DISCUSSION ON THE SCALE PROBLEM IN REMOTE SENSING DATA FOR LOESS LANDSLIDE SURVEY IN BAOJI, SHAANXI PROVINCE, CHIAN

XU Gang

2017 Vol. 23, No. 1

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XU Gang. DISCUSSION ON THE SCALE PROBLEM IN REMOTE SENSING DATA FOR LOESS LANDSLIDE SURVEY IN BAOJI, SHAANXI PROVINCE, CHIAN[J]. Journal of Geomechanics, 2017, 23(1): 88-96.

Citation:

XU Gang. DISCUSSION ON THE SCALE PROBLEM IN REMOTE SENSING DATA FOR LOESS LANDSLIDE SURVEY IN BAOJI, SHAANXI PROVINCE, CHIAN[J]. Journal of Geomechanics, 2017, 23(1): 88-96.

DISCUSSION ON THE SCALE PROBLEM IN REMOTE SENSING DATA FOR LOESS LANDSLIDE SURVEY IN BAOJI, SHAANXI PROVINCE, CHIAN

XU Gang^1,2,

1.
Key Laboratory of Neotectonic Movement & Geohazard, Beijijng 100081, China
2.
Ministry of Land and Resources/Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijijng 100081, China

Received Date: 18 September 2016

Publish Date: 25 February 2017

Abstract

Abstract

The content and accuracy are determined by the scale of remote sensing(RS) data, the RS Processing molds or methods vary with Remote sensing data scale in the same region. Based on the landslide RS survey in Baoji loess area, we discuss the problems that have great relationship with RS scale, such as Mininum regional area of landslide mass in different RS data source, precision measurement of spot area, the best and maxinum mapping scale, comparative analysis of interpretation of RS geological hazards, accuracy evaluation of landslide RS interpretation and so on. The result reveals that when investgating large and medium-sized landslide in Baoji loess area, SPOT-5(2.5 m)Fused image data can be used, and the scale is 1:25000 or 1:50000. Meanwhile, QuickBird(0.61m)Fused image data is used for medium-small landslide and quantitative information calculation on the internal structure of larger landslide, and the scale is 1:5000.
- Loess Landslide /
- Remote Sensing Data /
- Scale in Remote Sensing /
- Precision Problem /
- Object Identity

