岷江上游典型流域叶面积指数的遥感模型及反演

叶面积指数是植被定量遥感的重要参数,区域的时序列叶面积指数揭示了区域生态的演化过程,反演方法上主要是通过植被指数建立相关模型实现的,对于不同地区或不同气候带而言,模型的通用性以及各种植被指数在模型中的灵敏度都需做进一步探讨。以岷江上游典型流域毛儿盖地区为研究区,综合利用Aster和ETM遥感数据、地面实测数据和常规观测数据等资料,研究了植被指数与叶面积指数之间的相关性,以遥感图像中单个像元作为测算单位,对岷江上游毛儿盖地区叶面积指数进行了反演。利用研究区实测数据、生态环境本底遥感调查数据和水文气象数据,对上述模型反演结果进行验证和精度分析。结果表明,归一化植被指数NDVI在反演叶面积指数模型中具有较高的灵敏度,能较真实地反映研究区叶面积指数实际状况。

Remote Sensing Model and Inversion of Leaf Area Index in the Typical Area of Minjiang Valley Upriver

Leaf Area Index(LAI)is the main parameter in quantifying vegetation by means of remote sensing.The temporal variation in LAI is indicative of the evolution process of regional ecology.Vegetation index(VI)has been used widely formodeling vegetation.The applicability of the established models is subject to the local climate in different regions.It is thusnecessary to examine how the derived VI reacts to the change in climate.The paper constructs leaf area indexmodels in the typical area of minjiang valley upr...