Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2013, Vol. 25 Issue (4) : 133-137     DOI: 10.6046/gtzyyg.2013.04.21
Technology Application |
20 year’s evolution features and influence factor analysis of rocky desertification in Guizhou
LI Jiancun, TU Jienan, TONG Liqiang, GUO Zhaocheng
China Aero Geophysical Survey & Remote Sensing Center for Land and Resources, Beijing 100083, China
Download: PDF(759 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

Guizhous Karst rocky desertification is most serious in China. The analysis of the evolution features could provide the objective basis for the tackling and transformation of rocky desertification. The survey of the rocky desertification was based on the three phases of remote sensing images spanning 20 years (at the end of the 1980s, the end of the 1990s and the year of 2008). On the basis of geometric correction, image registration, image mosaic, radiometric correction, and information enhancement and in combination with the field examination and artificial interpretation, researchers obtained the limestone distribution map, the rocky desertification distribution map, the rocky desertification evolution map and the data base. Comparison and analysis show that, from 1988 to 1999, the rocky desertification of Guizhou Province became more and more serious, and the annual average degradation area increased by 744 km2; nevertheless, from 1999 to 2008, the area of degradation became smaller and smaller, and the degradation area was reduced by 1 153.3 km2 per year. In combination with the evolution features of rocky desertification in Guizhou Province, this paper deals with the relationship of decrease of agricultural population, the development and utilization of marsh gas, the increase of per head income and the policy of conversion of cropland into forest to the evolution regularity of rocky desertification, with the purpose of providing objective grounds for the further tackling and transformation of rocky desertification.

Keywords remote sensing      winter wheat planting area      information extracting      summary     
:  TP79  
  S157.1  
Issue Date: 21 October 2013
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
QUAN Wenting
WANG Zhao
Cite this article:   
QUAN Wenting,WANG Zhao. 20 year’s evolution features and influence factor analysis of rocky desertification in Guizhou[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(4): 133-137.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2013.04.21     OR     https://www.gtzyyg.com/EN/Y2013/V25/I4/133

[1] Wu X Q,Liu H M,Huang X L.Human driving force:Analysis of rocky desertification in Karst region in Guanling County,Guizhou Province[J].Chinese Geographical Science,2011,21(5):600-608.

[2] 刘春玲,童立强,聂洪峰,等.中国东部重要经济区带基础地质环境遥感调查与监测项目成果报告之二(石漠化遥感调查报告)[R].北京:国土资源部,2010. Liu C L,Tong L Q,Nie H F,et al.Basic geological environment investigation and inspection in China eastern economic zone(remote sensing investigation of rocky desertification)[R].Beijing:Ministry of Land and Resources,2010.

[3] Zhang P P,Hu Y M,Xiao D N,et al.Rocky desertification risk zone delineation in Karst plateau area:A case study in Puding County,Guizhou Province[J].Chinese Geographical Science,2010,20(1):84-90.

[4] Huang Q H,Cal Y L.Spatial pattern of Karst rock desertification in the middle of Guizhou Province,Southwestern China[J].Environmental Geology,2007,52(7):1325-1330.

[5] Li Y B,Shao J A,Hua Y,et al.The relations between land use and Karst rocky desertification in a typical Karst area,China[J].Environmental Geology,2009,57(3):621-627.

[6] 周常萍,童立强,雷蓉.贵州省土地石漠化形成与发展机理研究[J].云南农业大学,2005,20(2):269-273. Zhou C P,Tong L Q,Lei R.Study on the mechanism of the formation and development of the land rocky desertification in Guizhou Province[J].Journal of Yunnan Agricultural University,2005,20(2):269-273.

[7] 肖丹,熊康宁,兰安军,等.贵州省绥阳县喀斯特石漠化分布与岩性相关性分析[J].地球与环境,2006,34(2):77-81. Xiao D,Xiong K N,Lan A J,et al.Correlation analysis between Karst rocky desertification and lithology in Suiyang County,Guizhou Province[J].Earth and Environment,2006,34(2):77-81.

[8] 袁春,周常萍,童立强,等.贵州土地石漠化的形成原因及其治理对策[J].现代地质,2003,17(2):181-185. Yuan C,Chou C P,Tong L Q,et al.The causes and tackle countermeasures of land rocky desertification in Guizhou Province[J].Geo Science,2003,17(2):181-185.

[9] 李瑞玲,王世杰,周德全,等.贵州岩溶地区岩性与土地石漠化的相关分析[J].地理学报,2003,58(2):314-320. Li R L,Wang S J,Zhou D Q,et al.The correlation between rock desertification and lithology in Karst area of Guizhou[J].Acta Geographica Sinica,2003,58(2):314-320.

