Improving the upscaling of land cover maps by fusing uncertainty and spatial structure information
Abstract
Upscaling land cover maps is broadly employed to fill data gaps or match the spatial-resolution of preexisting projects. However, existing methods introduce systematic errors in the area information and the landscape pattern. We developed an upscaling method fusing the spatial structure information (i.e., class Membership probability) and the uncertainty information of the base map (e.g., Confidence level probability), called Fusing class Membership probability and Confidence level probability (FMC). The results showed that FMC obtained higher upscaling efficiency, and mitigated the negative influence of landscape heterogeneity and the negative influence of unequal proportions of land cover in the base maps, on the upscaling compared to Majority Rule Based (MRB) method. Additionally, FMC can reduce the uncertainty/error when these upscaled maps are used as input to Earth observation model (e.g., land cover change).
Department
Natural Resources and the Environment
Publication Date
2-1-2018
Journal Title
Photogrammetric Engineering and Remote Sensing
Publisher
American Society for Photogrammetry and Remote Sensing
Digital Object Identifier (DOI)
10.14358/PERS.84.2.87
Document Type
Article
Recommended Citation
Sun, Peijun, Russell G. Congalton, and Yaozhong Pan. 2018. Improving the upscaling of land cover maps by fusing uncertainty and spatial structure information. Photogrammetric Engineering and Remote Sensing. Vol. 84, No. 2. pp. 87 – 100. DOI: 10.14358/PERS.84.2.87.
Rights
© 2018 American Society for Photogrammetry and Remote Sensing