Abstract
Mapping the regional distribution of forest canopy height and aboveground biomass is worthwhile and necessary for estimating the carbon stocks on Earth and assessing the terrestrial carbon flux. In this study, we produced maps of forest canopy height and the aboveground biomass at a 30 m spatial resolution in Maryland by combining Geoscience Laser Altimeter System (GLAS) data and Landsat spectral imageries. The processes for calculating the forest biomass included the following: (i) processing the GLAS waveform and calculating spatially discrete forest canopy heights; (ii) developing canopy height models from Landsat imagery and extrapolating them to spatially contiguous canopy heights in Maryland; and, (iii) estimating forest aboveground biomass according to the relationship between canopy height and biomass. In our study, we explore the ability to use the GLAS waveform to calculate canopy height without ground-measured forest metrics (R2 = 0.669, RMSE = 4.82 m, MRE = 15.4%). The machine learning models performed better than the principal component model when mapping the regional forest canopy height and aboveground biomass. The total forest aboveground biomass in Maryland reached approximately 160 Tg. When compared with the existing Biomass_CMS map, our biomass estimates presented a similar distribution where higher values were in the Western Shore Uplands region and Folded Application Mountain section, while lower values were located in the Delmarva Peninsula and Allegheny Mountain regions.
Highlights
Increasing concerns regarding global climatic changes have emphasized the urgency of finding efficient ways to quantify terrestrial carbon stocks at regional, continental, and global scales [1]
2m72et0hfoodre(sRt2c=a0n.o6p06y, hReMigShEts=i4n.7M8 amry, MlanRdE. =F1ig5u.9r%e )3. a shows the results of the simple canopy height methoFdur(tRh2er=m0o.6r0e,6w, ReMalSsEo =us4e.d781m82,0MpRoiEnt=s 1to5.e9s%ta).blish a linear empirical relationship (Equation (2)) in orFduertthoeromptoimrei,zweecaanlsoopuysheedig1h82t 0(Hp)o. ints to establish a linear empirical relationship (Equation (2))
A regression was run between the estimated canopy height from the Geoscience Laser Altimeter System (GLAS) waveform and the canopy height from the NASA Carbon Monitoring System (CMS) with an acceptable result (R2 = 0.669, RMSE = 4.82 m, MRE = 15.4%)
Summary
Increasing concerns regarding global climatic changes have emphasized the urgency of finding efficient ways to quantify terrestrial carbon stocks at regional, continental, and global scales [1]. Forest biomass is of primary importance for the assessment and management of carbon resources on Earth. Changes in forest biomass can be a good proxy for the analysis of the global carbon cycle and a valid resource for the estimation of sequestration and carbon sources/sinks [2,3]. Scientific researchers use forest biomass to study ecosystem biodiversity [4,5]. Efforts have been made to mitigate the deforestation and emissions of greenhouse gases. Such forest biomass studies will record valuable information that can be used to evaluate the effects of these efforts. It is strongly necessary to explore an efficient approach to assess forest biomass at regional, continental, and even global scales
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
