基于对象的地裂缝分步提取方法研究与应用

doi:10.6046/gtzyyg.2019.01.12

摘要
图/表
参考文献
相关文章
Metrics

全文: PDF(4819 KB)

HTML
输出: BibTeX | EndNote (RIS)

摘要

基于遥感影像的区域尺度地裂缝自动提取技术存在光谱范围不确定和几何特征多样导致提取精度低的问题,对此提出了一种基于对象的地裂缝分步提取方法。首先,对影像进行分割,根据分割对象的光谱和几何特征,掩模去除与地裂缝区别较大的地表干扰要素; 然后,提取影像中的线性对象,去除不具有线性特征的地表要素; 最后,计算线性对象的分形特征,进一步区分地裂缝和其他线性地表要素,实现地裂缝的精确提取。以鄂尔多斯东北部某煤矿开采区为研究区进行实验,结果表明,该方法能够有效地提取地裂缝,正确率达到85.7%,高于传统监督分类精度(57.1%)和知识模型提取精度(71.4%)。在提取结果的基础上,研究了典型研究区的地裂缝分布特点,分析其与采空区位置以及地形的空间关系,结果显示该研究区的地裂缝个数与采空区距离呈现负相关关系,而与地形没有明显的相关性。研究可为区域性地质环境保护和矿区煤炭资源合理开发提供必要的技术支撑。

	服务

	把本文推荐给朋友
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	张兴航
	朱琳
	王威
	孟利山
	李小娟
	任应超

关键词 ： GeoEye影像, 地裂缝, 分步提取, 特征提取

Abstract：

The automatic extraction technology of regional scale ground fissures based on remote sensing images has the problem of low spectral range and low geometric feature, which leads to low extraction precision. Therefore, the sequential step extraction method for ground fissures based on objects is proposed. Firstly, the image is segmented. According to the spectral and geometric characteristics of segmentation object, surface interference factors which are different from the ground fissures are removed by mask. On such a basis, the linear objects are extracted and the surface factors without linear features are removed ultimately. Finally, the fractal characteristics of linear objects are calculated to differentiate between the ground fissures and other linear surface factors and complete the automatic extraction of ground fissures. The method was applied to the extraction of ground fissures in a coal-mining region of northeastern Ordos. The results show that the method is effective in extracting the ground fissures. Its accuracy reaches 85.7%, which is better than the precision of traditional supervised classification method (57.1%) and the precision of knowledge model extraction method (71.4%) . On the basis of extraction results, this paper discusses the distribution characteristics of ground fissures. The respective relations between ground fissures and the location of goafs as well as topography are analyzed. The results show that the number of ground fissures is negatively correlated to the distance of goafs and is not clearly correlated to the topography. The research can provide the necessary technical support for the regional geological environment protection and the rational exploitation of coal resources in the mining area.

Key words： GeoEye image ground fissures sequential extraction feature extraction

收稿日期: 2017-09-30 出版日期: 2019-03-15

TP79

基金资助:中国地质调查局地质调查项目“华北地区煤铀资源开发放射性地质环境调查”(DD20160130);国家高分专项项目联合资助(02-Y30B19-9001-15/17)

通讯作者: 朱琳

作者简介: 张兴航(1992-),女,硕士研究生,研究方向为信息水文地质。Email: jhj580724@163.com。

引用本文:

张兴航, 朱琳, 王威, 孟利山, 李小娟, 任应超. 基于对象的地裂缝分步提取方法研究与应用[J]. 国土资源遥感, 2019, 31(1): 87-94.
Xinghang ZHANG, Lin ZHU, Wei WANG, Lishan MENG, Xiaojuan LI, Yingchao REN. Study and application of sequential extraction method of ground fissures based on object. Remote Sensing for Land & Resources, 2019, 31(1): 87-94.

链接本文:

https://www.gtzyyg.com/CN/10.6046/gtzyyg.2019.01.12 或 https://www.gtzyyg.com/CN/Y2019/V31/I1/87

