Abstract
An accurate estimation of the leaf area index (LAI) by satellite remote sensing is essential for studying the spatial variation of ecosystem structure. The goal of this study was to estimate the spatial variation of LAI over a forested catchment in a mountainous landscape (ca. 60 km2) in central Japan. We used a simple model to estimate LAI using spectral reflectance by adapting the Monsi-Saeki light attenuation theory for satellite remote sensing. First, we applied the model to Landsat Operational Land Imager (OLI) imagery to estimate the spatial variation of LAI in spring and summer. Second, we validated the model’s performance with in situ LAI estimates at four study plots that included deciduous broadleaf, deciduous coniferous, and evergreen coniferous forest types. Pre-processing of the Landsat OLI imagery, including atmospheric correction by elevation-dependent dark object subtraction and Minnaert topographic correction, together with application of the simple model, enabled a satisfactory 30-m spatial resolution estimation of forest LAI with a maximum of 5.5 ± 0.2 for deciduous broadleaf and 5.3 ± 0.2―for evergreen coniferous forest areas. The LAI variation in May (spring) suggested an altitudinal gradient in the degree of leaf expansion, whereas the LAI variation in August (mid-summer) suggested an altitudinal gradient of yearly maximum forest foliage density. This study demonstrated the importance of an accurate estimation of fine-resolution spatial LAI variations for ecological studies in mountainous landscapes, which are characterized by complex terrain and high vegetative heterogeneity.
Highlights
Forest ecosystems play an important role in the regulation of the global climate
Application of elevation-dependent dark object subtraction (DOS) on the Landsat Operational Land Imager (OLI) imagery efficiently reduced the effects of overall atmospheric scattering and variation of optical depth along an altitudinal gradient (Figure 4)
The dependence of leaf area index (LAI) on temperature has been evidenced in numerous ecological studies with respect to spatial variations [1,7,23,40,67] and leaf seasonality [2,38]
Summary
Forest ecosystems play an important role in the regulation of the global climate. They are a key component of the carbon cycle because of their large carbon sequestration, heat budget, and hydrological cycle [1]. Because leaves are the main surface through which energy and mass are exchanged between terrestrial vegetation and the atmosphere, the leaf area index (LAI) is an essential variable used to integrate ecosystem functions such as photosynthesis, transpiration, and autotrophic respiration from the scale of an individual leaf to total tree and canopy scales [4,5,6,7]. LAI was first defined by Watson [8] as the total one-sided area of leaf tissue per unit ground surface area. This definition is applicable to flat leaves, both sides of which have the same area. For leaves with other geometries such as needles, Myneni et al [10] used the term LAI to mean the maximum projected leaf area per unit ground surface area. We use the definition of LAI by Myneni et al [10]
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