Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2014, Vol. 26 Issue (4) : 91-96     DOI: 10.6046/gtzyyg.2014.04.15
Technology and Methodology |
Method for inspection of frame digital aerial photographic quality
CHEN Jie, YANG Dachang, DU Lei, LI Jing, HAN Yachao
China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China
Download: PDF(973 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

At present, the aerial photographic quality inspection still uses the traditional method to check the digital frame images' quality, which prints the digital images on paper first and then checks them manually. The method greatly limits the advantages of digital aerial photography. This paper presents a fully digital aerial photographic quality inspection method, whose whole process is fully completed on computer. Firstly, index images are used to complete the image quality inspection, Then the aerial photography flight quality inspection software and airborne POS (position and orientation system) data are employed to check such quality factors as overlap, swing angle, strip deformation, and flying height, Finally, relevant documentation is collated and prepared according to the results. In order to verify the reliability and scientificalness of this method, the authors selected the manual quality inspection results of Hengyang area in Hunan Province to make comparison and analysis. The results show that this method can actually reflect the flight quality of aerial photography, is in good consistency with manual results, and has some other advantages such as simple operation, high efficiency and low cost.

Keywords GIS      remote sensing      natural disaster      emergency monitoring and evaluation      application demonstration system     
:  TP75  
Issue Date: 17 September 2014
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
TANG Tong
FAN Yida
YANG Siquan
WANG Lei
WANG Ping
Cite this article:   
TANG Tong,FAN Yida,YANG Siquan, et al. Method for inspection of frame digital aerial photographic quality[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(4): 91-96.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2014.04.15     OR     https://www.gtzyyg.com/EN/Y2014/V26/I4/91

[1] 中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.GB/T 24356-2009,测绘成果质量检查与验收[S].北京:中国标准出版社,2009. General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China,Standardization Administration of the People's Republic of China.GB/T 24356-2009,specifications for quality inspection and acceptance of surveying and mapping products[S].Beijing:China Standards Publishing House,2009.

[2] 中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.GB/T 6962-2005,1∶500,1∶1 000,1∶2 000比例尺地形图航空摄影规范[S].北京:中国标准出版社,2005. General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China,Standardization Administration of the People's Republic of China.GB/T 6962-2005, specification for aerial photography of 1∶500,1∶1 000,1∶2 000 scale topographic maps[S].Beijing:China Standards Publishing House,2005.

[3] 中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.GB/T 15661-2008,1∶5 000,l∶10 000,1∶25 000,1∶50 000,1∶100 000比例尺地形图航空摄影规范[S].北京:中国标准出版社,2008. General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China,Standardization Administration of the People's Republic of China.GB/T 15661-2008, specifications for aerial photography of 1∶5 000, 1∶10 000, 1∶25 000, 1∶50 000, 1∶100 000 topographic maps[S].Beijing:China Standards Publishing House,2008.

[4] 中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.GB/T 27920,1-2011,数字航空摄影规范·第1部分:框幅式数字航空摄影[S].北京:中国标准出版社,2012. General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China,Standardization Administration of the People's Republic of China.GB/T 27920,1-2011, specifications for digital aerial photography-Part 1:Frame digital aerial photography[S].Beijing:China Standards Publishing House,2012.

[5] 黄琳云.关于框幅式数字航空摄影成果质检方法的探讨[J].江西测绘,2013,2:52-53. Huang L Y.Discussion on quality inspection of frame digital photogrammetric images[J].Jiangxi Surveying,2013,2:52-53.

[6] 曾衍伟,易尧华,李倩,等.框幅式数字航空摄影成果质量检查方法研究[J].测绘,2011,34(5):195-197. Zeng Y W,Yi Y H,Li Q,et al.Research on frame digital aerial photography products quality inspection method[J].Surveying,2011,34(5):195-197.

[7] 袁桂生,顾宝永,黄健.数字航空影像的质量控制和检查[J].现代测绘,2003,(s1):102-103. Yuan G S,Gu B Y,Huang J.Quality control and inspection on digital aerial photography images[J]. Modern Surveying and Mapping,2003,(s1):102-103.

[8] 四川省测绘地理信息局.框幅式数字航空摄影成果质量检验技术[EB/OL].(2012-09-08)[2014-01-10].http://www.scbsm.com/kjjy/kjcghb/4757.htm. Sichuan Administration of Surveying Mapping and Geoinformation.Technology of frame digital aerial photographic quality inspection.[EB/OL].(2012-09-08)[2014-01-10].http://www.scbsm.com/kjjy/kjcghb/4757.htm.

[9] 华夏经纬网."航空摄影质量自动检查系统"在西安成功研发.[EB/OL].(2013-06-12)[2014-01-10].http://www.huaxia.com/zjsx/xwsc/2013/06/3390405.html. www.huaxia.com."System of aerial photographic quality inspection"has successful developed in Xi'an.[EB/OL].(2013-06-12)[2014-01-10].http://www.huaxia.com/zjsx/xwsc/2013/06/3390405.html.

