Multidimensional extraction of UAV tilt photography-based information of loess landslide and its application
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摘要:
本文针对黄土地区地质灾害调查与评估需求，探索了一种基于无人机倾斜摄影影像和飞控数据的滑坡单体信息多维提取的方法。通过影像处理获得的DEM、DOM和实景三维模型等多维数据，对贾家村滑坡坡形、坡度、相对高差、植被覆盖率、纵坡比降、表面积与物源体积进行定量提取，结合区域气象数据分析了贾家村滑坡年均降雨量时空分布规律，利用相关地质资料分析了其地层岩性特点和区域地质构造情况，为准确评定其稳定性及危险性提供既高效又准确的定性、定量参考依据。
Abstract:Aiming at the needs of geological disaster investigation and assessment in loess area, a multi-dimensional extraction method of landslide single information based on UAV tilt photographic image and flight control data was explored. Rich information of the Jiajiacun landslide was quantitatively extracted from DEM, DOM and real scene 3D model obtained by image processing, including its slope shape, slope, relative height difference, vegetation coverage, longitudinal slope ratio, surface area and source volume. The stratigraphic lithology and regional structure are analyzed by using relevant geological data. Combined with the regional meteorological data, the spatial and temporal distribution of annual average rainfall of Jiajicun landslide was analyzed, which provides an efficient and accurate qualitative and quantitative reference for the accurate assessment of its stability and risk.
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1. 研究目的（Objective）
甘肃省高台县大青山地区地处阿拉善地块龙首山基底杂岩带，位于酒东盆地马营凹陷东段山前沉积盆地北缘（图 1a）。区内主要出露有古元古界—新太古界龙首山岩群、中元古界蓟县系墩子沟群、海西期侵入岩、侏罗系龙凤山组和白垩系庙沟组（图 1b）。
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图 1 甘肃省高台县大青山地区大地构造位置图（a）、区域地质图（b）以及ZK1201岩性柱状图（c），含油气岩心照片（d-g）和油气成藏模式图（h）Figure 1. Tectonic location (a), regional geological map(b), lithology column(c) and drill photos of ZK1201 (d-g), hydrocarbon accumulation pattern (h) in the Daqingshan area of Gaotai County, Gansu Province为实现研究区金属资源和油气资源的综合调查，中国地质调查局发展研究中心联合甘肃省地调院、探矿工程所、吉林大学在前期“甘肃省高台县臭泥墩—西小口子地区三幅1∶5万矿产远景调查”项目基础上，通过开展专题地质填图、矿产综合信息预测、智能找矿预测等工作，部署实施钻孔ZK1201，以期实现找矿突破。
2. 研究方法（Methods）
利用研究区地质调查、磁法、激电测深、化探数据和无人机影像等资料，开展综合信息解译。采用卷积和孪生网络神经网络模型对区内典型金属矿床成矿作用特征标志、油气赋矿层位进行深度学习，提出工程验证建议。钻探验证所采用钻机为汽车钻，整机包括车底盘、动力系统、液压系统、操控系统等。
3. 结果（Results）
在综合研究和智能预测的基础上，布设的ZK1201孔在钻穿早二叠世花岗闪长岩（图 1c）后，钻遇地层，续钻至393.8 m后终孔（图 1c）。此次工作共钻遇中侏罗统龙凤山组地层220 m，共发现14层油层（总厚145 m，单层最大厚度28 m，最小厚度1.4 m）。钻孔含油性由上部砾岩（油斑级以下）向下部砂岩（富含油或饱含油）逐渐增多，其中高角度裂缝普遍见可流动原油（图 1d~g）。经国家地质实验测试中心分析，原油中饱和烃、芳烃含量分别占32.4%和34.6%，为高品质轻质原油。原油中正构烷烃分布完整，主峰碳数、奇偶优势及甾烷和藿烷分布都指示其陆相烃源岩来源。
野外地质调查发现，白垩系庙沟组近水平发育，与下伏侏罗系龙凤山组呈角度不整合接触。庙沟组主要由厚层暗色泥岩组成，并发育薄层暗色粉砂质泥岩，可能为区域烃源岩层。初步判断成熟的烃源岩排出的油气沿角度不整合运移至侏罗系砂砾岩和砂岩储层后，被逆冲推覆花岗岩体封闭，形成构造-岩性油气藏（图 1h）。
研究发现区域内沉积盆地最南缘边界处在祁连山北缘断裂之下，最北缘处在龙首山断裂的下盘，南北跨度约80 km。区域内沉积地层较厚，其中侏罗系龙凤山组厚约2100 m，白垩系庙沟组厚约900 m，说明研究区具有较大的成藏潜力。此次油气藏的发现，预示着大青山地区具有完整的油气成藏系统，显示出良好油气勘探前景。建议进一步加强油气基础地质调查研究工作。
4. 结论（Conclusions）
（1）在大青山地区花岗岩逆冲推覆体之下的中生代沉积地层中发现原油，所发现的高品质轻质原油，具陆相烃源岩来源特征。
（2）研究区具有良好的油气勘探前景，建议进一步加强油气地质调查研究工作。
5. 致谢（Acknowledgement）
感谢甘肃省地质调查院董国强，北京探矿工程研究所渠洪杰、谭春亮以及国家实验测试中心沈斌在野外工作和样品测试过程中的协助。
