Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    1999, Vol. 11 Issue (2) : 34-42     DOI: 10.6046/gtzyyg.1999.02.07
Technology Application |
THE APPLICATION OF REMOTE SENSING TECHNIQUE IN THE HIGHWAY PRE_FEASIBILITY RESEARCH OF PLATEAU MOUNTAINOUS AREA
Fang Xiangchi
Yunnan Highway Planning and Prospecting and Designing Institute, Kunming 650011
Download: PDF(513 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

During the comparing and slecting of the G320 Dali-Baoshan freeway, the author uses the remote sensing image for interpreting the topograph, the geomorphologic, the stratums and rock property, the geological structure and the geological disaster. By comparing the engineering geological conditions of three lines (the north line, the medium line and the south line), the author confirms that the medium line is the best than the others.

Keywords  Fast growing plantation      Time serial images      Change detection      Ecological disaster      LUCC     
Issue Date: 02 August 2011
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
WEN Qing-Ke
ZHANG Zeng-Xiang
LIU Bin
XU Jin-Yong
QIAO Zhu-Ping
Askar
Wushorali
LI Fu
Cite this article:   
WEN Qing-Ke,ZHANG Zeng-Xiang,LIU Bin, et al. THE APPLICATION OF REMOTE SENSING TECHNIQUE IN THE HIGHWAY PRE_FEASIBILITY RESEARCH OF PLATEAU MOUNTAINOUS AREA[J]. REMOTE SENSING FOR LAND & RESOURCES, 1999, 11(2): 34-42.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.1999.02.07     OR     https://www.gtzyyg.com/EN/Y1999/V11/I2/34

1 宁书年等.遥感图像处理与应用.北京:地展出版社,1995
2 Shalizi Z等.公路与环境手册.交通部水运环保科技信息网出版,1996
3 王宁明.遥感技术及其应用.北京:人民交通出版社,1991
4 朱亮琪等.遥感图像地质解译教程.北京:地质出版社,1981
5 王长姐.空间遥感图像的分析应用.北京:国防工业出版社,1985
6 黄蕊.广西公路航侧十年开发及推广作用.公路工程地质,1993,11(2)
7 马相三.应用航侧、遥感技术是提商铁路勘侧设计质t的保障.铁路航测,1995(1)
8 徐克进.遥感图像在川截公路工程地质中的应用.公路工程地质,1995,(2)
9 许也平.遥感技术在京珠高速公路奥北段工程地质勘察中的应用.公路工程地质.1995,(2)

[1] XUE Bai, WANG Yizhe, LIU Shuhan, YUE Mingyu, WANG Yiying, ZHAO Shihu. Change detection of high-resolution remote sensing images based on Siamese network[J]. Remote Sensing for Natural Resources, 2022, 34(1): 61-66.
[2] PAN Jianping, XU Yongjie, LI Mingming, HU Yong, WANG Chunxiao. Research and development of automatic detection technologies for changes in vegetation regions based on correlation coefficients and feature analysis[J]. Remote Sensing for Natural Resources, 2022, 34(1): 67-75.
[3] LI Yikun, YANG Yang, YANG Shuwen, WANG Zihao. A change vector analysis in posterior probability space combined with fuzzy C-means clustering and a Bayesian network[J]. Remote Sensing for Natural Resources, 2021, 33(4): 82-88.
[4] WANG Yiuzhu, HUANG Liang, CHEN Pengdi, LI Wenguo, YU Xiaona. Change detection of remote sensing images based on the fusion of co-saliency difference images[J]. Remote Sensing for Natural Resources, 2021, 33(3): 89-96.
[5] XU Rui, YU Xiaoyu, ZHANG Chi, YANG Jin, HUANG Yu, PAN Jun. Building change detection method combining Unet and IR-MAD[J]. Remote Sensing for Land & Resources, 2020, 32(4): 90-96.
[6] DIAO Mingguang, LIU Wenjing, LI Jing, LIU Fang, WANG Yanzuo. Dynamic change detection method of vector result data in mine remote sensing monitoring[J]. Remote Sensing for Land & Resources, 2020, 32(3): 240-246.
[7] Chunsen ZHANG, Rongrong WU, Guojun LI, Weihong CUI, Chenyi FENG. High resolution remote sensing image object change detection based on box-plot method[J]. Remote Sensing for Land & Resources, 2020, 32(2): 19-25.
[8] Yuting YANG, Hailan CHEN, Jiaqi ZUO. Remote sensing monitoring of impervious surface percentage in Hangzhou during 1990—2017[J]. Remote Sensing for Land & Resources, 2020, 32(2): 241-250.
[9] Linyan FENG, Bingxiang TAN, Xiaohui WANG, Xinyun CHEN, Weisheng ZENG, Zhao QI. Object-oriented rapid forest change detection based on distribution function[J]. Remote Sensing for Land & Resources, 2020, 32(2): 73-80.
[10] Chao MA, Panli CAI. Spatio-temporal changes and driving factors of environmental and ecological index in Culai-Lianhua area[J]. Remote Sensing for Land & Resources, 2019, 31(4): 199-208.
[11] Yizhi LIU, Huarong LAI, Dingwang ZHANG, Feipeng LIU, Xiaolei JIANG, Qing’an CAO. Change detection of high resolution remote sensing image alteration based on multi-feature mixed kernel SVM model[J]. Remote Sensing for Land & Resources, 2019, 31(1): 16-21.
[12] Zhan ZHAO, Wang XIA, Li YAN. Land use change detection based on multi-source data[J]. Remote Sensing for Land & Resources, 2018, 30(4): 148-155.
[13] Lijuan WANG, Xiao JIN, Hujun JIA, Yao TANG, Guochao MA. Change detection for mine environment based on domestic high resolution satellite images[J]. Remote Sensing for Land & Resources, 2018, 30(3): 151-158.
[14] Xinran ZHU, Bo WU, Qiang ZHANG. An improved CVAPS method for automatic updating of LUCC classification[J]. Remote Sensing for Land & Resources, 2018, 30(2): 29-37.
[15] Guanghui WANG, Jianlei LI, Huabin WANG, Huachao YANG. Change detection based on adaptive fusion of multiple features[J]. Remote Sensing for Land & Resources, 2018, 30(2): 93-99.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech