Skip to Main Content
Due to a lapse in federal funding, this USDA website will not be actively updated. Once funding has been reestablished, online operations will continue.
Modeling variability and scale integration of LAI measurementsAuthor(s): Kris Nackaerts; Pol Coppin
Source: In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 392-398.
Publication Series: General Technical Report (GTR)
Station: North Central Research Station
PDF: View PDF (413.51 KB)
DescriptionRapid and reliable estimation of leaf area at various scales is important for research on chance detection of leaf area index (LAI) as an indicator of ecosystem condition. It is of utmost importance to know to what extent boundary and illumination conditions, data aggregation method, and sampling scheme influence the relative accuracy of stand-level LAI measurements. This knowledge should lead to a high repeatability and relative accuracy of the LAI measurements. In this research, LI-COR is recorded with a Licor LAI-2000, one of the more modem and widely used plant canopy analyzer instruments. The impact of external factors (boundary and illumination conditions) is minimized by means of a viewcap. The impact of sampling scheme and data aggregation method on the relative accuracy of the retrieved stand-level LAI value is quantified by means of Monte Carlo simulation.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, email@example.com if you notice any errors which make this publication unusable.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationNackaerts, Kris; Coppin, Pol. 2000. Modeling variability and scale integration of LAI measurements. In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 392-398.
- Mapping urban forest structure and function using hyperspectral imagery and lidar data
- Comparing methods for measuring the rate of spread of invading populations
- Comparison of regression and geostatistical methods for mapping Leaf Area Index (LAI) with Landsat ETM+ data over a boreal forest.
XML: View XML