A1 Refereed original research article in a scientific journal
Combining Lidar and Synthetic Aperture Radar Data to Estimate Forest Biomass: Status and Prospects
Authors: Kaasalainen, Sanna; Holopainen, Markus; Karjalainen, Mika; Vastaranta, Mikko; Kankare, Ville; Karila, Kirsi; Osmanoglu, Batuhan
Publisher: MDPI
Publishing place: BASEL
Publication year: 2015
Journal: Forests
Journal name in source: FORESTS
Journal acronym: FORESTS
Volume: 6
Issue: 1
First page : 252
Last page: 270
Number of pages: 19
eISSN: 1999-4907
DOI: https://doi.org/10.3390/f6010252
Abstract
Research activities combining lidar and radar remote sensing have increased in recent years. The main focus in combining lidar-radar forest remote sensing has been on the retrieval of the above ground biomass (AGB), which is a primary variable related to carbon cycle in land ecosystems, and has therefore been identified as an essential climate variable. In this review, we summarize the studies combining lidar and radar in estimating forest AGB. We discuss the complementary use of lidar and radar according to the relevance of the added value. The most promising prospects for combining lidar and radar data are in the use of lidar-derived ground elevations for improving large-area biomass estimates from radar, and in upscaling of lidar-based AGB data across large areas covered by spaceborne radar missions.
Research activities combining lidar and radar remote sensing have increased in recent years. The main focus in combining lidar-radar forest remote sensing has been on the retrieval of the above ground biomass (AGB), which is a primary variable related to carbon cycle in land ecosystems, and has therefore been identified as an essential climate variable. In this review, we summarize the studies combining lidar and radar in estimating forest AGB. We discuss the complementary use of lidar and radar according to the relevance of the added value. The most promising prospects for combining lidar and radar data are in the use of lidar-derived ground elevations for improving large-area biomass estimates from radar, and in upscaling of lidar-based AGB data across large areas covered by spaceborne radar missions.
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