Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2010, Vol. 22 Issue (s1) : 169-173     DOI: 10.6046/gtzyyg.2010.s1.35
Technology Application |

An Analysis of the Effect of Peculiar Geological and Geomorphologic Conditions on Water Erosion Desertification in Guangxi

CHEN Hua 1, SONG Zhi-hong 2, WANG Yong-jiang 1
1. China Aero Geophysical Survey & Remote Sensing Center for Land and Resources, Beijing 100083, China; 2.School of Resources and Safety Engineering, China University of Mining and Technology, Beijing 100083, China
Download: PDF(854 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

 Guangxi is one of the less developed areas in China. With increasing population and accelerating regional

exploitation, water erosion desertification has become increasingly serious. The peculiar lithology and structure of

Guangxi are likely to form specific physiognomy. This paper holds that there exists direct effect of physiognomy, lithology

and structure on water erosion desertification in Guangxi, with the physiognomy being the primary factor in this aspect.

Based on GIS analysis, the authors have found that the water erosion desertification is mostly distributed in such  areas

as carbonate, granite, mudstone and gritstone. The area of carbonate is most serious in this aspect, possessing 46% of the

total desertification area. This paper has analyzed the lithology, structure, physiognomy of the desertification area. Some

logical control countermeasures are also put forward in this paper.

Keywords Hyperspectral remote sensing      Burnt rock      Fe3+content quantitative analysis     
:     
  TP 79  
Issue Date: 13 November 2010
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
WAN Yu-qing
YAN Yong-zhong
Cite this article:   
WAN Yu-qing,YAN Yong-zhong.
An Analysis of the Effect of Peculiar Geological and Geomorphologic Conditions on Water Erosion Desertification in Guangxi[J]. REMOTE SENSING FOR LAND & RESOURCES, 2010, 22(s1): 169-173.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2010.s1.35     OR     https://www.gtzyyg.com/EN/Y2010/V22/Is1/169

[1]中国荒漠化(土地退化)防治研究课题组. 中国荒漠化(土地退化)防治研究[M]. 北京:中国环境科学出版社,1998:32-47.


[2]刘柏根,温桃芳,梅宗焕,等. 江西宁都县地质因素与水土流失的关系[J]. 水土保持研究,1999(2):146-150.


[3]庞衍军,叶维强,黎广钊,等. 广西新构造运动的一些特征[J]. 广西地质,1987(1):49-56.


[4]Valle H F Del, Elissalde N O, Gagliardini D A, et al. Status of Desertification in the Patagonian Region:Assessment


and Mapping from Satellite Imagery[J]. Arid Soil Research and Rehabilitations, 1998,12:95-121.


[5]Tripathy G K, Ghosh T K, Shah S D. Monitoring of Desertification Process in Karnataka State of India Using


Multitemporal Remote Sensing and Ancillary Information Using GIS[J]. International Journal of Remote Sensing, 1996,17(12)


:2243-2257.


[6]朱震达,刘恕. 中国北方地区的沙漠化过程及其治理区划[M]. 北京:中国林业出版社,1981.


[7]陈建平,王功文,厉青,等. 北京及邻区荒漠化动态演化的遥感综合研究[J]. 遥感信息,2002(3):17-20.


[8]王世杰,李阳兵,李瑞玲. 喀斯特石漠化形成背景、演化与治理[J]. 第四纪研究,2003,23(6):657-666.


[9]袁道先. 中国岩溶生态系统[M]. 北京:地质出版社,2002:39-47.


[10]杨景春. 中国地貌特征与演化[M]. 北京:海洋出版社,1993:78-90.


[11]张龙. 华南地区几种常见岩性的水土流失成因与治理措施研究[J]. 资源调查与环境,2002(04):288-291.


[12]张建国,赵惠君. 山西省砂页岩土石山区土壤侵蚀的基本规律[J]. 人民黄河,1994(4):23-26.

[1] WANG Qian, REN Guangli. Application of hyperspectral remote sensing data-based anomaly extraction in copper-gold prospecting in the Solake area in the Altyn metallogenic belt, Xinjiang[J]. Remote Sensing for Natural Resources, 2022, 34(1): 277-285.
[2] GAO Wenlong, ZHANG Shengwei, LIN Xi, LUO Meng, REN Zhaoyi. The remote sensing-based estimation and spatial-temporal dynamic analysis of SOM in coal mining[J]. Remote Sensing for Natural Resources, 2021, 33(4): 235-242.
[3] JIANG Yanan, ZHANG Xin, ZHANG Chunlei, ZHONG Chengcheng, ZHAO Junfang. Classification of remote sensing images based on multi-scale feature fusion using local binary patterns[J]. Remote Sensing for Natural Resources, 2021, 33(3): 36-44.
[4] ZANG Chuankai, SHEN Fang, YANG Zhengdong. Aquatic environmental monitoring of inland waters based on UAV hyperspectral remote sensing[J]. Remote Sensing for Natural Resources, 2021, 33(3): 45-53.
[5] HU Xinyu, XU Zhanghua, CHEN Wenhui, CHEN Qiuxia, WANG Lin, LIU Hui, LIU Zhicai. Construction and application effect of normalized shadow vegetation index NSVI based on PROBA/CHRIS image[J]. Remote Sensing for Land & Resources, 2021, 33(2): 55-65.
[6] WANG Ruijun, ZHANG Chunlei, SUN Yongbin, WANG Shen, DONG Shuangfa, WANG Yongjun, YAN Bokun. Application of hyperspectral spectroscopy to constructing polymetallic prospecting model in Hongshan, Gansu Province[J]. Remote Sensing for Land & Resources, 2020, 32(3): 222-231.
[7] Donghui ZHANG, Yingjun ZHAO, Kai QIN. Design and construction of the typical ground target spectral information system[J]. Remote Sensing for Land & Resources, 2018, 30(4): 206-211.
[8] Jing CUI, Xinfeng DONG, Rui DING, Shimin ZHANG, Conghe WANG, Hengxin LU, Yanyun SUN. Stratigraphic division of loess along loess profile based on hyperspectral remote sensing[J]. Remote Sensing for Land & Resources, 2018, 30(2): 202-207.
[9] REN Guangli, YANG Min, LI Jianqiang, GAO Ting, LIANG Nan, YI Huan, YANG Junlu. Application of hyperspectral alteration information to gold prospecting: A case study of Fangshankou area,Beishan[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(3): 182-190.
[10] SU Hongjun, LIU Hao. A novel dynamic classifier selection algorithm using spatial-spectral information for hyperspectral classification[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(2): 15-21.
[11] LIN Na, YANG Wunian, WANG Bin. Pixel un-mixing for hyperspectral remote sensing image based on kernel method[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(1): 14-20.
[12] HE Hao, SHEN Yonglin, LIU Xiuguo, MA Li. Spatial-spectral constrained graph-based semi-supervised classification for hyperspectral image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 31-36.
[13] CHAI Ying, RUAN Renzong, CHAI Guowu, FU Qiaoni. Species identification of wetland vegetation based on spectral characteristics[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 86-90.
[14] DAI Xiaoai, JIA Hujun, ZHANG Xiaoxue, WU Fenfang, GUO Shouheng, YANG Wunian, YANG Ye. Identification of hyperspectral features for subalpine typical vegetation in the upper reaches of the Minjiang River[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 174-180.
[15] CHEN Shulin, BI Yinli. Application of remote sensing technology to microbial reclamation[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(3): 16-23.
Viewed
Full text


Abstract

Cited

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