联合星载光学与SAR图像的城市大面积建筑物高度快速提取

田峰; 李虎

doi:10.11947/j.AGCS.2017.20160573

测绘学报 >

2017 , Vol. 46 >Issue 7: 891 - 899

DOI: https://doi.org/10.11947/j.AGCS.2017.20160573

摄影测量学与遥感

联合星载光学与SAR图像的城市大面积建筑物高度快速提取

田峰 ,
李虎

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1. 新疆大学资源与环境科学学院, 新疆乌鲁木齐 830000;
2. 新疆维吾尔自治区卫星应用中心, 新疆乌鲁木齐 830000;
3. 滁州学院, 安徽滁州 239000

田峰(1992—),男,硕士生,研究方向为城市多光谱与SAR遥感应用,国产遥感卫星应用。

收稿日期: 2016-11-24

修回日期: 2017-05-31

网络出版日期: 2017-07-25

基金资助

高分辨率对地观测系统重大专项（95-Y40B02-9001-13/15）；新疆青年科技创新人才培养工程（2013701035）；安徽省高等学校自然科学研究项目（KJ2016A526）；滁州学院科研启动基金项目（2014QD029）

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Fusion of Spaceborne Optical and SAR Images for Building Height Quick Extraction in Big Urban Areas

TIAN Feng ,
LI Hu

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1. College of Resources and Environment Sciences, Xinjiang University, Urumqi 830000, China;
2. Satellite Application Center of Xinjiang Uygur Autonomous Region, Urumqi 830000, China;
3. Chuzhou University, Chuzhou 239000, China

Received date: 2016-11-24

Revised date: 2017-05-31

Online published: 2017-07-25

Supported by

National High Resolution Earth Observation Major Project(No.95-Y40B02-9001-13/15);Xinjiang Scientific and Technological Innovation Youth Talents Training Project(No.2013701035);Natural Science Research Project of Anhui University (No.KJ2016A526);Scientific Research Initializing Fund Project of Chuzhou University(No.2014QD029)

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摘要

星载高分辨率光学图像与SAR图像广泛应用于城市建筑物高度提取，但光学图像存在缺少相关卫星参数的情况，而SAR图像则存在散射特征不完整以及提取效率低等缺陷。针对以上问题，本文提出一种联合高分辨率星载光学与SAR图像的城市大面积建筑物高度快速提取方法。首先，结合支持向量机（SVM）和形态学阴影指数（MSI）快速提取光学图像中的阴影并自动测量阴影长度；之后选择多个合适样本，基于模型匹配法从SAR图像中提取高度；最后将高度与阴影长度作线性回归分析，建立数学模型来提取其他建筑物的高度。该方法将不同卫星系统的数据和特征相结合，互相弥补各自缺陷，不仅提高了效率、降低了成本，同时满足精度要求。

关键词： 星载高分辨率图像; 建筑物高度; 大面积; 快速提取; 形态学阴影指数; 模型匹配法; 线性回归

本文引用格式

田峰 , 李虎 . 联合星载光学与SAR图像的城市大面积建筑物高度快速提取[J]. 测绘学报, 2017 , 46(7) : 891 -899 . DOI: 10.11947/j.AGCS.2017.20160573

Abstract

The spaceborne high-resolution optical images and synthetic aperture radar (SAR) images are applied to extract building height in urban areas widely. But the lack of optical satellite parameters along with the SAR images' incomplete scattering characteristics and inefficient extraction make the application flawed. To cure the above problems, we investigated the joint use of the spaceborne high-resolution optical images and SAR images to extract building height information quickly in big urban areas. The chain is decomposed into the main following steps: First, the building shadows are extracted by integrating support vector machines (SVM) with morphological shadow index (MSI) and their lengths are measured automatically. Then, the height extraction from SAR images based on a model matching technique for some appropriate samples. Finally, obtain the other heights based on the simple linear regression analysis. This approach which combines the data and feature from different satellite systems to make up the flaws for each other is not only efficient and low-cost, but also satisfy the basic accuracy requirement.

Key words： spaceborne high-resolution image; building height; big areas; quick extraction; MSI; model match technique; simple linear regression

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