FUSING IMAGING SPECTROMETRY AND AIRBORNE LASER SCANNING DATA FOR TREE SPECIES DISCRIMINATION

被引：6

作者：

Torabzadeh, H. ^{[1
]}

Morsdorf, F. ^{[1
]}

Leiterer, R. ^{[1
]}

Schaepman, M. E. ^{[1
]}

机构：

[1] Univ Zurich, Dept Geog, Remote Sensing Labs, CH-8057 Zurich, Switzerland

来源：

2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年

关键词：

data fusion; airborne laser scanning; imaging spectrometry; tree species; support vector machines; LIDAR DATA; CLASSIFICATION;

D O I：

10.1109/IGARSS.2014.6946660

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Accurate mapping of tree species composition within forest ecosystems is an important aspect of management planning and monitoring. Passive optical remote sensing in general and imaging spectroscopy (IS) in particular have played an important role in producing such maps, but are suffering from issues due to vegetation structure. On the other hand, the structural information provided by airborne laser scanning (ALS) was shown to be helpful for species discrimination, particularly in heterogeneous forests. In this paper, we investigate the potential of product-level fusion of IS and ALS to provide a better tree species differentiation based on their complementarity. Our results show that the fused tree species map does improve on the single system maps and more accurately provides the distribution and fraction of each tree species within the study area.

引用

页码：1253 / 1256

页数：4

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