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图 2 贾家村滑坡DSM和DEM模型
a—原始测量数据构建的DSM初步模型；b—插值法处理后的DEM完整模型
Figure 2. The DSM and DEM model of Jiajiacun landslide
a-Preliminary DSM model based on original measurement data; b-complete DEM model based on Interpolation method
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图 7 贾家村滑坡相对高差分布图
Figure 7. Distribution of relative height difference of Jiajiacun landslid
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图 8 贾家村滑坡相对高差分布直方图
Figure 8. Histogram of relative height difference of Jiajiacun landslid
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图 11 贾家村滑坡纵向、横向剖面线
Figure 11. Longitudinal and transverse section lines of Jiajiacun landslide
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图 14 三维模型立体量测高差与坡长
Figure 14. Three-dimensional model height difference and slope length
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Bi Kai, Zhao Junxia, Ding Xiaobo, Liu Fei. 2017. Technical design and product quality inspection of oblique aerial photography[J]. Bulletin of Surveying and Mapping, (4): 71-76(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-CHTB201704018.htm
Department of Land and Resources of Gansu Province, China. 2014. A Detailed Investigation Report on Geological Disasters in Guanghe, Linxia Hui Autonomous Prefecture[R]. Lanzhou(in Chinese).
Ding Hui, Zhang Maosheng, Zhu Weihong, Zhang Tao. 2019. High resolution remote sensing for the identification of loess landslides: example from Yan'an City[J]. Northwestern Geology, 52(3): 231-239(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTotal-XBDI201903024.htm
Guo Jiawei, Li Yongshu, Li Zheng, Liu Kunming, Zhang Shuaiyi. 2016. An automatic interpretation model for mountains landslide disaster of high-resolution remote sensing images based on transfer learning[J]. Journal of Geomatics Science and Technology, 33(5): 496-501(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTotal-JFJC201605011.htm
Li Ying, Su Guozhong, Lin Zongjian. 2017. Study on the method of extracting high precision DEM from oblique image[J]. Bulletin of Surveying and Mapping, (2): 30-34(in Chinese with English abstract). http://search.cnki.net/down/default.aspx?filename=CHTB201702008&dbcode=CJFD&year=2017&dflag=pdfdown
Lu Xuejun, Shi Zhenchun, Shang Weitao, Zhou Heyi. 2014. The method and application of multi-dimensional interpretation for landslides using high resolution remote sensing image[J]. Journal of Image and Graphics, 19(1): 141-149(in Chinese with English abstract). http://d.wanfangdata.com.cn/periodical/zgtxtxxb-a201401018
Peng Dalei, Xu Qiang, Dong Xiujun, Ju Yuanzhen, Qi Xing, Tao Yeqing. 2017. Application of unmanned aerial vehicles low-altitude photogrammetry in investigation and evaluation of loess landslide[J]. Advances in Earth Science, 32(3): 319-330(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-DXJZ201703008.htm
