A Bayesian Based Method to Generate a Synergetic Land-Cover Map from Existing Land-Cover Products

Remote Sensing

Guang Xu¹  Hairong Zhang²  Baozhang Chen¹  Huifang Zhang¹  Jianwu Yan¹  Jing Chen¹  Mingliang Che¹  Xiaofeng Lin¹ 

[1] State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China; E-Mails:;School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China

关键词: land cover;    Bayes theory;    data fusing;    IGBP;    remote sensing;   

DOI  :  10.3390/rs6065589

来源: mdpi

【 摘 要 】

Global land cover is an important parameter of the land surface and has been derived by various researchers based on remote sensing images. Each land cover product has its own disadvantages and limitations. Data fusion technology is becoming a notable method to fully integrate existing land cover information. In this paper, we developed a method to generate a synergetic global land cover map (synGLC) based on Bayes theorem. A state probability vector was defined to precisely and quantitatively describe the land cover classification of every pixel and reduce the errors caused by legends harmonization and spatial resampling. Simple axiomatic approaches were used to generate the prior land cover map, in which pixels with high consistency were regarded to be correct and then used as benchmark to obtain posterior land cover map. Validation results show that our hybrid land cover map (synGLC, the dataset is available on request) has the best overall performance compared with the existing global land cover products. Closed shrub-lands and permanent wetlands have the highest uncertainty in our fused land cover map. This novel method can be extensively applied to fusion of land cover maps with different legends, spatial resolutions or geographic ranges.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland