Seamless Upscaling of the Field-Measured Grassland Aboveground Biomass Based on Gaussian Process Regression and Gap-Filled Landsat 8 OLI Reflectance

Seamless Upscaling of the Field-Measured Grassland Aboveground Biomass Based on Gaussian Process Regression and Gap-Filled Landsat 8 OLI Reflectance

The spatially explicit aboveground biomass (AGB) generated through upscaling field measurements is critical for carbon cycle simulation and optimized management of grasslands. However, the spatial gaps that exist in the optical remote sensing data, underutilization of the multispectral data cube and...

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Bibliographic Details
Main Authors: Gaofei Yin, Ainong Li, Chaoyang Wu, Jiyan Wang, Qiaoyun Xie, Zhengjian Zhang, Xi Nan, Huaan Jin, Jinhu Bian, Guangbin Lei
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:ISPRS International Journal of Geo-Information
Subjects:
aboveground biomass (AGB)
uncertainty
consistent adjustment of the climatology to actual observations (CACAO)
Gaussian process regression (GPR)
Online Access:http://www.mdpi.com/2220-9964/7/7/242

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http://www.mdpi.com/2220-9964/7/7/242

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