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REMOTE SENSING FOR LAND & RESOURCES    2016, Vol. 28 Issue (3) : 194-199     DOI: 10.6046/gtzyyg.2016.03.30
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Production data compilation system of mine remote sensing monitoring based on ArcGIS
DIAO Mingguang1, XUE Tao1, LI Jiancun2, LI Wenji2, LIANG Jiandong1
1. School of Information Engineering, China University of Geosciences, Beijing 100083, China;
2. China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China
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Abstract  

Based on an analysis of the mine remote sensing monitoring data processing, the authors designed and developed a resulting data compilation system for mine remote sensing monitoring. The system can achieve the data preparation, information extraction, production data compilation, production data quality inspection, production data storage and other functions. Using the Plug-In GIS framework technology to achieve a sustained development, integration, testing, and releasing of functional modules, the authors solved the problem of frequent functional requirements changes due to frequent changes of storing technical requirements and improved software maintainability and scalability. Using the metadata model design based on XSD, the authors made system updating and resulting data checking easy. The practical application shows that the system provides effective support for the production data compilation, improves the production data quality and work efficiency, strengthens the operability of the production quality inspection, and reduces the working intensity and workload.

Keywords vector map constraints      image segmentation      marker-based watershed      priority queue      vectorization     
:  TP319  
Issue Date: 01 July 2016
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LI Liang
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Cite this article:   
LI Liang,LIANG Bin,XUE Peng, et al. Production data compilation system of mine remote sensing monitoring based on ArcGIS[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 194-199.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.03.30     OR     https://www.gtzyyg.com/EN/Y2016/V28/I3/194

[1] 胡鹏,黄杏元,华一新.地理信息系统教程[M].武汉:武汉大学出版社,2007. Hu P,Huang X Y,Hua Y X.Geographic Information Systems Tutorial[M].Wuhan:Wuhan University Press,2007.
[2] 杨金中,秦绪文,张志,等.矿山遥感监测理论方法与实践[M].北京:测绘出版社,2011:1-20. Yang J Z,Qin X W,Zhang Z,et al.Theory and Practice on Remote Sensing Monitoring of Mine[M].Beijing:Surveying and Mapping Press,2011:1-20.
[3] 周进生,牛建英,张旭,等.矿山遥感监测评估特点与指标体系[J].国土资源遥感,2014,26(2):1-4.doi:10.6046/gtzyyg.2014.02.01. Zhou J S,Niu J Y,Zhang X,et al.Mine remote sensing monitoring and assessment characteristics and the index system[J].Remote Sensing for Land and Resources,2014,26(2):1-4.doi:10.6046/gtzyyg.2014.02.01.
[4] 路云阁,刘采,王姣.基于国产卫星数据的矿山遥感监测一体化解决方案——以西藏自治区为例[J].国土资源遥感,2014,26(4):85-90.doi:10.6046/gtzyyg.2014.04.14. Lu Y G,Liu C,Wang J.Integrated solutions for mine remote sensing monitoring based on domestic satellite images:A case study of Tibet[J].Remote Sensing for Land and Resources,2014,26(4):85-90.doi:10.6046/gtzyyg.2014.04.14.
[5] 聂洪峰,杨金中,王晓红,等.矿产资源开发遥感监测技术问题与对策研究[J].国土资源遥感,2007,19(4):11-13.doi:10.6046/gtzyyg.2007.04.03. Nie H F,Yang J Z,Wang X H,et al.The problems in the remote sensing monitoring technology for the exploration of mineral resources and the countermeasures[J].Remote Sensing for Land and Resources,2007,19(4):11-13.doi:10.6046/gtzyyg.2007.04.03.
[6] 中国国土资源航空物探遥感中心.矿山遥感监测成果数据入库要求(V3.0)[Z].2014-11. China Aero Geophysical Survey and Remote Sensing Center for Land and Resources.Production Data Requirements for Database of Mine Remote Sensing Monitoring(V3.0)[Z].2014-11.
[7] 张朝明.程序天下·XML开发典型应用:数据标记、处理、共享与分析[M].北京:电子工业出版社,2008:26-136. Zhang C M.Program World The Typical Application of XML Development:the Marking,Handling,Sharing and Analysis of Data[M].Beijing:Electronic Industry Press,2008:26-136.
[8] 许巨平.基于ArcEngine插件式GIS应用框架的设计与实现[J].安徽地质,2011,21(1):60-62,73. Xu J P.Design and implementation of ArcEngine-based pluggable GIS application framework[J].Geology of Anhui,2011,21(1):60-62,73.
[9] 刁明光,薛涛,李建存,等.基于地质信息元数据标准的多源空间数据管理系统[J].国土资源遥感,2013,25(1):165-170.doi:10.6046/gtzyyg.2013.01.29. Diao M G,Xue T,Li J C,et al.The multi-source spatial data management system based on geological information metadata standard[J].Remote Sensing for Land and Resources,2013,25(1):165-170.doi:10.6046/gtzyyg.2013.01.29.

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