高分辨率遥感影像城中村提取的景观语义指数方法

doi:10.11947/j.AGCS.2021.20190463

测绘学报 ›› 2021, Vol. 50 ›› Issue (1): 97-104.doi: 10.11947/j.AGCS.2021.20190463

高分辨率遥感影像城中村提取的景观语义指数方法

张涛¹, 丁乐乐¹, 史芙蓉²

1. 天津市勘察设计院集团有限公司, 天津 300191;
2. 武汉大学测绘遥感信息工程国家重点实验室, 武汉 430079

收稿日期:2019-11-18 修回日期:2020-09-15 发布日期:2021-01-15
通讯作者: 丁乐乐 E-mail:dinglelecumt@126.com
作者简介:张涛(1990-),男,博士,工程师,研究方向为遥感图像处理与应用。E-mail:zhangtao437@163.com
基金资助:
天津市重点研发计划科技支撑重点项目（18YFZCSF00620）；天津市重点研发计划院市合作项目（18YFYSZC00120）

Urban villages extraction from high-resolution remote sensing imagery based on landscape semantic metrics

ZHANG Tao¹, DING Lele¹, SHI Furong²

1. Tianjin Survey Design Institute Group Co., Ltd., Tianjin 300191, China;
2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Received:2019-11-18 Revised:2020-09-15 Published:2021-01-15
Supported by:
The Key Science and Technology Support Project of Key Research and Development Program of Tianjin (No. 18YFZCSF00620);The CAS-Tianjin Collaborative Project of Key Research and Development Program of Tianjin (No. 18YFYSZC00120)

摘要/Abstract

摘要： 城中村是中国一类特殊的非正式居民区。本文从城中村的物理特点出发，采用景观语义指数描述复杂的城中村场景，提出基于景观语义指数的高分辨率遥感影像城中村提取方法，并采用“分类置信度-反馈”机制进行实际可操作的大范围城中村制图。以广州市核心城区为例，城中村检测的总体精度达到了90%以上。试验结果表明相对于传统的光谱、纹理特征，景观语义指数能够更好地描述城中村的根本形态特点，更准确的城中村提取。此外，“分类置信度-反馈”机制能够充分参考机器学习的分类概率，以有限的人工干预生产更加准确的城中村制图产品。因此，本文方法能够有效应用于大范围的城中村提取与制图。

关键词: 城中村, 高分辨率遥感影像, 景观指数, 场景表达, 土地利用制图

Abstract: Urban villages (UVs), a special type of informal settlement in China. In this study, we proposed a method for UV extraction from high-resolution remote sensing imagery using landscape semantic metrics that can describe the complicated scene of UVs. In addition, an “uncertainty-feedback” strategy was proposed for large-scale practicable UV mapping. The experiment was performed in the urban areas of Guangzhou, with overall accuracy larger than 90%. The results reveal that the landscape semantic metrics have better ability to describe the essential characteristics of UVs compared to the traditional spectral and textural features. Besides, the “uncertainty-feedback” strategy can make full use of the classification reliability output by the machine learning, and produce more accurate UV mapping results with limited manual intervention. Thus, the proposed method can be effectively applied to large-scale UV extraction and mapping.

Key words: urban villages, high-resolution remote sensing imagery, landscape metrics, scene representation, land-use mapping

中图分类号:

P227

张涛, 丁乐乐, 史芙蓉. 高分辨率遥感影像城中村提取的景观语义指数方法[J]. 测绘学报, 2021, 50(1): 97-104.

ZHANG Tao, DING Lele, SHI Furong. Urban villages extraction from high-resolution remote sensing imagery based on landscape semantic metrics[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(1): 97-104.

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高分辨率遥感影像城中村提取的景观语义指数方法

Urban villages extraction from high-resolution remote sensing imagery based on landscape semantic metrics

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