首页> 外文会议>Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International >Chlorophyll content estimation of Boreal conifers using hyperspectral remote sensing
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Chlorophyll content estimation of Boreal conifers using hyperspectral remote sensing

机译:利用高光谱遥感估算北方针叶树种叶绿素含量

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This investigation quantitatively links physiologically based estimators of forest stand condition, such as chlorophyll concentration, to hyperspectral observations of Jack Pine (Pinus Banksiana), a dominant Boreal Forest species. Between June and September of 2001, four Intensive Field Campaigns (IFC) of data collection were conducted over the forested areas near Sudbury, Ontario, Canada. Using the CASI sensor, data were collected, in the visible and near infrared domain, over eight selected Jack Pine sites. Supplementing the airborne campaigns was simultaneous on-site collection of foliage samples for laboratory spectral and chemical measurements. The study first linked needle-level reflectance and pigment content through the inversions of leaf level radiative transfer models such as PROSPECT. Next, the red-edge index (R750/710), was scaled up to the canopy level through the use of canopy models and infinite reflectance calculations, which simulate the canopy as an optically thick vegetation medium. However, for the relatively open and clumped jack pine stands such a simple approach requires careful validation due to the confounding effects of the open canopy structure. Accordingly, the analysis has focused on high spatial resolution CASI imagery (1 meter) for which tree crowns, shadows, and open (sun-lit) understory can be identified visually and approaches can be examined for validity and effects. Effectively eliminating these confounding variables will permit the generation of predictive needle pigment content maps for forest condition assessment.
机译:这项研究定量地将基于森林生理状况的生理估计值(例如叶绿素浓度)与占主导地位的北方森林树种Jack Pine(Pinus Banksiana)的高光谱观测结果联系起来。在2001年6月至9月之间,在加拿大安大略省萨德伯里附近的森林地区进行了四次密集的数据收集运动。使用CASI传感器,在8个选定的Jack Pine站点的可见光和近红外域中收集了数据。对空降战役的补充是在现场同时采集树叶样本以进行实验室光谱和化学测量。该研究首先通过叶面辐射传递模型(例如PROSPECT)的反演将针级反射率和色素含量联系起来。接下来,通过使用冠层模型和无限反射率计算(将冠层模拟为光学上较厚的植被介质),将红边指数(R750 / 710)放大到冠层水平。但是,对于相对开放且结块的松木架,由于开放式顶篷结构的混杂效应,这种简单的方法需要仔细验证。因此,分析集中在高空间分辨率CASI图像(1米)上,对于这些图像,可以从视觉上识别树冠,阴影和敞开的(阳光直射的)林下树木,并且可以检查方法的有效性和效果。有效消除这些混杂变量将允许生成预测针叶色素含量图,以进行森林状况评估。

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