Peng Jianbing, Lin Hongzhou, Wang Qiyao, Zhuang Jianqi, Cheng Yuxiang, Zhu Xinghua. 2014. The critical issues and creative concepts in mitigation research of loess geological hazards[J]. Journal Engineering Geology, 22(4): 684-691(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-GCDZ201404018.htm
Qiao Jianping, Wang Meng, Wu Caiyan. 2016. Landslides risk assessment method of Wenchuan M8.0 earthquake region[J]. Journal of Catastrophology, 31(1): 55-59(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-ZHXU201601013.htm
Shen Yonglin, Li Xiaojing, Wu Lixin. 2011. Detection of Haiti earthquake induced landsides from aerial images and LiDAR data[J]. Geography and Geo-Information Science, 27(1): 16-20 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-DLGT201101005.htm
Shi Mingchang, Shen Jingyu. 2006. Studies on the relations between the grids size of various undulate landforms and the accuracy of DEM[J]. Research of Soil and Water Conservation, 13(3): 35-38(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-STBY200603010.htm
Wang Futao, Wang Shixin, Zhou Yi, Wang Litao. Yan Fuli, Li Wenjun, Liu Xiongfei. 2016. High resolution remote sensing monitoring and assessment of secondary geological disasters triggered by the Lushan earthquake[J]. Spectroscopy and Spectral Analysis, 36(1): 181-185(in Chinese with English abstract). http://www.ncbi.nlm.nih.gov/pubmed/27228764
Wang Jiayun, Wang Genlong, Shi Xiaoya. 2019. Analysis on the mechanical analysis of apparent slip-failure of Shanyang large landslide in Shaanxi[J]. Geology in China, 46(2): 381-388(in Chinese with English abstract).
Xu Chong, Xu Xiwei, Wu Xiyan, Dai Fuchu, Yao Xin, Yao Qi. 2013. Detailed catalog of landslides triggered by the 2008 Wenchuan earthquake and statistical analyses of their spatial distribution[J]. Journal Engineering Geology, 21(1): 25-44(in Chinese with English abstract).
Xue Y, Meng X, Guo P, Li K, Guan C. 2015. The correlation of spatial distribution between surface deformation and landslides by SBAS-InSAR and spatial analysis in Longnan region, China[J]. Open Civil Engineering Journal, 9(1): 867-876. doi: 10.2174/1874149501509010867
Zhang Shuxuan, Yang Weimin, Cheng Xiaojie, Tian You, Li Hao, Huang Xiao. 2017. Genetic mechanism and stability analysis of loess landslides group in Tianshui Hongqishan, Gansu Province[J]. Geology in China, 44(5): 924-937(in Chinese with English abstract). http://www.researchgate.net/publication/324131373_Genetic_mechanism_and_stability_analysis_of_loess_landslides_group_in_Tianshui_Hongqishan_Gansu_Province
Zhao Chenchen. 2015. Research on Key Technologies of Automatic DSM Extraction from Multi-View Oblique Images[D]. Zhengzhou: People's Liberation Army Information Engineering University(in Chinese with English abstract).
Zhao Yingshi. 2013. Remote Sensing Application Analysis Principle and Method[M]. Beijing: Science Press: 1-502(in Chinese).
