Estimating forest leaf area index using satellite images : comparison of k-NN based Landsat-NFI LAI with MODIS-RSR based LAI product for Finland

• Main Authors: Härkönen, Sanna, Lehtonen, Aleksi, Manninen, Terhikki, Tuominen, Sakari, Peltoniemi, Mikko
• Other Authors: Department of Forest Sciences
• Format: Article in Journal/Newspaper
• Language: English
• Published: Finnish Environment Institute 2016
• Subjects: CLOUD-COVER ASSESSMENT; SCOTS PINE; LIGHT INTERCEPTION; SHOOT STRUCTURE; BOREAL FORESTS; REFLECTANCE MODEL; BIOMASS EQUATIONS; NORWAY SPRUCE; ABSORBED PAR; SILVER BIRCH; 4112 Forestry; Norway; Boreal Environment Research; Northern Finland
• Online Access: http://hdl.handle.net/10138/165218

Leaf area index (LAI) is a key variable for many ecological models, but it is typically not available from basic forest inventories. In this study, we (1) construct a high-resolution LAI map using k nearest-neighbor (k-NN) imputation based on National Forest Inventory data and Landsat 5 TM images (Landsat-NFI LAI), and (2) examine a moderate-resolution LAI map produced based on reduced simple ratio derived from MODIS reflectances (MODIS-RSR LM). The maps cover all the forested areas in Finland. Country-level averages of Landsat-NFI and MODIS-RSR LAI were at same level, but several geographical and land-use related differences between them were detected. Difference was the largest in the lake district of Finland and in northern Finland, and it increased with decreasing share of forests and increasing share of deciduous trees. As MODIS-RSR LAI does not take into account the sub-pixel variation in land use, Landsat-NFI LAI was found to produce more reliable estimates. Peer reviewed