粤港澳大湾区部分城市遥感影像数据集

传统的遥感影像分析方法主要基于像素，而不同遥感数据源的空间分辨率存在较大差异，难以开展基于像素的融合分析。在多源遥感数据融合分类方面，面向对象的分析技术具有较大的应用潜力。为探索面向对象的多源遥感数据融合分类技术，实现城市土地利用/覆盖的精确提取和识别，项目组获取了多个年份、不同种类的粤港澳大湾区广州、深圳、东莞、香港、澳门5个城市的遥感影像数据，形成了本数据集。Traditional remote sensing image analysis methods are mostly pixel-based. However, there are significant discrepancies in the spatial resolutions of different remote sensing data sources, making pixel-based fusion analysis difficult to conduct. Object-oriented analysis technologies have great application potential in multi-source remote sensing data fusion classification. To explore such object-oriented multi-source remote sensing data fusion classification technologies and achieve accurate extraction and recognition of urban land use/cover, the research team collected remote sensing image data of five cities in the Guangdong-Hong Kong-Macao Greater Bay Area, namely Guangzhou, Shenzhen, Dongguan, Hong Kong and Macau, across multiple years and of various types, and thus developed this dataset.

搜集汇总

背景与挑战

背景概述

该数据集包含粤港澳大湾区广州、深圳、东莞、香港、澳门5个城市的多源遥感影像数据，旨在支持面向对象的遥感数据融合分类技术研究，实现城市土地利用/覆盖的精确识别。数据集总大小为763.47MB，覆盖多个年份和不同种类的遥感影像。