地震研究

基于无人机、高分卫星影像资料,通过实地调研与遥感影像对比分析,建立基于无人机、高分卫星遥感影像获取建筑物的技术路线,并以甘肃省陇南市为研究区进行实例验证。研究结果表明:利用无人机航拍进行建筑物识别时,采用倾斜摄影和正射影像相结合的方式,建筑物识别效果较好,尤其是对屋顶相同或类似的不同结构建筑物的识别;基于遥感技术获取建筑物时不仅要建立区域建筑物遥感影像解译标志,还需要借助区域地理环境特征、建筑物排列、占地面积、建筑物阴影等因素进行辅助识别,才能获取较为可靠的结果; 陇南市建筑物类型主要有土木(含木构架)结构、砖木结构、砖混结构、框架结构4类,占比分别为19.25%、44.29%、31.32%、5.14%,建筑物遥感解译结果精度在-23.92%～25.28%; 基于无人机和卫星遥感影像获取居民地建筑物数据可以用于更新地震应急基础数据库,但存在一定的误差。

Based on miniature unmanned aerial vehicle(UAV),high resolution satellite images and comparison between field survey data and remote sensing image,we build a technical route to get building data through UAV and high resolution satellite images,which is validated by taking Longnan city as the study area. The research result shows that the combined use of unmanned aerial vehicle and tilt photography can lead to a better result for building recognition,especially for the different types of buildings with similar roofs. The establishment of building interpretation signs can lead to a more reliable result with the help of geographical environment characteristics,building arrangement,building area,building shadows and other factors. The building types of Longnan city are mainly civil(including wood framestructure,brick-wood structure,brick-concrete structure,frame structure,and the proportion of each type reaches 19.25%(civil structure),44.29%(brick-wood),31.32%(brick-concrete structure),5.14%(frame structure),respectively. The accuracy range of the interpretation varies from -23.92% to 25.28%. It is feasible to obtain the residential building data for the update of the earthquake emergency database based on UAV and the satellite remote sensing images though there is some errors.

引言
1 研究区与数据源选取
2 技术路线及处理方法
3 结果分析
4 结论与讨论

图1 实地调研及无人机航拍点示意图<br/>Fig.1 The schematic diagram of field survey and UAV photography

图1 实地调研及无人机航拍点示意图
Fig.1 The schematic diagram of field survey and UAV photography

图2 陇南市高分卫星遥感影像覆盖图<br/>Fig.2 The overlay of high resolution remote sensing images of Longnan city

图2 陇南市高分卫星遥感影像覆盖图
Fig.2 The overlay of high resolution remote sensing images of Longnan city

图3 建筑物识别技术路线图<br/>Fig.3 The technology roadmap of building recognition

图3 建筑物识别技术路线图
Fig.3 The technology roadmap of building recognition

图4 土木结构无人机正射影像(a)及倾斜摄影(b)<br/>Fig.4 The orthoimage(a)and oblique photography(b)of civil structure buildings

图4 土木结构无人机正射影像(a)及倾斜摄影(b)
Fig.4 The orthoimage(a)and oblique photography(b)of civil structure buildings

图5 砖木结构无人机正射影像(a)及倾斜摄影(b)<br/>Fig.5 The orthoimage(a)and oblique photography(b)of brick-wood structure buildings

图5 砖木结构无人机正射影像(a)及倾斜摄影(b)
Fig.5 The orthoimage(a)and oblique photography(b)of brick-wood structure buildings

图6 砖混结构无人机正射影像(a)及倾斜摄影(b)<br/>Fig.6 The orthoimage(a)and oblique photography(b)of brick-concrete structure buildings

图6 砖混结构无人机正射影像(a)及倾斜摄影(b)
Fig.6 The orthoimage(a)and oblique photography(b)of brick-concrete structure buildings

图7 框架结构无人机正射影像(a)及倾斜摄影(b)<br/>Fig.7 The orthoimage(a)and oblique photography(b)of frame structure buildings

图7 框架结构无人机正射影像(a)及倾斜摄影(b)
Fig.7 The orthoimage(a)and oblique photography(b)of frame structure buildings

图8 土木结构、砖混结构建筑物影像对比<br/>Fig.8 Image contrast of civil structure and brick-concrete structure buildings

图8 土木结构、砖混结构建筑物影像对比
Fig.8 Image contrast of civil structure and brick-concrete structure buildings

