首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Evaluation of simulated bands in airborne optical sensors for tree species identification
【24h】

Evaluation of simulated bands in airborne optical sensors for tree species identification

机译:评估机载光学传感器中的模拟波段以识别树木

获取原文
获取原文并翻译 | 示例
           

摘要

Airborne multispectral remote sensing devices have been used in automatic identification of tree species, and the spatial and spectral properties of the sensors affect the remote sensing measurement results. Previous work based on a simulation model with ground-level measured reflectance data of pine (Pinus sylvestris L.), spruce (Picea abies (L.) H. Karst.), and birch (Betula pubescens Ehrh. and Betula pendula Roth) tree species and idealized Leica ADS80 sensitivities suggested that the addition of a fifth sensitivity band in the red edge wavelength region to the existing Leica ADS80 system significantly improves the classification performance. In this paper, we extend this analysis using a simulated model with accurate spectral sensitivity information and airborne AisaEAGLE II hyperspectral data for these three tree species. We simulated multispectral responses using spectral sensitivity characteristics of the Leica ADS40, the Vexcel UltraCam-D, the Intergraph-Z/I Digital mapping camera and the Leica ADS40 system with an added band in the 691-785. nm region. We evaluated the tree species classification performance of these simulated responses using Discriminant Analysis and Support Vector Machine classifiers. The classification experiment result showed that the simulated responses of the 5-band multispectral system yielded the most robust classification performance with approximately 98% accuracy. This result was similar to the accuracy obtained with the hyperspectral data. Although differences were observed in the sensitivity functions of the 4-band systems, there were no large differences observed in the classification performances between them. With the simulated 5-band system, there was an increase of 5-13% points in classification accuracy when compared to the accuracies of the 4-band systems. The results obtained via proposed 5-band system support results from previous studies suggesting that there is a need for a sensitivity band in the red edge wavelength region for applications in tree species classification.
机译:机载多光谱遥感设备已用于树木种类的自动识别,并且传感器的空间和光谱特性会影响遥感测量结果。基于模拟模型的先前工作,该模型具有松树(Pinus sylvestris L.),云杉(Picea abies(L.)H. Karst。)和桦木(Betula pubescens Ehrh。和Betula pendula Roth)的地面测量反射率数据种类和理想的Leica ADS80感光度表明,在现有Leica ADS80系统的红色边缘波长区域中添加第五个感光带可显着提高分类性能。在本文中,我们使用具有准确光谱敏感度信息和机载AisaEAGLE II高光谱数据的这三个树种的模拟模型扩展了此分析。我们使用Leica ADS40,Vexcel UltraCam-D,Intergraph-Z / I数字制图相机和Leica ADS40系统的光谱灵敏度特性(在691-785中增加了波段)来模拟多光谱响应。纳米区域。我们使用判别分析和支持向量机分类器评估了这些模拟响应的树种分类性能。分类实验结果表明,在5波段多光谱系统的仿真响应中,最可靠的分类性能达到了98%左右。该结果类似于利用高光谱数据获得的准确性。尽管在4波段系统的灵敏度函数中观察到了差异,但是在它们之间的分类性能上并没有观察到很大的差异。与4频段系统的精度相比,使用模拟的5频段系统,分类精度提高了5-13%。通过提议的5波段系统获得的结果支持以前的研究结果,表明在红树边缘波长区域中需要一个敏感性波段以用于树种分类。

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