Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    1992, Vol. 4 Issue (1) : 40-45     DOI: 10.6046/gtzyyg.1992.01.07
Applied Research |
THE RESEARCH OF AERIAL REMOTE SENSING OF INDUSTRIAL“THREE POLLUTANTS” IN BAIYIN CITY
Yang Fachang
The station of the remnote sensing geology of the geology bureau of Gansu
Download: PDF(1135 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

By interpretation of infrared aerial color photograph on the scale of 1:8000, industrial "three pollutants" in Baiyin city are divided into three big classification and twelve sub classification. Three sorts of special drawing of the source of atmospherics pollution. solid pollutant and industrial sewage (distribution have been worked out. and Agreat mass of data have been given. All these provide a great amount of foundetional information for enrironmenttal protection and urban constrtiction. It shows remote sensing that is a high-speed. economic and accurate method in investigating industrial"three pollutants" in industrialore area.

Keywords Object-oriented method      ETM image      Wetland      Information extraction     
Issue Date: 02 August 2011
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
SUN Yong-Jun
TONG Qing-Xi
QIN Qi-Ming
LI Feng-Quan
PAN Hong-Mei
YE Wei
ZHU Li-Dong
CAO Zhi-Chun
Cite this article:   
SUN Yong-Jun,TONG Qing-Xi,QIN Qi-Ming, et al. THE RESEARCH OF AERIAL REMOTE SENSING OF INDUSTRIAL“THREE POLLUTANTS” IN BAIYIN CITY[J]. REMOTE SENSING FOR LAND & RESOURCES, 1992, 4(1): 40-45.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.1992.01.07     OR     https://www.gtzyyg.com/EN/Y1992/V4/I1/40
[1] HE Chenlinqiu, CHENG Bo, CHEN Jinfen, ZHANG Xiaoping. Information extraction methods of coastal wetland based on GF-3 fully polarimetric SAR data[J]. Remote Sensing for Natural Resources, 2021, 33(4): 105-110.
[2] WEI Yingjuan, LIU Huan. Remote sensing-based mineralized alteration information extraction and prospecting prediction of the Beiya gold deposit, Yunnan Province[J]. Remote Sensing for Natural Resources, 2021, 33(3): 156-163.
[3] MOU Xiaoli, LI He, HUANG Chong, LIU Qingsheng, LIU Gaohuan. Application progress of Google Earth Engine in land use and land cover remote sensing information extraction[J]. Remote Sensing for Land & Resources, 2021, 33(2): 1-10.
[4] 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.
[5] XIA Yan, HUANG Liang, CHEN Pengdi. Tobacco fine extraction from UAV image based on fuzzy-superpixel segmentation algorithm[J]. Remote Sensing for Land & Resources, 2021, 33(1): 115-122.
[6] WANG Lin, XIE Hongbo, WEN Guangchao, YANG Yunhang. A study on water information extraction method of cyanobacteria lake based on Landsat8[J]. Remote Sensing for Land & Resources, 2020, 32(4): 130-136.
[7] Chang LIU, Kang YANG, Liang CHENG, Manchun LI, Ziyan GUO. Comparison of Landsat8 impervious surface extraction methods[J]. Remote Sensing for Land & Resources, 2019, 31(3): 148-156.
[8] Zhan YIN, Lijun ZHANG, Jianliang DUAN, Pei ZHANG. Improvement and application of forced invariance vegetation suppression in southern vegetation area[J]. Remote Sensing for Land & Resources, 2019, 31(2): 82-88.
[9] Jinxia LYU, Weiguo JIANG, Wenjie WANG, Yinghui LIU, Yue DENG, Xiaoya WANG. Wetland landscape evolution and its relation to human disturbance in Xiong’an New Area based on the moving window method[J]. Remote Sensing for Land & Resources, 2019, 31(2): 140-148.
[10] Yueru WANG, Pengpeng HAN, Shujing GUAN, Yu HAN, Lin YI, Tinggang ZHOU, Jinsong CHEN. Information extraction of Dracaena sanderiana planting area based on Landsat8 OLI data[J]. Remote Sensing for Land & Resources, 2019, 31(1): 133-140.
[11] Chao MA, Fei YANG, Xuecheng WANG. Extracting tea plantations in southern hilly and mountainous region based on mesoscale spectrum and temporal phenological features[J]. Remote Sensing for Land & Resources, 2019, 31(1): 141-148.
[12] Yong WANG, Yinling ZHANG, Shucheng YOU, Zhongwu WANG, Hai WEI, Yang LI. Checkup of land consolidation project using ZY1-02C data[J]. Remote Sensing for Land & Resources, 2018, 30(1): 144-149.
[13] DING Yuxue, CHU Yu, XUE Guangyin. Using domestic satellite data to carry out wetland survey:Exemplified by Heilongjiang Province[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(s1): 151-154.
[14] WEI Benzan, FU Lihua, FAN Fang, ZHANG Ce, JIE Wenhui, DONG Shuangfa. Remote sensing monitoring of wetlands dynamics in the Manas River basin from 1998 to 2015[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(s1): 90-94.
[15] XUE Qing, WU Wei, LI Mingsong, DONG Shuangfa, ZHANG Xinyi, SHI Haigang. Application of GF-1 satellite data to remote sensing monitoring of the mine[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(s1): 67-72.
Viewed
Full text


Abstract

Cited

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