Fig.1 研究区位置图

Fig.2 技术流程图

Fig.3 不同分割尺度结果对比

Tab.1 地裂缝光谱范围

Tab.2 地裂缝几何特征阈值范围

Fig.4 掩模处理结果

Fig.5 Canny算子线性提取对比

Fig.6 试验区线性特征提取结果

Fig.7 试验区地裂缝提取结果

Fig.8 试验区监督分类和知识模型提取结果图

Tab.3 试验区地裂缝提取结果精度评价

Fig.9 研究区地裂缝提取结果图

Fig.10 研究区地裂缝方向玫瑰图

Tab.4 煤矿开采区不同缓冲区内地裂缝个数统计表

Tab.5 地形等间距的地裂缝个数统计表

[1]	符继卫 . 矿区采空塌陷与地裂缝灾害探析[J]. 山西焦煤科技, 2011,35(7):46-48. doi: 10.3969/j.issn.1672-0652.2011.07.013
	Fu J W . Discussion on mining subsidence and ground fissures[J]. Shanxi Coking Coal Science and Technology, 2011,35(7):46-48.
[2]	Xu L Q, Li S Z, Cao X Z , et al. Holocene intracontinental deformation of the northern North China Plain:Evidence of tectonic ground fissures[J]. Journal of Asian Earth Sciences, 2016,119(9):49-64. doi: 10.1016/j.jseaes.2016.01.003
[3]	Peng J B, Qiao J W, Leng Y Q , et al. Distribution and mechanism of the ground fissures in Wei River Basin,the origin of the Silk Road[J]. Environmental Earth Sciences, 2016,75(8):718. doi: 10.1007/s12665-016-5527-3
[4]	赵炜 . 基于GIS、RS技术的陕北煤炭开发区地裂缝信息的自动提取[D]. 西安:长安大学, 2009.
	Zhao W . Based on the GIS and RS Technology of Remote Sensing of Cracks in the Coal Mining Area in North Shaanxi[D]. Xi’an:Chang’an University, 2009.
[5]	王娅娟, 孟淑英, 李军 , 等. 地裂缝信息遥感提取方法研究[J]. 神华科技, 2011,9(5):31-33,39. doi: 10.3969/j.issn.1674-8492.2011.05.010
	Wang Y J, Meng S Y ,Li J. et al.Study on remote sensing extraction of cracks information[J]. Shen Hua Science and Technology, 2011,9(5):31-33,39.
[6]	魏长婧, 汪云甲, 王坚 , 等. 无人机影像提取矿区地裂缝信息技术研究[J]. 金属矿山, 2012,41(10):90-92,96. doi: 10.3969/j.issn.1001-1250.2012.10.024
	Wei C J, Wang Y J ,Wang J. et al.The technical research of extracting ground fissure information in mining area with the UAV image[J]. Metal Mine, 2012,41(10):90-92,96.
[7]	Wang Y J, Tian F, Huang Y , et al. Monitoring coal fires in Datong coalfield using multi-source remote sensing data[J]. Transactions of Nonferrous Metals Society of China, 2015,25(10):3421-3428. doi: 10.1016/S1003-6326(15)63977-2
[8]	肖春蕾, 郭兆成, 张宗贵 , 等. 利用机载LiDAR数据提取与分析地裂缝[J].国土资源遥感, 2014(4):111-118.doi: 10.6046/gtzyyg.2014.04.18. doi: 10.6046/gtzyyg.2014.04.18
	Xiao C L, Guo Z C, Zhang Z G , et al. Extraction and analysis of ground fissures from airborne LiDAR data[J]. Remote Sensing for Land and Resources, 2014,26(4):111-118.doi: 10.6046/gtzyyg.2014.04.18.
[9]	Gruen A, Li H . Semi-automatic linear feature extraction by dynamic programming and LSB-Snakes[J]. Photogrammetric Engineering and Remote Sensing, 1997,63(8):985-995.
[10]	李朝锋 . 遥感图像智能处理[M]. 北京: 电子工业出版社, 2007.
	Li Z F. Intelligent Processing of Remote Sensing Images[M]. Beijing: Pubshing House of Electronics Industry, 2007.
[11]	Peng J B, Sun X H, Wang W , et al. Characteristics of land subsidence,earth fissures and related disaster chain effects with respect to urban hazards in Xi’an,China[J]. Environmental Earth Sciences, 2016,75(16):1190. doi: 10.1007/s12665-016-5928-3
[12]	张正健, 李爱农, 雷光斌 , 等. 基于多尺度分割和决策树算法的山区遥感影像变化检测方法——以四川攀西地区为例[J]. 生态学报, 2014,34(24):7222-7232. doi: 10.5846/stxb201310112439
	Zhang Z J, Li A N, Lei G B , et al. Change detection of remote sensing images based on multiscale segmentation and decision tree algorithm over mountainous area:A case study in Panxi region,Sichuan Province[J]. Acta Ecologica Sinica, 2014,34(24):7222-7232.
[13]	鲁恒, 付萧, 李龙国 , 等. 最优分割尺度支持下高分遥感影像水土资源信息分类[J]. 农业机械学报, 2016,47(9):327-333. doi: 10.6041/j.issn.1000-1298.2016.09.044
	Lu H, Fu X, Li L G , et al. Soil and water resources information classification in high resolution images with optimal segmentation scale[J]. Transactions of the Chinese Society for Agricultural Machinery, 2016,47(9):327-333.
[14]	宫兆宁, 赵雅莉, 赵文吉 , 等. 基于光谱指数的植物叶片叶绿素含量的估算模型[J]. 生态学报, 2014,34(20):5736-5745. doi: 10.5846/stxb201301250160
	Gong Z N, Zhao Y L, Zhao W J , et al. Estimation model for plant leaf chlorophyll content based on the spectral index content[J]. Acta Ecologica Sinic, 2014,34(20):5736-5745.
[15]	王今飞 . 遥感卫星图像中线性地质特征的自动提取[J]. 第四纪研究, 2000,20(3):252-258. doi: 10.3321/j.issn:1001-7410.2000.03.006
	Wang J F . Automated geologic lineament detection from satellite remote sensing imagery[J]. Quaternary Sciences, 2000,20(3):252-258.
[16]	吴俐民, 於雪琴, 黄亮 . FCM聚类算法协同Canny算子的遥感影像边缘检测方法[J]. 测绘工程, 2014,23(12):1-4. doi: 10.3969/j.issn.1006-7949.2014.12.001
	Wu L M, Yu X Q, Huang L . Edge detection method of remote sensing images based on FCM clustering algorithm and canny operator. Engineering of Surveying and Mapping, 2014,23(12):1-4.
[17]	孙少林, 马志强, 汤伟 . 灰度图像二值化算法研究[J]. 价值工程, 2010,29(5):142-143. doi: 10.3969/j.issn.1006-4311.2010.05.080
	Sun S L, Ma Z Q, Tang W . Research on gray-level image binarization algorithms[J]. Value Engineering, 2010,29(5):142-143.
[18]	Mandelbrot B B . The fractal geometry of nature[J]. The Quarterly Review of Biology, 1983,58(3):412-413. doi: 10.1119/1.13295
[19]	宋晓夏, 唐跃刚, 李伟 , 等. 中梁山南矿构造煤吸附孔分形特征[J]. 煤炭学报, 2013,38(1):134-139. doi:
	Song X X, Tang Y G, Li W , et al. Fractal characteristics of adsorption pores of tectonic coal from Zhongliangshan southern coalmine[J]. Journal of China Coal Society, 2013,38(1):134-139.

