Robust Forest Cover Indices for Multispectral Images

被引:5
|
作者
Becker, Sarah J. [1 ]
Daughtry, Craig S. T. [2 ]
Russ, Andrew L. [2 ]
机构
[1] US Army Corps Engineers, Engineer Res & Dev Ctr, Geospatial Res Lab, Alexandria, VA 22315 USA
[2] ARS, Hydrol & Remote Sensing Lab, USDA, Beltsville, MD 20705 USA
来源
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING | 2018年 / 84卷 / 08期
关键词
TREE CROWN DETECTION; CLASSIFICATION ACCURACY; DELINEATION; WORLDVIEW-2; VEGETATION; REFLECTANCE; AREA;
D O I
10.14358/PERS.84.8.505
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Trees occur in many land cover classes and provide significant ecosystem services. Remotely sensed multispectral images are often used to create thematic maps of land cover, but accurately identifying trees in mixed land-use scenes is challenging. We developed two forest cover indices and protocols that reliably identified trees in World View-2 multispectral images. The study site in Maryland included coniferous and deciduous trees associated with agricultural fields and pastures, residential and commercial buildings, roads, parking lots, wetlands, and forests. The forest cover indices exploited the product of either the reflectance in red (630 to 690 nm) and red edge (705 to 745 nm) bands or the product of reflectance in red and near infrared (770 to 895 nm) bands. For two classes (trees versus other), overall classification accuracy was >77 percent for the four images that were acquired in each season of the year. Additional research is required to evaluate these indices for other scenes and sensors.
引用
收藏
页码:505 / 512
页数:8
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