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• W2802177710 endingPage "694" @default.
• W2802177710 startingPage "694" @default.
• W2802177710 abstract "Solar radiation, the radiant energy from the sun, is a driving variable for numerous ecological, physiological, and other life-sustaining processes in the environment. Traditional methods to quantify solar radiation are done either directly (e.g., quantum sensors), or indirectly (e.g., hemispherical photography). This study, however, evaluates literature which utilized remote sensing (RS) technologies to estimate various forms of solar radiation or components, thereof under or within forest canopies. Based on the review, light detection and ranging (LiDAR) has, so far, been preferably used for modeling light under tree canopies. Laser system’s capability of generating 3D canopy structure at high spatial resolution makes it a reasonable choice as a source of spatial information about light condition in various parts of forest ecosystem. The majority of those using airborne laser system (ALS) commonly adopted the volumetric-pixel (voxel) method or the laser penetration index (LPI) for modeling the radiation, while terrestrial laser system (TLS) is preferred for canopy reconstruction and simulation. Furthermore, most of the studies focused only on global radiation, and very few on the diffuse fraction. It was also found out that most of these analyses were performed in the temperate zone, with a smaller number of studies made in tropical areas. Nonetheless, with the continuous advancement of technology and the RS datasets becoming more accessible and less expensive, these shortcomings and other difficulties of estimating the spatial variation of light in the forest are expected to diminish." @default.
• W2802177710 created "2018-05-17" @default.
• W2802177710 creator A5001705778 @default.
• W2802177710 creator A5026728788 @default.
• W2802177710 creator A5034504969 @default.
• W2802177710 date "2018-05-01" @default.
• W2802177710 modified "2023-10-13" @default.
• W2802177710 title "Modeling Solar Radiation in the Forest Using Remote Sensing Data: A Review of Approaches and Opportunities" @default.
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• W2802177710 doi "https://doi.org/10.3390/rs10050694" @default.
• W2802177710 hasPublicationYear "2018" @default.
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