气候变化领域集成服务门户(CCPortal): Predicting and mapping site index in operational forest inventories using bitemporal airborne laser scanner data

CCPortal

DOI	10.1016/j.foreco.2019.117768
	Predicting and mapping site index in operational forest inventories using bitemporal airborne laser scanner data
	Noordermeer L.; Gobakken T.; Næsset E.; Bollandsås O.M.
发表日期	2020
ISSN	0378-1127
卷号	457
英文摘要	Forest productivity reflects the wood production capacity of a given site and provides crucial information for forest management planning. The most widely accepted measure of forest productivity is site index (SI), defined as the average height of dominant trees at a given index age. In forest management inventories, SI is commonly interpreted manually from aerial images. While the use of airborne laser scanner (ALS) data has revolutionized operational practices for estimating many forest attributes relevant to forest management planning, practices for determining SI remain unchanged. The main objective of this study was to demonstrate a practical method for predicting and mapping SI in repeated ALS-based forest inventories. We used data acquired as part of three operational large-scale forest inventories in southeastern Norway. First, we identified areas in which forest growth had remained undisturbed since the initial inventory. We then regressed field predictions of SI against bitemporal ALS canopy metrics and used the regression models to predict SI for forest areas classified as undisturbed. The result was SI maps constructed with a spatial resolution of 15.81 m. User accuracies of class predictions of undisturbed forest in the three districts were 92%, 95% and 89%. Plot-level validation revealed root mean squared errors of SI predictions ranging from 1.72 to 2.84 m for Norway spruce, and 1.35 to 1.73 m for Scots pine. The method presented here can be used to map SI over large areas of forest automatically, depicting forest productivity at a much finer spatial resolution than what is common in operational inventories. © 2019 The Authors
关键词	Antennas Forecasting Image resolution Laser applications Mapping Mean square error Productivity Regression analysis Scanning Airborne laser scanners Forest management planning Forest productivity Mapping site index Operational forest inventories Operational practices Root mean squared errors Undisturbed forests Forestry airborne sensor classification forest inventory forest management growth response prediction scanner site index spatial resolution woody plant Forecasts Forestry Mapping Productivity Regression Analysis Scanning Norway Picea abies Pinus sylvestris
语种	英语
来源机构	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/133113
推荐引用方式 GB/T 7714	Noordermeer L.,Gobakken T.,Næsset E.,et al. Predicting and mapping site index in operational forest inventories using bitemporal airborne laser scanner data[J]. Forest Ecology and Management,2020,457.
APA	Noordermeer L.,Gobakken T.,Næsset E.,&Bollandsås O.M..(2020).Predicting and mapping site index in operational forest inventories using bitemporal airborne laser scanner data.,457.
MLA	Noordermeer L.,et al."Predicting and mapping site index in operational forest inventories using bitemporal airborne laser scanner data".457(2020).