MSLU-100K:在中国主要城市进行土地利用分析的大型多源数据集
Yao Yao1,2,3,4,5, Yueheng Ma6, Ronghui Gao6
1UrbanComp Lab, School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430078, Hubei province, China. yaoy@cug.edu.cn.
Scientific data
|May 7, 2025
概括
一个新的土地使用数据集MSLU-100K提供了来自中国81个城市的超过10万个样本. 这种高质量的资源整合了遥感和兴趣点 (POI) 数据,改善了土地利用识别和城市规划研究.
科学领域:
- 地理信息科学 地理信息科学
- 遥感 遥感 遥感 遥感
- 城市规划 城市规划
背景情况:
- 高质量的土地使用数据集对于研究至关重要,但由于复杂性和空间异质性,其创建具有挑战性.
- 现有的数据集可能缺乏足够的细节或质量来完成先进的土地使用分类和识别任务.
研究的目的:
- 介绍MSLU-100K,这是一个新的,大规模的,多来源的土地使用数据集为中国.
- 提供高质量的资源,解决当前土地使用数据集的局限性.
主要方法:
- 开发了一个人机协作框架,用于数据集的构建.
- 综合多源数据,包括遥感和兴趣点 (POI) 数据.
- 采用多级分类方法,将手动标签和深度学习结合起来,以确保质量.
主要成果:
- MSLU-100K包含来自中国81个城市的超过10万个不规则的包裹样本.
- 土地被分为7种主要和28种次要的土地使用类型.
- 超过57%的数据集实现了高质量分类 (第四级和第五级),显著提高了性能.
结论:
- MSLU-100K是用于土地利用识别的强大和高质量的数据集.
- 该数据集支持城市规划和空间研究的进步.
- 人与计算机的协作和多层分类方法确保了数据的可靠性.
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