Characterizing and estimating forest structure using active remote sensing: An overview
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Abstract
Vegetation plays an important role in supporting our lives by maintaining many environmental and ecological services. Forests, as part of the vegetation cover, are the most critical components of the Earth's carbon cycle. The information about the forest structure is vital for ecosystem health, carbon cycle assessment, and a better understanding of the forest resources. Forest structural parameters estimation by field-based methods has limitations, such as being expensive, impractical, labor-intensive, and time-consuming at a large scale. Remote sensing has proven to be a more competent and low-cost tool for monitoring and measuring forest parameters compared to field surveys. Active remote sensing systems i.e., Light Detection and Ranging (LiDAR) and Radio Detection and Ranging (RADAR) provide horizontal and vertical forest structure information. In addition, these systems are susceptible to the forest components arrangement, given their ability to penetrate the different depths of the canopy. Therefore, there are many types of research focusing on the estimating of the forest aboveground biomass (AGB) which is one of the critical measures of forest resources, using active remote sensing. This research investigates the potential of active remotely sensed data to estimate forest structural parameters and extract data information. Furthermore, this research focused on various methods used for AGB estimation with active remote sensing.
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