverage,LAI,NDVI.The results showed that the correlation coefficient between wheat coverage and LAI,NDVI was high and correlation coefficients were 0.765,0.896,respectively.The correlation coefficients between biomass and wheat coverage,LAI,NDVI were also high and its correlation coefficients were 0.774,0.876 and 0.712 respectively.Multiple regression analysis had better correlativity,its coefficient reached 0.891.Therefore,it was proved that wheat biomass could be estimated effectively using digital photos without destructing vegetation growth situation.