图9 土木结构、砖木结构建筑物影像对比<br/>Fig.9 Image contrast of civil structure and brick-wood structure buildings

图9 土木结构、砖木结构建筑物影像对比
Fig.9 Image contrast of civil structure and brick-wood structure buildings

图10 多种框架结构建筑物的高分辨率卫星影像(空间分辨率0.8 m)<br/>Fig.10 High resolution images of various frame structure buildings(the spatial resolution is 0.8 m)

图10 多种框架结构建筑物的高分辨率卫星影像(空间分辨率0.8 m)
Fig.10 High resolution images of various frame structure buildings(the spatial resolution is 0.8 m)

表1 各类建筑物遥感影像解译标志<br/>Tab.1 The remote sensing interpretation characteristics of various types of buildings

表1 各类建筑物遥感影像解译标志
Tab.1 The remote sensing interpretation characteristics of various types of buildings

图11 陇南市居民地建筑物成果图<br/>Fig.11 The result map of residential building of Longnan city

图11 陇南市居民地建筑物成果图
Fig.11 The result map of residential building of Longnan city

表2 建筑物类型统计数据与遥感解译结果对比<br/>Tab.2 Comparison of statistical data of building types with remote sensing interpretation results

表2 建筑物类型统计数据与遥感解译结果对比
Tab.2 Comparison of statistical data of building types with remote sensing interpretation results

表3 建筑物类型遥感解译结果精度评价<br/>Tab.3 Precision evaluation of remote sensing interpretation results of building types

表3 建筑物类型遥感解译结果精度评价
Tab.3 Precision evaluation of remote sensing interpretation results of building types

表4 陇南市各县(区)各类建筑物百分比<br/>Tab.4 The percentage of various types buildings in districts and counties of Longnan city

表4 陇南市各县(区)各类建筑物百分比
Tab.4 The percentage of various types buildings in districts and counties of Longnan city

表5 陇南市各县(区)地区生产总值与人均生产总值<br/>Tab.5 Local GDP and per capita GDP of districts and counties of Longnan city

表5 陇南市各县(区)地区生产总值与人均生产总值
Tab.5 Local GDP and per capita GDP of districts and counties of Longnan city

柴荣建.2011.广东省应急基础数据库更新维护方法研究[J].华南地震,31(3):96-100.
段锋,袁志祥.2010.结合汶川8.0级地震实践探讨地震应急基础数据库更新途径[J].四川地震,(1):32-35.
何少林,陈文凯,周中红,等.2014.甘肃岷县漳县6.6级地震灾情快速评估及应急处置保障[J].地震研究,37(4):589-594.
和仕芳,邓树荣,张方浩,等.2016.旋翼无人机在建筑物抗震能力调查中的应用[J].地震研究,39(4):673-679.
胡晓曦,李永树,李何超,等.2010.无人机低空数码航测与高分辨率卫星遥感测图精度试验分析[J].测绘工程,19(4):68-74.
姜立新,帅向华,聂高众,等.2014.地震应急指挥协同技术平台设计研究[J].震灾防御技术,7(3):294-302.
金伟,葛宏立,杜华强,等.2009.无人机遥感发展与应用概况[J].遥感信息,(1):88-92.
李军,李永树,蔡国林.2012.利用无人机影像制作地震灾区三维景观图[J].测绘工程,21(1):50-53.
李铁铮,翟永梅.2010.震害预测中建筑物属性信息提取方法研究[J].灾害学,25(S0):300-304.
陆博迪,孟迪文,陆鸣,等.2011.无人机在重大自然灾害中的应用与探讨[J].灾害学,26(4):122-126.
闫庆武.2011.空间数据分析方法在人口数据空间化中的应用[M].南京:东南大学出版社.
杨国东,王民水.2016.倾斜摄影测量技术应用及展望[J].测绘与空间地理信息,39(1):13-18.
袁道阳,雷中生.2014.1879年甘肃武都南8级地震的震灾特征[J].兰州大学学报,50(5):611-621.
臧克,孙永华,李京,等.2010.微型无人机遥感系统在汶川地震中的应用[J].自然灾害学报,19(3):162-166.
周洋,明小娜,杨艳珠,等.2017.灾评新技术在云龙5.0级地震烈度调查中的应用[J].地震研究,40(1):161-166.

备注

引言

1 研究区与数据源选取

2 技术路线及处理方法

3 结果分析

4 结论与讨论

期刊信息