首页> 外文会议>International Symposium on Remote Sensing of Environment >PROSPECT INVERSION FOR INDIRECT ESTIMATION OF LEAF DRY MATTER CONTENT AND SPECIFIC LEAF AREA
【24h】

PROSPECT INVERSION FOR INDIRECT ESTIMATION OF LEAF DRY MATTER CONTENT AND SPECIFIC LEAF AREA

机译:预期反演间接估算叶干物质含量和特定叶面积

获取原文

摘要

Quantification of vegetation properties plays an indispensable role in assessments of ecosystem function with leaf dry mater content (LDMC) and specific leaf area (SLA) being two important vegetation properties. Methods for fast, reliable and accurate measurement of LDMC and SLA are still lacking. In this study, the inversion of the PROSPECT radiative transfer model was used to estimate these two leaf parameters. Inversion of PROSPECT traditionally aims at quantifying its direct input parameters rather than identifying the parameters which can be derived indirectly from the input parameters. The technique has been tested here to indirectly model these parameters for the first time. Biophysical parameters such as leaf area, as well as fresh and dry weights of 137 leaf samples were measured during a field campaign in July 2013 in the mixed mountain forests of the Bavarian Forest National Park, Germany. Reflectance and transmittance of the leaf samples were measured using an ASD field spec III equipped with an integrating sphere. The PROSPECT model was inverted using a look-up table (LUT) approach for the NIR/SWIR region of the spectrum. The retrieved parameters were evaluated using their calculated R2 and normalized root mean square error (nRMSE) values with the field measurements. Among the retrieved variables the lowest nRMSE (0.0899) was observed for LDMC. For both traits higher R2 values (0.83 for LDMC and 0.89 for SLA) were discovered. The results indicate that the leaf traits studied can be quantified as accurately as the direct input parameters of PROSPECT. The strong correlation between the estimated traits and the NIR/SWIR region of the electromagnetic spectrum suggests that these leaf traits could be assessed at canopy and in the landscape by using hyperspectral remote sensing data.
机译:植被特性的量化在生态系统功能评估中起着不可或缺的作用,其中叶片干物质含量(LDMC)和比叶面积(SLA)是两个重要的植被特性。仍然缺乏用于快速,可靠和准确地测量LDMC和SLA的方法。在这项研究中,使用PROSPECT辐射传递模型的反演来估算这两个叶片参数。传统上,PROSPECT的反转旨在量化其直接输入参数,而不是识别可以从输入参数间接导出的参数。此处已对该技术进行了测试以首次对这些参数进行间接建模。 2013年7月,在德国巴伐利亚森林国家公园的混交林中,在田间运动期间测量了137个叶样品的生物物理参数,例如叶面积以及鲜重和干重。叶片样品的反射率和透射率是使用配备有积分球的ASD场规范III测量的。使用查找表(LUT)方法对光谱的NIR / SWIR区域反转PROSPECT模型。取回的参数使用其计算的R2和归一化的均方根误差(nRMSE)值以及现场测量值进行评估。在检索到的变量中,对于LDMC观察到最低的nRMSE(0.0899)。对于这两个性状,发现较高的R2值(LDMC为0.83,SLA为0.89)。结果表明,所研究的叶片性状可以像PROSPECT的直接输入参数一样准确地量化。估计的性状与电磁光谱的NIR / SWIR区域之间的强相关性表明,可以使用高光谱遥感数据在冠层和景观中评估这些叶片性状。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号