DOI: 10.1016/j.jag.2017.03.012
Scopus记录号: 2-s2.0-85018753284
论文题名: Image matching as a data source for forest inventory – Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment
作者: Kukkonen M ; , Maltamo M ; , Packalen P
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2017
卷: 60 起始页码: 11
结束页码: 21
语种: 英语
英文关键词: Airborne laser scanning
; Forest inventory
; Image matching
; LIDAR
; Photogrammetry
Scopus关键词: airborne sensing
; algorithm
; boreal forest
; comparative study
; data processing
; digital terrain model
; forest inventory
; forest management
; image analysis
; laser method
; lidar
; photogrammetry
英文摘要: Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79981
Appears in Collections: 气候变化事实与影响
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作者单位: University of Eastern Finland, School of Forest Sciences, P.O. Box 111, Joensuu, Finland
Recommended Citation:
Kukkonen M,, Maltamo M,, Packalen P. Image matching as a data source for forest inventory – Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment[J]. International Journal of Applied Earth Observation and Geoinformation,2017-01-01,60