Zhu Qing, Cao Zhenyu, Lin Hui, Xie Weiting, Ding Yulin. 2014. Key technologies of emergency surveying and mapping service system[J]. Geomatics and Information Science of Wuhan University, 39(5): 551-555(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-WHCH201405009.htm
Zuo Jianyang, Ni Wankui. 2016. Fast implementation of 3D visualization modeling method for accurate calculation of earth-rock work[J]. Bulletin of Soil and Water Conservation, 36(6): 136-138(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-STTB201606026.htm
毕凯, 赵俊霞, 丁晓波, 刘飞. 2017. 倾斜航空摄影技术设计与成果质量检验[J]. 测绘通报, (4): 71-76. https://www.cnki.com.cn/Article/CJFDTOTAL-CHTB201704018.htm 丁辉, 张茂省, 朱卫红, 张涛. 2019. 黄土滑坡高分辨率遥感影像识别——以陕西省延安市地区为例[J]. 西北地质, 52(3): 231-239. https://www.cnki.com.cn/Article/CJFDTOTAL-XBDI201903024.htm 甘肃省国土资源厅. 2014. 临夏回族自治州广河县地质灾害详细调查报告[R]. 兰州. 郭加伟, 李永树, 李政, 刘锟铭, 张帅毅. 2016. 迁移学习支持下的高分影像山地滑坡灾害解译模型[J]. 测绘科学技术学报, 33(5): 496-501. https://www.cnki.com.cn/Article/CJFDTOTAL-JFJC201605011.htm 李莹, 苏国中, 林宗坚. 2017. 倾斜影像中提取高精度DEM的方法研究[J]. 测绘通报, (2): 30-34. https://www.cnki.com.cn/Article/CJFDTOTAL-CHTB201702008.htm 鲁学军, 史振春, 尚伟涛, 周和颐. 2014. 滑坡高分辨率遥感多维解译方法及其应用[J]. 中国图象图形学报, 19(1): 141-149. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201401018.htm 彭大雷, 许强, 董秀军, 巨袁臻, 亓星, 陶叶青. 2017. 无人机低空摄影测量在黄土滑坡调查评估中的应用[J]. 地球科学进展, 32(3): 319-330. https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201703008.htm 彭建兵, 林鸿州, 王启耀, 庄建琦, 成玉祥, 朱兴华. 2014. 黄土地质灾害研究中的关键问题与创新思路[J]. 工程地质学报, 22(4): 684-691. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201404018.htm 乔建平, 王萌, 吴彩燕. 2016. 汶川8.0级地震灾区滑坡风险评估方法[J]. 灾害学, (1): 55-59. doi: 10.3969/j.issn.1000-811X.2016.01.012 沈永林, 李晓静, 吴立新. 2011. 基于航空影像和LiDAR数据的海地地震滑坡识别研究[J]. 地理与地理信息科学, 27(1): 16-20. https://www.cnki.com.cn/Article/CJFDTOTAL-DLGT201101005.htm 史明昌, 沈晶玉. 2006. 不同地貌起伏状况下网格尺寸与DEM精度关系研究[J]. 水土保持研究, 13(3): 35-38. doi: 10.3969/j.issn.1005-3409.2006.03.011 王福涛, 王世新, 周艺, 王丽涛, 阎福礼, 李文俊, 刘雄飞. 2016. 高分辨率多光谱的芦山地震次生地质灾害遥感监测与评估[J]. 光谱学与光谱分析, 36(1): 181-185. https://www.cnki.com.cn/Article/CJFDTOTAL-GUAN201601048.htm 王佳运, 王根龙, 石小亚. 2019. 陕西山阳特大型滑坡视向滑移-溃屈破坏力学分析[J]. 中国地质, 46(2): 381-388. http://geochina.cgs.gov.cn/geochina/ch/reader/view_abstract.aspx?file_no=20190214&flag=1 许冲, 徐锡伟, 吴熙彦, 戴福初, 姚鑫, 姚琪. 2013.2008年汶川地震滑坡详细编目及其空间分布规律分析[J]. 工程地质学报, 21(1): 25-44. doi: 10.3969/j.issn.1004-9665.2013.01.004 张树轩, 杨为民, 程小杰, 田尤, 李浩, 黄晓. 2017. 甘肃天水红旗山黄土滑坡群成因及稳定性分析[J]. 中国地质, 44(5): 924-937. http://geochina.cgs.gov.cn/geochina/ch/reader/view_abstract.aspx?file_no=20170507&flag=1 赵琛琛. 2015. 多视角倾斜影像DSM自动提取的关键技术研究[D]. 郑州: 解放军信息工程大学. 赵英时. 2013. 遥感应用分析原理与方法(第二版)[M]. 北京: 科学出版社: 1-502. 朱庆, 曹振宇, 林珲, 谢维挺, 丁雨淋. 2014. 应急测绘保障体系若干关键问题研究[J]. 武汉大学学报(信息科学版), 39(5): 551-555. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201405009.htm 左健扬, 倪万魁. 2016. 快速实现三维可视化土石方量精确计算的方法与应用[J]. 水土保持通报, 36(6): 136-138. https://www.cnki.com.cn/Article/CJFDTOTAL-STTB201606026.htm
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