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Designing an Experiment to Investigate Subpixel Mapping as an Alternative Method to Obtain Land Use/Land Cover Maps

机译:设计用于调查亚像素映射的实验作为获取土地使用/土地覆盖图的替代方法

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Various subpixel mapping (SPM) methods have been proposed as downscaling techniques to reduce uncertainty in classifying mixed pixels. Such methods can provide category maps of a higher spatial resolution than the original input images. The aim of this study was to explore and validate the potential of SPM as an alternative method for obtaining land use/land cover (LULC) maps of regions where high-spatial-resolution LULC maps are unavailable. An experimental design was proposed to evaluate the feasibility of SPM for providing the alternative LULC maps. A case study was implemented in the Jingjinji region of China. SPM results for spatial resolutions of 500–100 m were derived from a single 1-km synthetic fraction image using two representative SPM methods. The 1-km synthetic fraction image was assumed to be error free. Accuracy assessment and analysis showed that overall accuracies of the SPM results were reduced from about 85% to 75% with increasing spatial resolution, and that producer’s accuracies varied considerably from about 62% to 93%. SPM performed best when handling areal features in comparison with linear and point features. The highest accuracies were achieved for areas with the lowest complexity. The study concluded that the results from SPM could provide an alternative LULC data source with acceptable accuracy, especially in areas with low complexity and with a large proportion of areal features.
机译:已经提出了各种子像素映射(SPM)方法作为缩小尺寸的技术,以减少分类混合像素时的不确定性。这样的方法可以提供比原始输入图像更高的空间分辨率的类别图。这项研究的目的是探索和验证SPM作为获得高空间分辨率LULC地图不可用区域的土地使用/土地覆盖(LULC)地图的替代方法的潜力。提出了一个实验设计,以评估SPM用于提供替代LULC图的可行性。在中国的京津冀地区进行了案例研究。使用两种代表性的SPM方法,从单个1 km合成分数图像中得出500–100 m空间分辨率的SPM结果。假定1公里合成分数图像没有错误。准确性评估和分析表明,随着空间分辨率的提高,SPM结果的总体准确性从大约85%降低到75%,生产者的准确性从大约62%降低到93%。与线性特征和点特征相比,SPM在处理区域特征时表现最佳。对于复杂度最低的区域,精度最高。该研究得出的结论是,SPM的结果可以提供一种具有可接受的准确性的替代LULC数据源,尤其是在复杂性较低且区域特征很大的区域中。

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