Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    1993, Vol. 5 Issue (2) : 17-21     DOI: 10.6046/gtzyyg.1993.02.06
Applied Research |
APPLICATION OF AERIAL REMOTE SENSING TO SURVEYING IRRIGATED FIELDS AND DYNAMIC MONITORING SALINIZED SOIL IN XINDING BASIN
Qiao Yu Liang
Reeeach Institute of Remote Sensing Application in Agriculture of Shanxi Province
Download: PDF(359 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

According to the interpretation principle of the color infrared aerial photograph, the interpretive methods and marks of the first, second and third grade were used for surveying irrigated fields. And the growth-decline of salinized boils was analysed using aerial Photograph taken during 1980 to 1987, in Dinxiang area-one county of xinding basin.

Keywords False topographic phenomenon      Remote sensing image      DEM      IHS transformation     
Issue Date: 02 August 2011
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
ZHOU Ai-Xia
GAO Lian-Feng
ZUO Jian-Jun
LIN Song-Hui
KONG Qing-Feng
WEI Guo-Hua
WEI Hong-Quan
LI Jiu-Sheng
Cite this article:   
ZHOU Ai-Xia,GAO Lian-Feng,ZUO Jian-Jun, et al. APPLICATION OF AERIAL REMOTE SENSING TO SURVEYING IRRIGATED FIELDS AND DYNAMIC MONITORING SALINIZED SOIL IN XINDING BASIN[J]. REMOTE SENSING FOR LAND & RESOURCES, 1993, 5(2): 17-21.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.1993.02.06     OR     https://www.gtzyyg.com/EN/Y1993/V5/I2/17
[1] JIANG Na, CHEN Chao, HAN Haifeng. An optimization method of DEM resolution for land type statistical model of coastal zones[J]. Remote Sensing for Natural Resources, 2022, 34(1): 34-42.
[2] 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.
[3] 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.
[4] 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.
[5] LIU Zhizhong, SONG Yingxu, YE Runqing. An analysis of rainstorm-induced landslides in northeast Chongqing on August 31, 2014 based on interpretation of remote sensing images[J]. Remote Sensing for Natural Resources, 2021, 33(4): 192-199.
[6] ZHANG Chengye, XING Jianghe, LI Jun, SANG Xiao. Recognition of the spatial scopes of tailing ponds based on U-Net and GF-6 images[J]. Remote Sensing for Natural Resources, 2021, 33(4): 252-257.
[7] 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.
[8] 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.
[9] LIU Wanjun, GAO Jiankang, QU Haicheng, JIANG Wentao. Ship detection based on multi-scale feature enhancement of remote sensing images[J]. Remote Sensing for Natural Resources, 2021, 33(3): 97-106.
[10] SANG Xiao, ZHANG Chengye, LI Jun, ZHU Shoujie, XING Jianghe, WANG Jinyang, WANG Xingjuan, LI Jiayao, YANG Ying. Application of intensity analysis theory in the land use change in Yijin Holo Banner under the background of coal mining[J]. Remote Sensing for Natural Resources, 2021, 33(3): 148-155.
[11] LU Qi, QIN Jun, YAO Xuedong, WU Yanlan, ZHU Haochen. Buildings extraction of GF-2 remote sensing image based on multi-layer perception network[J]. Remote Sensing for Land & Resources, 2021, 33(2): 75-84.
[12] HU Suliyang, LI Hui, GU Yansheng, HUANG Xianyu, ZHANG Zhiqi, WANG Yingchun. An analysis of land use changes and driving forces of Dajiuhu wetland in Shennongjia based on high resolution remote sensing images: Constraints from the multi-source and long-term remote sensing information[J]. Remote Sensing for Land & Resources, 2021, 33(1): 221-230.
[13] LIU Zhao, ZHAO Tong, LIAO Feifan, LI Shuai, LI Haiyang. Research and comparative analysis on urban built-up area extraction methods from high-resolution remote sensing image based on semantic segmentation network[J]. Remote Sensing for Land & Resources, 2021, 33(1): 45-53.
[14] WANG Xiaolong, YAN Haowen, ZHOU Liang, ZHANG Liming, DANG Xuewei. Using SVM classify Landsat image to analyze the spatial and temporal characteristics of main urban expansion analysis in Democratic People’s Republic of Korea[J]. Remote Sensing for Land & Resources, 2020, 32(4): 163-171.
[15] WANG Xiaobing. Denoising algorithm based on the fusion of lifting wavelet thresholding and multidirectional edge detection of remote sensing image of mining area[J]. Remote Sensing for Land & Resources, 2020, 32(4): 46-52.
Viewed
Full text


Abstract

Cited

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