[10] 陈起伟,熊康宁,蓝安军.基于"3S"的贵州喀斯特石漠化现状及变化趋势分析[J].中国岩溶,2007,26(1):37-42. Chen Q W,Xiong K N,Lan A J.Analysis on Karst rocky desertification in Guizhou based on"3S"[J].Carsologica Sinica,2007,26(1):37-42.

[11] 钱铭杰,吴芳芳,童立强.基于RS-GIS的贵州省石漠化成因及治理研究[J].中国水土保持,2008(11):16-18. Qian M J,Wu F F,Tong L Q.The research of cauoriginse and treatment of rocky desertification in Guizhou Province based on RS-GIS[J].Soil and Water Consistent of China,2008(11):16-18.

[12] 李丽,童立强,李小慧.基于植被覆盖度的石漠化遥感信息提取方法研究[J].国土资源遥感,2010,22(2):59-62. Li L,Tong L Q,Li X H.The remote sensing information extraction method based on vegetation converage[J].Remote Sensing for Land and Resources,2010,22(2):59-62.

[1] LI Weiguang, HOU Meiting. A review of reconstruction methods for remote-sensing-based time series data of vegetation and some examples[J]. Remote Sensing for Natural Resources, 2022, 34(1): 1-9.
[2] DING Bo, LI Wei, HU Ke. Inversion of total suspended matter concentration in Maowei Sea and its estuary, Southwest China using contemporaneous optical data and GF SAR data[J]. Remote Sensing for Natural Resources, 2022, 34(1): 10-17.
[3] GAO Qi, WANG Yuzhen, FENG Chunhui, MA Ziqiang, LIU Weiyang, PENG Jie, JI Yanzhen. Remote sensing inversion of desert soil moisture based on improved spectral indices[J]. Remote Sensing for Natural Resources, 2022, 34(1): 142-150.
[4] ZHANG Qinrui, ZHAO Liangjun, LIN Guojun, WAN Honglin. Ecological environment assessment of three-river confluence in Yibin City using improved remote sensing ecological index[J]. Remote Sensing for Natural Resources, 2022, 34(1): 230-237.
[5] HE Peng, TONG Liqiang, GUO Zhaocheng, TU Jienan, WANG Genhou. A study on hidden risks of glacial lake outburst floods based on relief amplitude: A case study of eastern Shishapangma[J]. Remote Sensing for Natural Resources, 2022, 34(1): 257-264.
[6] LIU Wen, WANG Meng, SONG Ban, YU Tianbin, HUANG Xichao, JIANG Yu, SUN Yujiang. Surveys and chain structure study of potential hazards of ice avalanches based on optical remote sensing technology: A case study of southeast Tibet[J]. Remote Sensing for Natural Resources, 2022, 34(1): 265-276.
[7] 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.
[8] LYU Pin, XIONG Liyuan, XU Zhengqiang, ZHOU Xuecheng. FME-based method for attribute consistency checking of vector data of mines obtained from remote sensing monitoring[J]. Remote Sensing for Natural Resources, 2022, 34(1): 293-298.
[9] ZHANG Daming, ZHANG Xueyong, LI Lu, LIU Huayong. Remote sensing image segmentation based on Parzen window density estimation of super-pixels[J]. Remote Sensing for Natural Resources, 2022, 34(1): 53-60.
[10] 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.
[11] SONG Renbo, ZHU Yuxin, GUO Renjie, ZHAO Pengfei, ZHAO Kexin, ZHU Jie, CHEN Ying. A method for 3D modeling of urban buildings based on multi-source data integration[J]. Remote Sensing for Natural Resources, 2022, 34(1): 93-105.
[12] AI Lu, SUN Shuyi, LI Shuguang, MA Hongzhang. Research progress on the cooperative inversion of soil moisture using optical and SAR remote sensing[J]. Remote Sensing for Natural Resources, 2021, 33(4): 10-18.
[13] LI Teya, SONG Yan, YU Xinli, ZHOU Yuanxiu. Monthly production estimation model for steel companies based on inversion of satellite thermal infrared temperature[J]. Remote Sensing for Natural Resources, 2021, 33(4): 121-129.
[14] LIU Bailu, GUAN Lei. An improved method for thermal stress detection of coral bleaching in the South China Sea[J]. Remote Sensing for Natural Resources, 2021, 33(4): 136-142.
[15] WU Fang, JIN Dingjian, ZHANG Zonggui, JI Xinyang, LI Tianqi, GAO Yu. A preliminary study on land-sea integrated topographic surveying based on CZMIL bathymetric technique[J]. Remote Sensing for Natural Resources, 2021, 33(4): 173-180.
Viewed
Full text


Abstract

Cited

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