DOI: 10.1016/j.jag.2017.04.008
Scopus记录号: 2-s2.0-85030869407
论文题名: Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data
作者: Kandare K ; , Ørka H ; O ; , Dalponte M ; , Næsset E ; , Gobakken T
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2017
卷: 60 起始页码: 72
结束页码: 82
语种: 英语
英文关键词: ALS
; Biophysical attribute prediction
; Forestry
; Fusion
; Hyperspectral data
; Individual tree crowns
; Remote sensing
; Site index
Scopus关键词: accuracy assessment
; airborne sensing
; boreal forest
; canopy architecture
; laser method
; mapping
; prediction
; site index
; spectral analysis
; Norway
; Picea abies
; Pinus sylvestris
英文摘要: Site productivity is essential information for sustainable forest management and site index (SI) is the most common quantitative measure of it. The SI is usually determined for individual tree species based on tree height and the age of the 100 largest trees per hectare according to stem diameter. The present study aimed to demonstrate and validate a methodology for the determination of SI using remotely sensed data, in particular fused airborne laser scanning (ALS) and airborne hyperspectral data in a forest site in Norway. The applied approach was based on individual tree crown (ITC) delineation: tree species, tree height, diameter at breast height (DBH), and age were modelled and predicted at ITC level using 10-fold cross validation. Four dominant ITCs per 400 m2 plot were selected as input to predict SI at plot level for Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.). We applied an experimental setup with different subsets of dominant ITCs with different combinations of attributes (predicted or field-derived) for SI predictions. The results revealed that the selection of the dominant ITCs based on the largest DBH independent of tree species, predicted the SI with similar accuracy as ITCs matched with field-derived dominant trees (RMSE: 27.6% vs 23.3%). The SI accuracies were at the same level when dominant species were determined from the remotely sensed or field data (RMSE: 27.6% vs 27.8%). However, when the predicted tree age was used the SI accuracy decreased compared to field-derived age (RMSE: 27.6% vs 7.6%). In general, SI was overpredicted for both tree species in the mature forest, while there was an underprediction in the young forest. In conclusion, the proposed approach for SI determination based on ITC delineation and a combination of ALS and hyperspectral data is an efficient and stable procedure, which has the potential to predict SI in forest areas at various spatial scales and additionally to improve existing SI maps in Norway. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79962
Appears in Collections: 气候变化事实与影响
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作者单位: FoxLab, Joint CNR-FEM Initiative, Fondazione E. Mach, Via E. Mach 1, San Michele all'Adige, TN, Italy; Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, Norway; Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, Fondazione E. Mach, Via E. Mach 1, San Michele all'Adige, TN, Italy
Recommended Citation:
Kandare K,, Ørka H,O,et al. Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data[J]. International Journal of Applied Earth Observation and Geoinformation,2017-01-01,60