APPLICATION OF REMOTE SENSING TO SANDSTONE FOREST LANDSCAPE INVESTIGATION IN ZHANGJIAJIE

doi:10.6046/gtzyyg.1993.03.04

Download: PDF(870 KB)
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Remote sensing technique was applied to the investigation of the sands- tone forest landscape in Zhangjiajie. It is newly confirmed that NNEtrend fold repeaded on the NEEtrend fold, and 1031 lineaments were first interpreted. Anew knowledge was suggested that this area was undergone more than twice fold structural movements. The relationship between the formation of sandstone forest landscape and geological tectonic was ascertained.It’s mechanism of formation was explored. It is considered that Devonian system (upper and middle series) huge thick quarty sandstone is the material foundation for forming sandstone forest landscape) the particular tectonic position favoured the formation of sandstone pillar steady; several times tectonic processes producing high angle fracture favoured sandstone forest landscape modelling; the neoid crustal uprising is the driving power for the formation of the sandstone forest landscape.

Keywords Principal components analysis Normalized difference vegetation index Band combinations Supervised classification Neighborhood analysis Maximum likelihood

Issue Date: 02 August 2011

	Service

	E-mail this article
	E-mail Alert
	RSS
	Articles by authors

	DENG Shu-Bin
	WU Hong-Gan
	JIANG Tao
	SUO Xiao-Dong

Cite this article:

DENG Shu-Bin,WU Hong-Gan,JIANG Tao, et al. APPLICATION OF REMOTE SENSING TO SANDSTONE FOREST LANDSCAPE INVESTIGATION IN ZHANGJIAJIE[J]. REMOTE SENSING FOR LAND & RESOURCES, 1993, 5(3): 15-18.

URL:

https://www.gtzyyg.com/EN/10.6046/gtzyyg.1993.03.04 OR https://www.gtzyyg.com/EN/Y1993/V5/I3/15

[1]	Zhen CHEN, Yunshi ZHANG, Yuanyu ZHANG, Lingling SANG. A study of remote sensing monitoring methods for the high standard farmland[J]. Remote Sensing for Land & Resources, 2019, 31(2): 125-130.
[2]	Zhaohua LIU, Chunyan ZHANG. Dynamic monitoring and driving factors analysis of urban expansion in Kaifeng[J]. Remote Sensing for Land & Resources, 2018, 30(4): 193-199.
[3]	Jianhui XU, Yi ZHAO, Minghong XIAO, Kaiwen ZHONG, Huihua RUAN. Relationship of air temperature to NDVI and NDBI in Guangzhou City using spatial autoregressive model[J]. Remote Sensing for Land & Resources, 2018, 30(2): 186-194.
[4]	Ting WANG, Jun PAN, Lijun JIANG, Lixin XING, Yifan YU, Pengju WANG. Topographic variable analysis and lithologic classification based on DEM[J]. Remote Sensing for Land & Resources, 2018, 30(2): 231-237.
[5]	LIANG Shouzhen, SUI Xueyan, YAO Huimin, WANG Meng, HOU Xuehui, CHEN Jinsong, MA Wandong. An analysis of influence of non-photosynthetic vegetation of deciduous broad-leaved forest on canopy FPAR: A method based on layered simulation[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(2): 29-36.
[6]	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.
[7]	WANG Kai, ZHANG Jiahua. Extraction of rape seed cropping distribution information in Hubei Province based on MODIS images[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(3): 65-70.
[8]	CHEN Mengjie, WU Hong, LIU Chao, ZHOU Minyue, LU Dingge, GUO Wei. Remote sensing inversion of dissolution rate of limestone bedrock surface based on ecological parameters in Karst areas[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(3): 71-76.
[9]	LIU Yadi, WANG Xiaoqin, JIANG Hong. Estimation of vegetation coverage based on topography-adjusted vegetation index (TAVI) in Changting County, Fujian Province[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(1): 164-171.
[10]	LI Cheng, CHEN Renxi, WANG Qiuyan. Improvement of the automatic recognition method based on vegetation visual characteristics[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(2): 75-80.
[11]	LI Weina, YANG Jiansheng, LI Xiao, ZHANG Jilong, LI Shiwei. Extraction of urban impervious surface information from TM image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(1): 66-70.
[12]	DANG Qing, YANG Wu-nian. Dynamic Supervision and Reason Analysis of Vegetation Coverage Changes of Chengdu in the Past 20 years[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(4): 121-125.
[13]	SONG Qi-Fan, WANG Shao-Jun, ZHANG Zhi, WANG Peng, AN Ping. A Water Information Extraction Method Based on WorldView II Remote Sensing Image in Tungsten Ore Districts: A Case Study of of Dayu County in Jiangxi Province[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(2): 33-37.
[14]	LI Na, ZHAO Hui-Jie. An Improved Independent Component Analysis Method for Unsupervised Classification of Hyperspectral Data [J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(2): 70-74.
[15]	DENG Rui, HUANG Jing-Feng. The Monitoring of Landslide and Debris Flow Caused by Typhoon Morakot Based on HJ-1 Images[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(1): 106-109.