COSMO-SkyMed颜色变换强度RC法南京建设用地变化检测

doi:10.13474/j.cnki.11-2246.2019.0355

测绘通报 ›› 2019, Vol. 0 ›› Issue (11): 74-78,84.doi: 10.13474/j.cnki.11-2246.2019.0355

COSMO-SkyMed颜色变换强度RC法南京建设用地变化检测

张涛¹, 王源^2,3, 陈富龙², 周伟², 胡祺¹

1. 南京市规划和自然资源局, 江苏南京 210029;
2. 中国科学院遥感与数字地球研究所数字地球重点实验室, 北京 100094;
3. 中国科学院大学, 北京 100049

收稿日期:2019-04-04 发布日期:2019-12-02
通讯作者: 王源。E-mail:wangyuan@radi.ac.cn E-mail:wangyuan@radi.ac.cn
作者简介:张涛(1962-),男,高级工程师,研究方向为城市遥感测绘与地理信息。E-mail:njghjzt@126.com
基金资助:
国家自然科学基金（41771489）；国家重点研发计划（2016YFB0501502）

Nanjing City urban change detection using the color-space transformation of COSMO-SkyMed intensity RC composition imagery

ZHANG Tao¹, WANG Yuan^2,3, CHEN Fulong², ZHOU Wei², HU Qi¹

1. Nanjing Bureau of Planning and Natural Resources, Nanjing 210029, China;
2. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2019-04-04 Published:2019-12-02

摘要/Abstract

摘要： 基于非局部滤波的SAR强度RC合成变化检测法对小图斑、线型地物等动态监测灵敏，且对数据获取无时空基线要求，在多云多雨城市地表要素变化检测中具备潜力。本文研究以多时相SAR强度RC合成图为数据源，提出一种基于色彩空间变换的变化图斑半自动提取方法，即通过色彩空间转换、训练样本选取、监督分类影像分割、变化区域提取4步骤，可实现基于SAR强度图的城市建设用地动态监测与图斑高效更新。选取南京河西新城与江北新区为示范，以最优参数配置（3特征向量与10样本类别）进行试验，实现了优于88%的建设用地查准率指标。

关键词: 城市变化检测, SAR强度RC合成, 色彩空间变换, COSMO-SkyMed, 建设用地

Abstract: The developed change detection method, by utilizing the non-local filtered SAR intensity RC composition, is sensitive in the extraction of small patches and linear features. Consequently, it will indicate a better performance in practical applications, in particular this method is not constrained by additional requirements, e.g. the spatiotemporal baseline. In this study, taking the intensity RC composite imagery as the data-source, a semi-automatic change detection method is proposed by utilizing color-transformed features. In order to realize the thematic updating of urban-area land, the corresponding data procedures include four primary steps, they are color space transformation, training-sample selection, supervised classification based image segmentation, and change region extraction. Taking Hexi New Town and Jiangbei Developing District (Nanjing) as example, the checking probability is better than 88% with the optimum parameter setting (3 features along with 10 training-sample categories).

Key words: urban change detection, SAR intensity RC composition, color space transformation, COSMO-SkyMed, construction land-use

中图分类号:

P237

张涛, 王源, 陈富龙, 周伟, 胡祺. COSMO-SkyMed颜色变换强度RC法南京建设用地变化检测[J]. 测绘通报, 2019, 0(11): 74-78,84.

ZHANG Tao, WANG Yuan, CHEN Fulong, ZHOU Wei, HU Qi. Nanjing City urban change detection using the color-space transformation of COSMO-SkyMed intensity RC composition imagery[J]. Bulletin of Surveying and Mapping, 2019, 0(11): 74-78,84.

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COSMO-SkyMed颜色变换强度RC法南京建设用地变化检测

Nanjing City urban change detection using the color-space transformation of COSMO-SkyMed intensity RC composition imagery

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