气候变化领域集成服务门户(CCPortal): Above-ground biomass mapping in West African dryland forest using Sentinel-1 and 2 datasets

CCPortal

DOI	10.1016/j.rse.2019.111496
	Above-ground biomass mapping in West African dryland forest using Sentinel-1 and 2 datasets - A case study
	Forkuor G.; Benewinde Zoungrana J.-B.; Dimobe K.; Ouattara B.; Vadrevu K.P.; Tondoh J.E.
发表日期	2020
ISSN	00344257
卷号	236
英文摘要	The Sudanian Savanna (SS) of West Africa is characterized by tropical savannas and woodlands. Accurate estimation of AGB and carbon stocks in this biome is important for addressing sustainable development goals as the information can aid natural resource management at varied spatial scales. Previous AGB mapping efforts focused on humid forests, with little attention on savannas. This study explored the use of annual monthly time-series of Senitinel-1 (S-1) and Sentinel-2 (S-2) data to map AGB in the SS. Backscatter, spectral reflectance, and derivatives (vegetation indices and biophysical parameters) were combined with field inventory data in a Random Forest regression to map AGB. Eight experiments were conducted with different data configurations to determine: (1) the potential of S-1 and S-2 for AGB mapping, (2) optimal image acquisition period for AGB mapping, and (3) contribution of image derivatives to improving the accuracy of AGB mapping. The predicted map was validated with 40% of the inventory data. Uncertainty in the AGB was assessed using mean absolute error, root mean squared error, coefficient of determination and symmetrical mean absolute percentage error. Results show that about 90% of the study area have low AGB stocks of less than 90 Mg/ha. Compared to S-1 (RMSE: 78.6; MAE: 25.6), S-2 achieved better prediction accuracy (RMSE: 60.6; MAE: 19.2), although combination of the two according to seasonality produced the best results (RMSE: 45.4; MAE: 16.3). Images acquired in the dry season were found to be more useful for predicting AGB than those of rainy season. Also, stress-related vegetation indices and a red-edge dependent normalized difference vegetation index not tested in previous AGB studies using Sentinels were found to be significant contributors to the superior performance of S-2. Since biomass is a finite resource, our results can provide valuable information on the sustainable use of biomass and energy security including studies on carbon cycling and ecosystem functions in the region. The demonstrated possibility of using open access earth observation data to map and monitor AGB in data scarce regions is useful and beneficial to attaining SDG indicators 15.2.1 (sustainable forest management) and 15.3.1 (proportion of land that is degraded over total land area). Further work on developing species-specific wood densities and allometric equations is required to improve AGB and carbon stock estimation in the SS. © 2019 Elsevier Inc.
英文关键词	Above-ground biomass; Random forest; SDGs; Sentinel; Sudanian savanna; West africa
语种	英语
scopus关键词	Biomass; Carbon; Decision trees; Ecosystems; Energy security; Errors; Forestry; Image acquisition; Image enhancement; Mapping; Mean square error; Monitoring; Natural resources management; Uncertainty analysis; Vegetation; Above ground biomass; Random forests; SDGs; Sentinel; Sudanian savanna; West Africa; Information management; aboveground biomass; accuracy assessment; algorithm; backscatter; biomass; carbon sequestration; data set; satellite data; savanna; Sentinel; spatial analysis; woodland; West Africa
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179590
作者单位	West African Science Service Center on Climate Change and Adapted Land Use, Competence, Center, Avenue Muamar Ghadhafi, Ouagadougou, BP 9507, Burkina Faso; NASA Marshall Space Flight Center, Huntsville, Albama, United States; Nangui Abrogoua University, Department of Natural Sciences, 02 BP 801 Abidjan 02, Cote d'Ivoire
推荐引用方式 GB/T 7714	Forkuor G.,Benewinde Zoungrana J.-B.,Dimobe K.,et al. Above-ground biomass mapping in West African dryland forest using Sentinel-1 and 2 datasets - A case study[J],2020,236.
APA	Forkuor G.,Benewinde Zoungrana J.-B.,Dimobe K.,Ouattara B.,Vadrevu K.P.,&Tondoh J.E..(2020).Above-ground biomass mapping in West African dryland forest using Sentinel-1 and 2 datasets - A case study.Remote Sensing of Environment,236.
MLA	Forkuor G.,et al."Above-ground biomass mapping in West African dryland forest using Sentinel-1 and 2 datasets - A case study".Remote Sensing of Environment 236(2020).