ABSTRACT

Understanding the scale of land use/cover (LULC) map and its impacts on representing LULC is central to address earth observation issues. However, there is an absence of quantitative uncertainty evaluation of upscaled maps to be used over decades. An approach based on the Shannon entropy theory was then proposed to tackle this issue by reporting categorical heterogeneity information contained in upscaled pixels. The Majority Rule-Based aggregation algorithm was performed to generate upscaled maps at different widely used scales using a national LU map. The results reveal that substantial uncertainties inevitably exist in the upscaled maps. Additionally, the analysts demonstrate that the proposed approach can-and-indeed accurately provide spatially uncertain information of upscaled maps. These findings suggest that this approach is necessary for users to most effectively use these maps in earth observation models and should be extensively used in the future work.

摘要

了解土地利用/覆盖 (LULC) 地图的规模及其对表示 LULC 的影响是解决地球观测问题的核心。然而，几十年来使用的放大地图缺乏定量的不确定性评估。然后提出了一种基于香农熵理论的方法，通过报告放大像素中包含的分类异质性信息来解决这个问题。执行基于多数规则的聚合算法以使用国家 LU 地图生成不同广泛使用的比例尺的放大地图。结果表明，放大的地图中不可避免地存在大量不确定性。此外，分析人员证明，所提出的方法可以而且确实可以准确地提供放大地图的空间不确定信息。