Urban areas have higher heterogeneity compared to natural areas,it is crucial to assessfine-resolution land cover products and discover how they differ in urban areas so that they can be efficiently used for various a...Urban areas have higher heterogeneity compared to natural areas,it is crucial to assessfine-resolution land cover products and discover how they differ in urban areas so that they can be efficiently used for various application scenarios.In this study,five typical cities in China were chosen as study areas to evaluate four commonly used 30 m land cover products:GLC_FCS30-2020,FROM-GLC30-2017,Globeland30-2020,and CLCD-2019.We analyzed the reliability of these four products using validation samples as well as by examining their area and spatial pattern consistency.Given the limitations of traditional accuracy assessments at the macro level,we added a local area evaluation to further examine the classification details in these products.The macro results indicated that four land cover products within urban areas have a similar overall accuracy,surpassing 76%,but there was a low consistency among them,ranging from 42.21%to 61.13%.The local accuracy assessment illustrated that GLC_FCS30-2020 and FROM-GLC30-2017 performed well in reflecting the intricate details of the city,however,the four products exhibited varying degrees of misclassifications and omissions.These phenomena suggest that more sophisticated algorithms are needed to consider urban particularities sincefine-resolution land cover products may fail to capture complex urban details.展开更多
基金supported by the National Natural Science Foundation of China[42090012].
文摘Urban areas have higher heterogeneity compared to natural areas,it is crucial to assessfine-resolution land cover products and discover how they differ in urban areas so that they can be efficiently used for various application scenarios.In this study,five typical cities in China were chosen as study areas to evaluate four commonly used 30 m land cover products:GLC_FCS30-2020,FROM-GLC30-2017,Globeland30-2020,and CLCD-2019.We analyzed the reliability of these four products using validation samples as well as by examining their area and spatial pattern consistency.Given the limitations of traditional accuracy assessments at the macro level,we added a local area evaluation to further examine the classification details in these products.The macro results indicated that four land cover products within urban areas have a similar overall accuracy,surpassing 76%,but there was a low consistency among them,ranging from 42.21%to 61.13%.The local accuracy assessment illustrated that GLC_FCS30-2020 and FROM-GLC30-2017 performed well in reflecting the intricate details of the city,however,the four products exhibited varying degrees of misclassifications and omissions.These phenomena suggest that more sophisticated algorithms are needed to consider urban particularities sincefine-resolution land cover products may fail to capture complex urban details.