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References

[1]	Metternicht G, Hurni L and Gogu R. Remote sensing of landslides: An analysis of the potential contribution to geospatial systems for hazard assessment in mountainous environments. Remote Sensing of Environment, 2005, 98(2/3):284~303. Google Scholar
[2]	Nichol J E, Shaker A and Wong M S. Application of high-resolution stereo satellite images to detailed landslide hazard assessment.Geomorphology, 2006, 76(1/2):68~75. Google Scholar
[3]	Weirich F and Blesius L. Comparison of satellite and air photo based landslide susceptibility maps. Geomorphology, 2007, 87(4):352~364. Google Scholar
[4]	Wasowski J and Singhroy V. Special issue from the symposium on Remote Sensing and Monitoring of Landslides. Engineering Geology, 2003, 68(1/2):1~2. Google Scholar
[5]	Mantovani F, Soeters R and Van Westen C Y, . Remote sensing techniques for landslide studies and hazard zonation in Europe. Geomorphology, 1996, 15(3/4):213~225. Google Scholar
[6]	Hervas J, Barredo J I, Rosin P L, Pasuto A, Mantovani F, Silvano, S. Monitoring landslides from optical remotely sensed imagery:the case history of Tessina landslide, Italy.Geomorphology, 2003, 54(1/2):63~75. Google Scholar
[7]	Fourniadis I G, Liu J G and Mason P J, Landslide hazard assessment in the Three Gorges area, China, using ASTER imagery: Wushan-Badong. Geomorphology, 2007, 73(1/2):131~148. Google Scholar
[8]	Cheng K S, Wei C and Chang S C. Locating landslides using multi-temporal satellite images. Advances in Space Research, 2004, 33(3):296~301. doi: 10.1016/S0273~1177(03)00471-X CrossRef Google Scholar
[9]	Chadwick J, Dorsch S, Glenn N, Thackray G and Shilling K. Application of multi-temporal high-resolution imagery and GPS in a study of the motion a canyon rim landslide.ISPRS Journal of Photogrammetry and Remote Sensing, 2005, 59(4):212~221. doi: 10.1016/j.isprsjprs.2005.02.001 CrossRef Google Scholar
[10]	Schwab M, Rieke-Zapp D, Schneider H, Liniger M and Schlunegger F. Landsliding and sediment flux in the Central Swiss Alps: A photogrammetric study of the Schimbrig landslide, Entlebuch. Geomorphology, In Press, Corrected Proof, 2007. Google Scholar
[11]	Lee S and Lee M J. Detecting landslide location using KOMPSAT 1 and its application to landslide-susceptibility mapper at the Gangneung area, Korea. Advances in Space Research, 2006, 38(10):2261~2271. Google Scholar
[12]	Barlow J, Franklin S, Martin Y. High spatial resolution satellite imagery DEM derivatives, and image segmentation for the detection of mass wasting processes[J]. Photogrammetric Engineering & Remote Sensing, 2006, 72(6):687~692. Google Scholar
[13]	McDermid G, Franklin S. Remote Sensing and geomorphic discrimination of slope processes[J]. Zeitschrift fur Geomorphologie, 1995, 101:165~185. Google Scholar
[14]	王治华..RS+GCPs获取滑坡基本信息[J].中国地质灾害与防治学报, 2004, 15(1):94~100. Google Scholar WANG Zhi-hua.RS+GCPs Select Basic information of Landslide[J]. The Chinese Journal of Geological Hazard and Control, 2004, 15(1):94~100. Google Scholar
[15]	王治华.滑坡遥感调查、监测与评估.国土资源遥感, 2007, 1:10~15. doi: 10.6046/gtzyyg.2007.02.03 CrossRef Google Scholar WANG Zhi-hua. Landslide Remote Sensing Survey Monitoring and Evaluation[J]. Remote Sensing for land & Resource, 2007, 1: 10~15. doi: 10.6046/gtzyyg.2007.02.03 CrossRef Google Scholar
[16]	王治华.数字滑坡技术及其在天台乡滑坡调查中的应用[J].岩土工程学报, 2006, 28:516~520. doi: 10.3321/j.issn:1000~4548.2006.04.017 CrossRef Google Scholar WANG Zhi-hua. Digital Landslide Technology and Its Application in Investigation of Tiantai Town Landslide[J]. Chinese Journal of Geotechnical Engineering, 2006, 28:516~520. doi: 10.3321/j.issn:1000~4548.2006.04.017 CrossRef Google Scholar
[17]	李铁锋, 徐岳仁, 潘懋, 等.基于多期Spot~5影像的降雨型浅层滑坡遥感解译研究[J].北京大学学报(自然科学版), 2007, 43(2):204~210. Google Scholar LI Tie-feng, XU Yue-ren, PAN Mao, et al. Study on interpretation of Rain induced Group Shallow Landslides Based on Multi-period SPOT~5 Remote Sensing images[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2007, 43(2):204~210. Google Scholar
[18]	Cao, C., and Lan, N.S.N. Understanding the scale and resolution effect s in remote sensing and GIS[A]. In:Scale in Remote sensing and GIS[A]. Lewis Publishers, 1997:57~72. Google Scholar