[1]	曲海成, 王雅萱, 申磊. 多感受野特征与空谱注意力结合的高光谱图像超分辨率算法[J]. 自然资源遥感, 2022, 34(1): 43-52.
[2]	栗旭升, 刘玉锋, 陈冬花, 刘赛赛, 李虎. 结合图像特征的支持向量机高分一号云检测[J]. 国土资源遥感, 2020, 32(3): 55-62.
[3]	魏英娟, 郑雄伟, 雷兵, 甘宇航. 基于样本模型的高分一号遥感影像云雾自动提取[J]. 国土资源遥感, 2017, 29(s1): 39-45.
[4]	张永梅, 杨飞, 许静. 改进的变长夹角链码算法及在码头识别中的应用[J]. 国土资源遥感, 2016, 28(4): 164-169.
[5]	李孚煜, 叶发茂. 基于SIFT的遥感图像配准技术综述[J]. 国土资源遥感, 2016, 28(2): 14-20.
[6]	刘鹏程. 基于水平集理论的海岸线轮廓特征提取[J]. 国土资源遥感, 2015, 27(2): 75-79.
[7]	肖春蕾, 郭兆成, 张宗贵, 李迁, 尚博譞, 吴芳. 利用机载LiDAR数据提取与分析地裂缝[J]. 国土资源遥感, 2014, 26(4): 111-118.
[8]	常睿春, 王璐, 王茂芝. FastICA在高光谱遥感矿物信息提取中的应用[J]. 国土资源遥感, 2013, 25(4): 129-132.
[9]	李婷, 詹庆明, 喻亮. 基于地物特征提取的车载激光点云数据分类方法[J]. 国土资源遥感, 2012, 24(1): 17-21.
[10]	崔林林, 罗毅, 包安明. NWFE结合纹理特征的SVM土地覆被分类方法研究[J]. 国土资源遥感, 2012, 24(1): 36-42.
[11]	沈照庆, 陶建斌. 基于模糊核主成分分析的高光谱遥感影像特征提取研究[J]. 国土资源遥感, 2009, 21(3): 41-44.
[12]	柴登峰, 舒宁, 张剑清. 动态DEM匹配方法研究[J]. 国土资源遥感, 2002, 14(1): 38-42.

Viewed

Full text

Abstract

Cited

Shared

Discussed