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Remote Sensing for Land & Resources    2020, Vol. 32 Issue (3) : 240-246     DOI: 10.6046/gtzyyg.2020.03.31
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Dynamic change detection method of vector result data in mine remote sensing monitoring
DIAO Mingguang1(), LIU Wenjing1, LI Jing1, LIU Fang1, WANG Yanzuo2
1. School of Information Engineering, China University of Geosciences(Beijing), Beijing 100083, China
2. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China
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Abstract  

In order to effectively carry out remote sensing monitoring work of mine geological environment restoration and management, the authors established a model for dynamic change detection of vector data, and proposed an automatic method for change detection of vector result data, which is suitable for the change of mine geological features. According to the spatial topological relationship and the attribute change situation of different temporal vector result data, the dynamic change of elements is automatically analyzed and detected, and the plug-in application framework based on ArcGIS Engine (AE) is used to develop the dynamic change detection software of result data. The results show that this method improves effectively the efficiency of dynamic change detection of vector result data, reduces the workload of restoring, harnessing and mining damaged data when they are put into storage, and provides strong support for relevant departments to further monitor the recovery and management of mine geological environment.
Keywords vector result data      change detection      variation types of spatial data      mine remote sensing monitoring      plug-in development     
:  TP311  
Issue Date: 09 October 2020
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Mingguang DIAO
Wenjing LIU
Jing LI
Fang LIU
Yanzuo WANG
Cite this article:   
Mingguang DIAO,Wenjing LIU,Jing LI, et al. Dynamic change detection method of vector result data in mine remote sensing monitoring[J]. Remote Sensing for Land & Resources, 2020, 32(3): 240-246.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020.03.31     OR     https://www.gtzyyg.com/EN/Y2020/V32/I3/240
Fig.1  Organization structure of data
属性名称 字段编码 字段类型 字段长度 约束条件 字段阈值
用户ID KFID C 18 M 综合代码
占地面积 KFZDMJ F 16位整数、2位小数 M —
治理状态 ZLZT C 1 O 单一代码
治理方式 ZLFS C 100 B或C 自由文本
说明 属性名称缩写,用来描述图层特性 C为文本型;F为浮点型 面积类16位整数、2位小数;文本类不超过256位;坐标类保留6位小数 M为必填;O为选填;B为已治理;C为部分治理 包括综合代码、单一代码、代码表、自由文本。综合代码按特定规则组合;单一代码、代码表为枚举值
Tab.1  Definition of partial attribute information of vector data
Fig.2  Process of dynamic change detection
变化类型代码 变化类型 旧时态 新时态
10 新增要素
20 灭失要素
3A 延续要素增加
3B 延续要素减少
3C 延续要素不变
Tab.2  variation types of different time-state spatial data
Fig.3  Topological relationship between polygon A and B
拓扑关系 数学描述 变化类型
不相交 Ta={a|t∈T,o∈O且t∩o=ф,a=t} 10
Ob={b|o∈O,t∈T且o∩t=ф,b=o} 20
相交/包含 Tc={c|t∈T,o∈O且t∩o≠ф,c=t-o} 3A
Td={d|t∈T,o∈O且t∩o≠ф,d=t∩o} 3C
Oe={e|o∈O,t∈T且t∩o≠ф,e=o-t} 3B
Tab.3  Mathematical description of variation types
Fig.4  Metadata management model
Fig.5  Application framework architecture based on AE
Fig.6  Dynamic change detection model
Fig.7  Development of land-occupied vector data in 2015,2016
Fig.8  Five kinds of change detection results
Fig.9  Dynamic change detection results
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