Aboveground Biomass Changes in Tropical Montane Forest of Northern Borneo Estimated Using Spaceborne and Airborne Digital Elevation Data

Ho Yan Loh,Wilson Vun Chiong Wong,Satoshi Tsuyuki,Daniel James,Keiko Ioki,Mui-How Phua

doi:10.3390/rs12223677

Abstract

Monitoring anthropogenic disturbances on aboveground biomass (AGB) of tropical montane forests is crucial, but challenging, due to a lack of historical AGB information. We examined the use of spaceborne (Shuttle Radar Topographic Mission Digital Elevation Model (SRTM) digital surface model (DSM)) and airborne (Light Detection and Ranging (LiDAR)) digital elevation data to estimate tropical montane forest AGB changes in northern Borneo between 2000 and 2012. LiDAR canopy height model (CHM) mean values were used to calibrate SRTM CHM in different pixel resolutions (1, 5, 10, and 30 m). Regression analyses between field AGB of 2012 and LiDAR CHM means at different resolutions identified the LiDAR CHM mean at 1 m resolution as the best model (modeling efficiency = 0.798; relative root mean square error = 25.81%). Using the multitemporal AGB maps, the overall mean AGB decrease was estimated at 390.50 Mg/ha, but AGB removal up to 673.30 Mg/ha was estimated in the managed forests due to timber extraction. Over the 12 years, the AGB accumulated at a rate of 10.44 Mg/ha/yr, which was attributed to natural regeneration. The annual rate in the village area was 8.31 Mg/ha/yr, which was almost 20% lower than in the managed forests (10.21 Mg/ha/yr). This study identified forestry land use, especially commercial logging, as the main driver for the AGB changes in the montane forest. As SRTM DSM data are freely available, this approach can be used to estimate baseline historical AGB information for monitoring forest AGB changes in other tropical regions.

Highlights

Emissions from land-use changes, such as deforestation, logging, and intensive cultivation of cropland, are the second-largest anthropogenic emissions source after fossil fuel emissions [1]
Deforestation contributes to carbon emissions, forest degradation is the result of human-induced activities that lead to a long-term reduction in forest carbon stocks
Our objectives were to examine the correlation between the canopy height information in Shuttle Radar Topographic Mission Digital Elevation Model (SRTM) data and Light Detection and Ranging (LiDAR) canopy height model (CHM) for developing an SRTM-to-LiDAR canopy height calibration model and to determine the best spatial resolution for developing an aboveground biomass (AGB) estimation model using field and LiDAR data that can be applied to the SRTM canopy height values

Summary

Introduction

Emissions from land-use changes, such as deforestation, logging, and intensive cultivation of cropland, are the second-largest anthropogenic emissions source after fossil fuel emissions [1]. Deforestation contributes to carbon emissions, forest degradation is the result of human-induced activities that lead to a long-term reduction in forest carbon stocks. The remaining upland rainforests are severely threatened by increasing anthropogenic activities, in the mountains of the Malaysian Borneo adjacent to the Indonesian border (Sarawak) in which rates of loss are 10-times greater than across the border [5]. Much of the forest loss and degradation could affect cover, structure, and carbon stocks or biomass of the remaining forests. To monitor the change of carbon stocks caused by these human disturbances, it is necessary to obtain periodical information about the aboveground biomass (AGB) of a forest. Remote sensing coupled with field sampling plots can be used to estimate the AGB of a relatively large area at an acceptable cost [7]

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Conclusion