第一个季节性绿色视图指数映射数据集跨越中国城市,由深度学习驱动
Yibin Ma1,2, Pengfei Chen3,4, Mengjie Gong1,2
1School of Geospatial Engineering and Science, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China.
Scientific data
|August 6, 2025
概括
本研究介绍了2023年季节性绿色视图指数 (SGVI-2023),这是一个新的遥感数据集,用于绘制城市绿色的地图. SGVI-2023能够对多个城市的街景植被进行大规模的季节性分析.
科学领域:
- 城市生态学 城市生态学
- 遥感科学是遥感的科学.
- 地理信息系统 (GIS) 是指地理信息系统.
背景情况:
- 多时间绿色视图指数 (GVI) 地图绘制对于评估城市季节性绿色至关重要.
- 街景图像 (SVI) 对大规模分析的时间频率和空间覆盖有局限性.
- 现有的GVI方法通常依赖于SVI,阻碍跨城市和季节性研究.
研究的目的:
- 使用遥感数据开发一个新的,大规模的,季节性解析的GVI数据集.
- 解决基于SVI的GVI估计的局限性,用于动态城市绿色监测.
- 支持以人为中心的城市绿色评估和数据驱动的城市规划.
主要方法:
- 开发了2023年季节性绿色视图指数 (SGVI-2023) 数据集,使用多源遥感数据和深度学习.
- 在中国19个主要城市中,利用了大约100万个来自2019-2023年的卫星和SVI数据样本.
- 实施严格的数据预处理和分区,以确保准确性.
主要成果:
- 在GVI估计中获得了高准确度,Pearson相关性为0.867 (点级) 和0.918 (街道级).
- SGVI-2023是第一个基于遥感的跨城市,季节性解析的GVI数据集.
- 证明了对城市街景绿化进行大规模动态监测的能力.
结论:
- SGVI-2023提供了一个强大的,基于遥感的解决方案,用于监测季节性城市绿色.
- 该数据集支持加强城市规划和更好地了解人类对城市植被的看法.
- 促进城市绿色基础设施动态的跨城市和长期分析.
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