摘要
针对当前矿山遥感监测成果数据编制过程中出现的新增矿山图斑手动编号耗时长、易出错以及规范不明确的问题,基于成果数据提交技术要求的分析结果,实现全流程、自动化地对新增矿山图斑进行编号并将该过程进行可视化。该流程通过ArcPy站点包实现矢量数据分割、排序、编号以及写入等一系列操作过程;并利用ArcToolbox的定制功能,对该一体化全流程进行封装与可视化,提高其交互性与有效性;并针对ArcPy内部原有的空间排序方式的不完善之处,提出并实现了矿山图斑排序方法的改进。通过对不同县市几十至近千个图斑进行编号验证,自动编号的速度能够达到每秒数十个,且编号效率随着图斑数量的增加而提高。实验结果表明该全流程自动化功能可以为矿山遥感监测成果数据编制工作提供有效支撑,显著降低编号过程的工作量,提高工作效率,并对其他大量、重复性的遥感监测图斑编号具有适用性。
In view of the problems of manual numbering of new mine patchs in the compilation of existing mine remote sensing monitoring data,such as time-consuming and error-prone nature and unclear specification,the authors,based on the analysis of the technical requirements for the submission of achievement data,realized the whole process automation of new mine patchs numbering.By using ArcPy site package,automatic operations such as dividing vectors,sorting,numbering and writing attribute table were realized.By using the customization function of ArcToolbox,the numbering function of the whole process was encapsulated into the toolbox and visualized to improve its interactivity and effectiveness.In view of the imperfection of the original spatial sorting method in ArcPy,an improved method of mine patchs sorting method was put forward and realized.By verifying the numbering of dozens to hundreds of patches in different counties and cities,the speed of automatic numbering could reach dozens per second,and the numbering efficiency increased with the increase of the number of samples.Experimental results show that this function can provide effective support for the compilation of mine remote sensing monitoring data,significantly reduce the workload of the numbering process and improve work efficiency.In addition,this method is also applicable to other similar large and repetitive remote sensing monitoring patch numbering.
作者
陈栋
姚维岭
CHEN Dong;YAO Weiling(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
出处
《国土资源遥感》
CSCD
北大核心
2021年第2期262-269,共8页
Remote Sensing for Land & Resources
基金
中国地质调查局项目“全国矿山环境恢复治理状况遥感地质调查与监测”(编号:DD20190705)资助。
关键词
矿山遥感监测
ArcPy
图斑编号
自动编制
mine remote sensing monitoring
ArcPy
patch numbering
automatic compiling
