Effect of field plot location on estimating tropical forest above-ground biomass in Nepal using airborne laser scanning data |
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| Institution: | 1. School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI – 80101 Joensuu, Finland;2. Arbonaut Ltd., Kaislakatu 2, FI – 80130 Joensuu, Finland;1. Division of Materials Chemistry, Graduate School of Engineering, Hokkaido University, Kita-ku, Sapporo 060-8628, Japan;2. Department of Bio- and Material photonics, Chitose Institute of Science and Technology, Bibi, Chitose 066-8655, Japan;1. Department of Epidemiology, Tel Aviv Sourasky Medical Center, Affiliated to the Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel;2. Department of Obstetrics and Gynecology, Tel Aviv Sourasky Medical Center, Affiliated to the Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel;3. Department of Pediatrics, Tel Aviv Sourasky Medical Center, Affiliated to the Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel;4. Department of Radiology, Tel Aviv Sourasky Medical Center, Affiliated to the Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel;1. College of Information Engineering, Shenzhen University, Shenzhen, Guangdong, 518060, China;2. Department of Electronics, University of York, YO10 5DD, York, UK |
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| Abstract: | The prediction of tropical forest attributes using airborne laser scanning (ALS) is becoming attractive as an alternative to traditional field measurements. Area-based ALS inventories require a set of representative field plots from the study area, which may be difficult to obtain in tropical forests with limited accessibility. This study investigates the effect of sample-plot selection in Nepal, based on two accessibility factors: distance to road and degree of slope. The sparse Bayesian method was employed in the model to estimate above-ground biomass (AGB) with an independent validation dataset for model validation. Study findings showed that the sample plot distance and slope had a considerable effect on the accuracy of the AGB estimation, because the forest structure varied according to the level of accessibility. Thus, the field sample plots that are used in model construction should cover the full range of sample plot distances and slopes occurring within the area. |
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| Keywords: | ALS Field data Prediction Sampling design Tropical forest Sparse Bayesian method |
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