[19]	承继成, 郭华东, 史文中等.2004.遥感数据的不确定性[M], 北京:科学出版社, 1~247. Google Scholar CHENG Ji-cheng, GUO Hua-dong, SHI Wen, et al. The Uncertainty of Remote Sensing Data[M], Beijing:Science Press, 2004, 1~247. Google Scholar
[20]	Silvestri S, Marani M, Settle J, et al. Salt Marsh Vegetation Radiometry: Data Analysis and Scaling[J]. Remote Sensing of Environment, 2002, 80(3):473~482. doi: 10.1016/S0034~4257(01)00325-X CrossRef Google Scholar
[21]	彭晓鹃, 邓孺孺, 刘小平.遥感尺度转换研究进展[J].地理与地理信息科学, 2004, 20(5):6~14. Google Scholar PENG Xiao-juan, DENG Ru-ru, LIU Xiao-ping. A Review of Scale Transformation in Remote Sensing[J]. Geography and Geo-information Science, 2004, 20(5):6~14. Google Scholar
[22]	Hay G J, Niemman K O, Good enough D G1 Spatial thresholds, image objects and up scaling: a multi-scale evaluation[J]. Remote Sensing of Environment, 1997, 62:1~19. doi: 10.1016/S0034~4257(97)81622~7 CrossRef Google Scholar
[23]	刘东生.黄土与环境[M].北京:科学出版社. 1985, 1~481. Google Scholar LIU Dong-sheng. Loess and Environment[M]. Beijing:Science Press, 1985, 1~481. Google Scholar
[24]	胡海涛, 项式均, 王肇芬, 等.关中西部滑坡的结构、构造特征及稳定性分析[J].地质学报, 1965, 45(4):435~458. Google Scholar HU Hai-tao, XIANG Shi-jun, WANG Zhao-fen, et al. The Characteristic Constitution and Structure of Landslides in Western GuanZhong Region and Analysis of their Stability[J]. Acta Geologica Sinica, 1965, 45 (4):435~458. Google Scholar
[25]	徐刚, 郑达兴, 李述靖, 等.黄土高原西南部陇县—千阳一带崩塌、滑坡地质灾害遥感解译特征及其分布规律[J].地质通报, 2008, 27(11):1837~1845. doi: 10.3969/j.issn.1671~2552.2008.11.011 CrossRef Google Scholar XU Gang, ZHENG Da-xing, LI Shu-jing, et al. Remote Sensing Images and Distribution Characteristics of Avalanche and Landslide Geohazards in the Western part of the Weihei Plateau, Shaanxi Province, China[J]. Geological Bulletin of China, 2008, 27(11):1837~1845. doi: 10.3969/j.issn.1671~2552.2008.11.011 CrossRef Google Scholar
[26]	徐刚, 郑达兴, 乔子江, 于新兵.基于高精度DEM和RS技术的滑坡环境指标参数快速提取方法研究—以宝鸡市金台区长乐塬特大型滑坡为例[J].地质通报, 2009, 28(8):1047~1052. Google Scholar XU Gang, ZHENG Da-xing, QIAO Zi-jiang, et al. Study on fast Extraction of Landslide Environmental Indicator Parameters Based on High-percision DEM and RS—A Case Study of Changleyuan Super Large-scale Landslide in Jintai District, Baoji City, Shaanxi Province, China[J]. Geological Bulletin of China, 2009, 28(8):1047~1052. Google Scholar
[27]	王晓红, 聂洪峰, 杨清华, 等.高分辨率卫星遥感数据在矿山开发状况及环境监测中的应用效果比较[J].国土资源遥感, 2004, (1):15~18. doi: 10.6046/gtzyyg.2004.01.04 CrossRef Google Scholar WANG Xiao-hong, NIE Hong-feng, YANG Qing-hua et al. The Different Monitoring Effects of Quickbird and SPOT~5 Data in Mine Exploitation[J]. Remote Sensing for land & Resource, 2004, (1): 15~18. doi: 10.6046/gtzyyg.2004.01.04 CrossRef Google Scholar
[28]	王晓红, 聂洪峰, 李成尊, 等.不同遥感数据源在矿山开发状况及环境调查中的应用[J].国土资源遥感, 2006, 68(2): 69~71. doi: 10.6046/gtzyyg.2006.02.17 CrossRef Google Scholar WANG Xiao-hong, NIE Hong-feng, LI Cheng-zun et al. The Application of Characteristics of Different Remote Sensing data Sources to the Investigation of the Mine Situation and Environment of Mines[J]. Remote Sensing for land & Resource, 2006, 68(2):69~71. doi: 10.6046/gtzyyg.2006.02.17 CrossRef Google Scholar
[29]	初艳锋, 李二森, 卢俊, 张魁珂.卫星影像空间分辨率与成图比例尺的适应性分析[J].海洋测绘, 2007, 27 (4):47~50. Google Scholar CHU Yan-feng, LI Er-sen, LU Jun, et al. The Adaptability Analysis to the Satellite Image Spatial Resolution and Mapping Scale[J]. Hydrographic Surveying and Charting, 2007, 27(4):47~50. Google Scholar
[30]	龚明劼, 张鹰, 张芸.卫星遥感制图最佳影像空间分辨率与地图比例尺关系探讨[J].测绘科学, 2009, 34(4): 232~233. Google Scholar GONG Ming-jie, ZHANG Ying, ZHANG Yun. The Discussion of the Relation Between the Scale and the best Spatial Resolution in Making Cartographies with RS[J]. Science of Surveying and Mapping, 2009, 34(4):232~233. Google Scholar
[31]	郭仕德, 林旭东.高空间分辨率遥感环境制图的几个关键技术研究[J].北京大学学报·自然科学版, 2004, 40 (1):116~120. Google Scholar GUO Shi-de, LIN Xu-dong. Some Key Techniques Research in Environmental Mapping Using High Spatial Resolution Remote Sensed Data[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2004, 40(1):116~120. Google Scholar