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Local uncertainty maps for land-use/land-cover classification without remote sensing and modeling work using a class-conditional conformal approach
International Journal of Applied Earth Observation and Geoinformation ( IF 7.6 ) Pub Date : 2024-12-10 , DOI: 10.1016/j.jag.2024.104288
Denis Valle, Rodrigo Leite, Rafael Izbicki, Carlos Silva, Leo Haneda

Land use/land cover (LULC) is one of the most impactful global change phenomenon. As a result, considerable effort has been devoted to creating large-scale LULC products from remote sensing data, enabling the scientific community to use these products for a wide range of downstream applications. Unfortunately, uncertainty associated with these products is seldom quantified because most approaches are too computationally intensive. Furthermore, uncertainty maps developed for large regions might fail to perform adequately at the spatial scale in which they will be used and might need to be customized to suit the specific applications of end-users.

中文翻译:


用于土地利用/土地覆被分类的局部不确定性地图,无需遥感和使用类条件保形方法进行建模工作



土地利用/土地覆被 (LULC) 是影响最大的全球变化现象之一。因此,人们投入了大量精力从遥感数据创建大规模 LULC 产品,使科学界能够将这些产品用于广泛的下游应用。遗憾的是,与这些产品相关的不确定性很少被量化,因为大多数方法的计算量都太大了。此外,为大区域开发的不确定性地图可能无法在它们将使用的空间尺度上充分执行,并且可能需要进行定制以适应最终用户的特定应用程序。
更新日期:2024-12-10
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