Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    1998, Vol. 10 Issue (2) : 61-61     DOI: 10.6046/gtzyyg.1998.02.10
Comment |
Download: PDF(73 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Keywords  Coastal wetland in Yancheng      Spartina alterniflora      RS      GIS      Landscape pattern     
Issue Date: 02 August 2011
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
LIU Chun-Yue
ZHANG Shu-Qing
JIANG Hong-Xing
WANG Hui
SUN Yan
QIN Lin-Jiang
Cite this article:   
LIU Chun-Yue,ZHANG Shu-Qing,JIANG Hong-Xing, et al. [J]. REMOTE SENSING FOR LAND & RESOURCES, 1998, 10(2): 61-61.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.1998.02.10     OR     https://www.gtzyyg.com/EN/Y1998/V10/I2/61
[1] SUN Yiming, ZHANG Baogang, WU Qizhong, LIU Aobo, GAO Chao, NIU Jing, HE Ping. Application of domestic low-cost micro-satellite images in urban bare land identification[J]. Remote Sensing for Natural Resources, 2022, 34(1): 189-197.
[2] SONG Qi, FENG Chunhui, MA Ziqiang, WANG Nan, JI Wenjun, PENG Jie. Simulation of land use change in oasis of arid areas based on Landsat images from 1990 to 2019[J]. Remote Sensing for Natural Resources, 2022, 34(1): 198-209.
[3] 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.
[4] WU Yijie, KONG Xuesong. Simulation and development mode suggestions of the spatial pattern of “ecology-agriculture-construction” land in Jiangsu Province[J]. Remote Sensing for Natural Resources, 2022, 34(1): 238-248.
[5] YAO Jinxi, ZHANG Zhi, ZHANG Kun. An analysis of the characteristics, causes, and trends of spatio-temporal changes in vegetation in the Nuomuhong alluvial fan based on Google Earth Engine[J]. Remote Sensing for Natural Resources, 2022, 34(1): 249-256.
[6] 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.
[7] LI Dong, TANG Cheng, ZOU Tao, HOU Xiyong. Detection and assessment of the physical state of offshore artificial reefs[J]. Remote Sensing for Natural Resources, 2022, 34(1): 27-33.
[8] 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.
[9] QU Haicheng, WAND Yaxuan, SHEN Lei. Hyperspectral super-resolution combining multi-receptive field features with spectral-spatial attention[J]. Remote Sensing for Natural Resources, 2022, 34(1): 43-52.
[10] ZANG Liri, YANG Shuwen, SHEN Shunfa, XUE Qing, QIN Xiaowei. A registration algorithm of images with special textures coupling a watershed with mathematical morphology[J]. Remote Sensing for Natural Resources, 2022, 34(1): 76-84.
[11] REN Chaofeng, PU Yuchi, ZHANG Fuqiang. A method for extracting match pairs of UAV images considering geospatial information[J]. Remote Sensing for Natural Resources, 2022, 34(1): 85-92.
[12] 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.
[13] CHEN Jie, ZHANG Lifu, ZHANG Linshan, ZHANG Hongming, TONG Qingxi. Research progress on online monitoring technologies of water quality parameters based on ultraviolet-visible spectra[J]. Remote Sensing for Natural Resources, 2021, 33(4): 1-9.
[14] 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.
[15] GUO Xiaozheng, YAO Yunjun, JIA Kun, ZHANG Xiaotong, ZHAO Xiang. Information extraction of Mars dunes based on U-Net[J]. Remote Sensing for Natural Resources, 2021, 33(4): 130-135.
Viewed
Full text


Abstract

Cited

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