气候变化领域集成服务门户(CCPortal): Assessment of multi-wavelength SAR and multispectral instrument data for forest aboveground biomass mapping using random forest kriging

CCPortal

DOI	10.1016/j.foreco.2019.05.057
	Assessment of multi-wavelength SAR and multispectral instrument data for forest aboveground biomass mapping using random forest kriging
	Chen L.; Wang Y.; Ren C.; Zhang B.; Wang Z.
发表日期	2019
ISSN	0378-1127
起始页码	12
结束页码	25
卷号	447
英文摘要	Aboveground biomass (AGB) plays an important role in carbon cycle. Assessment of AGB presents a challenge in forest management. Reported studies have explored the potential of synthetic aperture radar (SAR) and multispectral instrument (MSI) data using random forest (RF) approach in AGB mapping. However, how AGB prediction would be affected by using data from different sources based on random forest kriging (RFK), which integrates RF and estimates residuals by ordinary kriging (OK), deserves further exploration. This study reported an assessment of multisensor data from Advanced Land Observing Satellite 2 (ALOS-2) L band and Sentinel-1C band SAR, Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), and Sentinel-2 MSI for forest AGB mapping using RFK. The effectiveness of 97 predictor variables derived from multisensor data was evaluated for AGB prediction in a temperate continental forest site in northeastern China. The assessment was tested by field-measured data from 1167 forest plots in 2017. The results showed that the RFK model achieved the accuracy with mean error, mean absolute error, root mean square error and correlation coefficient in –0.11, 19.37, 28.15 Mg ha−1 and 0.98, respectively. The study revealed that backscatters and texture features from ALOS-2 L band SAR and vegetation indices from Sentinel-2 MSI were primary contributors for explaining the observed variability of AGB. Topographic indices from SRTM DEM were more important than C band SAR backscatters and texture features. The accuracy improvement on forest AGB mapping by RFK over RF was more distinguished in models using a single sensor than those using multisensors. © 2019 Elsevier B.V.
英文关键词	ALOS-2 L band SAR; Forest aboveground biomass; Random forest kriging; Sentinel-1C band SAR; Sentinel-2 MSI; SRTM DEM
语种	英语
scopus关键词	Backscattering; Biomass; Decision trees; Errors; Forecasting; Forestry; Interpolation; Mapping; Mean square error; Surveying; Synthetic aperture radar; Textures; Topography; Tracking radar; Above ground biomass; C-bands; Kriging; L-band SAR; Sentinel-2 MSI; SRTM DEM; Space-based radar; aboveground biomass; assessment method; digital elevation model; kriging; mapping method; satellite data; satellite sensor; Sentinel; Shuttle Radar Topography Mission; synthetic aperture radar; Biomass; Errors; Forecasts; Forestry; Mapping; Surveying; China
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/155921
作者单位	Northeast Institute of Geography and Agroecology, Key Laboratory of Wetland Ecology and Environment, Chinese Academy of Sciences, Changchun, 130102, China; University of Chinese Academy of Sciences, Beijing, 100049, China; Department of Natural Resources Science, University of Rhode Island, 1 Greenhouse Rd., Kingston, RI 02881, United States
推荐引用方式 GB/T 7714	Chen L.,Wang Y.,Ren C.,et al. Assessment of multi-wavelength SAR and multispectral instrument data for forest aboveground biomass mapping using random forest kriging[J],2019,447.
APA	Chen L.,Wang Y.,Ren C.,Zhang B.,&Wang Z..(2019).Assessment of multi-wavelength SAR and multispectral instrument data for forest aboveground biomass mapping using random forest kriging.Forest Ecology and Management,447.
MLA	Chen L.,et al."Assessment of multi-wavelength SAR and multispectral instrument data for forest aboveground biomass mapping using random forest kriging".Forest Ecology and Management 447(2019).