[10] 段福洲,赵文吉.基于图像匹配的机载遥感影像质量自动检查方法研究[J].测绘科学,2010,35(6):57-58. Duan F Z,Zhao W J.Method of aerial remotely sensing image qulity evaluation base on image match[J].Science of Surveying and Mapping,2010,35(6):57-58.

[11] 余长慧,曾衍伟.数字航空摄影成果的自动质量检查系统设计[J].测绘信息与工程,2011,36(1):8-10. Yu C H,Zeng Y W.The Developing of automatic quality check software on digital photogrammetric products[J].Surveying Information and Engineering,2011,36(1):8-10.

[12] 吴石虎.航空摄影飞行质量数字化验收系统的设计与实现[D].郑州:解放军信息工程大学,2005. Wu S H.Design and implementation of digital aerial photography quality inspection system[D].Zhengzhou:PLA Information Engineering University,2005.

[1] LI Weiguang, HOU Meiting. A review of reconstruction methods for remote-sensing-based time series data of vegetation and some examples[J]. Remote Sensing for Natural Resources, 2022, 34(1): 1-9.
[2] DING Bo, LI Wei, HU Ke. Inversion of total suspended matter concentration in Maowei Sea and its estuary, Southwest China using contemporaneous optical data and GF SAR data[J]. Remote Sensing for Natural Resources, 2022, 34(1): 10-17.
[3] GAO Qi, WANG Yuzhen, FENG Chunhui, MA Ziqiang, LIU Weiyang, PENG Jie, JI Yanzhen. Remote sensing inversion of desert soil moisture based on improved spectral indices[J]. Remote Sensing for Natural Resources, 2022, 34(1): 142-150.
[4] ZHANG Qinrui, ZHAO Liangjun, LIN Guojun, WAN Honglin. Ecological environment assessment of three-river confluence in Yibin City using improved remote sensing ecological index[J]. Remote Sensing for Natural Resources, 2022, 34(1): 230-237.
[5] WU Yijie, KONG Xuesong. Simulation and development mode suggestions of the spatial pattern of “ecology-agriculture-construction” land in Jiangsu Province[J]. Remote Sensing for Natural Resources, 2022, 34(1): 238-248.
[6] HE Peng, TONG Liqiang, GUO Zhaocheng, TU Jienan, WANG Genhou. A study on hidden risks of glacial lake outburst floods based on relief amplitude: A case study of eastern Shishapangma[J]. Remote Sensing for Natural Resources, 2022, 34(1): 257-264.
[7] LIU Wen, WANG Meng, SONG Ban, YU Tianbin, HUANG Xichao, JIANG Yu, SUN Yujiang. Surveys and chain structure study of potential hazards of ice avalanches based on optical remote sensing technology: A case study of southeast Tibet[J]. Remote Sensing for Natural Resources, 2022, 34(1): 265-276.
[8] LI Dong, TANG Cheng, ZOU Tao, HOU Xiyong. Detection and assessment of the physical state of offshore artificial reefs[J]. Remote Sensing for Natural Resources, 2022, 34(1): 27-33.
[9] WANG Qian, REN Guangli. Application of hyperspectral remote sensing data-based anomaly extraction in copper-gold prospecting in the Solake area in the Altyn metallogenic belt, Xinjiang[J]. Remote Sensing for Natural Resources, 2022, 34(1): 277-285.
[10] LYU Pin, XIONG Liyuan, XU Zhengqiang, ZHOU Xuecheng. FME-based method for attribute consistency checking of vector data of mines obtained from remote sensing monitoring[J]. Remote Sensing for Natural Resources, 2022, 34(1): 293-298.
[11] ZHANG Daming, ZHANG Xueyong, LI Lu, LIU Huayong. Remote sensing image segmentation based on Parzen window density estimation of super-pixels[J]. Remote Sensing for Natural Resources, 2022, 34(1): 53-60.
[12] XUE Bai, WANG Yizhe, LIU Shuhan, YUE Mingyu, WANG Yiying, ZHAO Shihu. Change detection of high-resolution remote sensing images based on Siamese network[J]. Remote Sensing for Natural Resources, 2022, 34(1): 61-66.
[13] ZANG Liri, YANG Shuwen, SHEN Shunfa, XUE Qing, QIN Xiaowei. A registration algorithm of images with special textures coupling a watershed with mathematical morphology[J]. Remote Sensing for Natural Resources, 2022, 34(1): 76-84.
[14] SONG Renbo, ZHU Yuxin, GUO Renjie, ZHAO Pengfei, ZHAO Kexin, ZHU Jie, CHEN Ying. A method for 3D modeling of urban buildings based on multi-source data integration[J]. Remote Sensing for Natural Resources, 2022, 34(1): 93-105.
[15] AI Lu, SUN Shuyi, LI Shuguang, MA Hongzhang. Research progress on the cooperative inversion of soil moisture using optical and SAR remote sensing[J]. Remote Sensing for Natural Resources, 2021, 33(4): 10-18.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech