Optimizing the sampling scheme for LAI-2000 measurements in a boreal forest

Field measurements of leaf area index (LAI) are needed for many ecological and remote sensing applications, but they are laborious and time-consuming. The sampling designs of optical LAI measurements have been mainly driven by the field-of-view of the sensor as well as the upscaling process and spatial resolution of satellite imagery. An optimized sampling design would improve the accuracy of the LAI measurements and reduce the time needed for field work. However, a systematic comparison of sampling designs for LAI measurements in boreal forests has not been done. The aim of this study was to analyze the effect of sampling designs on the accuracy of LAI estimates obtained with the LAI-2000 Plant Canopy Analyzer in a boreal forest. Field data was collected from six study sites in Hyytiälä, central Finland. Two sites were dominated by Pinus sylvestris, two sites by Picea abies, and two sites by Betula pendula. Each site had a regular 9 × 9 -grid of LAI measurement points. All sites were studied using regular and systematic sampling techniques. Statistical analysis was used to examine the site-specific number of measurement points needed in random sampling to achieve a given precision, and as a starting point for regular and systematic sampling. Results indicated that twelve randomly located measurement points are enough to characterize site-specific LAI with standard error less than 0.15 LAI units. If the twelve sampling points are organized systematically, the average standard error is reduced to 0.06 units and the coefficient of variation to less than 0.03.