Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2000, Vol. 12 Issue (1) : 24-27,33     DOI: 10.6046/gtzyyg.2000.01.05
Technology Application |
RAPID UPDATING OF RICE MAP FOR LOCAL GOVERNMENT USING SAR DATA AND GIS IN ZENGCHENG COUNTY, GUANGDONG PROVINCE, CHINA
Tan Bingxiang, Li Zengyuan
Institute of Forest Resources Information, CAF, Beijing, 100091
Download: PDF(915 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

For rice growing areas in the tropics, experience shows that SAR Satellite sensor can provide the desired information due to acquiring images independently of cloud coverage or daylight conditions. The current study testifies the potential of SARdata for rice mapping. This paper discusses the methodology and result of using SARdata and GISin updating rice map for the local government in Zengcheng County of Guangzhou province, South of China. The methodology was carefully laid out and was determined to be easily implemented on a semi-automatic basis to facilitate frequent updating of rice map.

Keywords HJ-1      CCD      6S      Atmospheric correction     
Issue Date: 02 August 2011
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
DU Xin
CHEN Xue-Yang
MENG Ji-Hua
ZHANG Fei-Fei
ZHANG Miao
WU Bing-Fang
ZHOU Si-chun
LIU Xiao-hui
GU Jiang-bo
LV Shao-hui
WANG Zi-yun
WU Li-rong
Cite this article:   
DU Xin,CHEN Xue-Yang,MENG Ji-Hua, et al. RAPID UPDATING OF RICE MAP FOR LOCAL GOVERNMENT USING SAR DATA AND GIS IN ZENGCHENG COUNTY, GUANGDONG PROVINCE, CHINA[J]. REMOTE SENSING FOR LAND & RESOURCES, 2000, 12(1): 24-27,33.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2000.01.05     OR     https://www.gtzyyg.com/EN/Y2000/V12/I1/24

[1] Aschbacher J, Pongsrihadulchai A. ERS SAR Datafor Rice Crop Mappingand Monitoring, Proceedingsofthe Second ERS Application Workshop, London, UK,1995,21~24

[2] Yoshida M, Barbero F B. Rapid Updatingof Land-use Mapsfor Local Governmentin Japanthrough GISand Remote Sengsing, ASIAN-ACIFIC Remote Sensingand GIS Journal, 1997,9(2):75~84

[3] Kurosu T. Rice Crop Mappingand Monitoringusing ERS-1 Data Basedon Experimentand Modeling Results, IEEE IGARS, 1997,35(1):41~53

[4] 刘浩等.多时相Radarsat数据在广东肇庆地区稻田分类中的应用.国土资源遥感,1997,(4):1~6

[1] HE Haiying, CHEN Caifen, CHEN Fulong, TANG Panpan. Deformation monitoring along the landscape corridor of Zhangjiakou Ming Great Wall using Sentinel-1 SBAS-InSAR approach[J]. Remote Sensing for Land & Resources, 2021, 33(1): 205-213.
[2] Zhenyu SHEN, Xiaohong GAO, Min TANG. Comparison and accuracy verification for atmospheric correction of SPOT6 image in high altitude complex terrain area[J]. Remote Sensing for Land & Resources, 2020, 32(1): 81-89.
[3] Dongya CHENG, Xudong LI. Comparison of change characteristics of NDVI in mountain basin before and after atmospheric correction[J]. Remote Sensing for Land & Resources, 2020, 32(1): 90-97.
[4] Ling CHEN, Li CHEN, Wei LI, Jianyu LIU. Atmospheric correction of Worldview3 image based on FLAASH model[J]. Remote Sensing for Land & Resources, 2019, 31(4): 26-31.
[5] Xianlei FAN, Hongbo YAN, Ying QU. Comparison and validation of the methods for estimating surface albedo from HJ-1 A/B CCD data[J]. Remote Sensing for Land & Resources, 2019, 31(3): 123-131.
[6] Piyuan YI, Hanbo LI, Peng TONG, Yingjun ZHAO, Chuan ZHANG, Feng TIAN, Yongfei CHE, Wenhuan WU. Atmospheric radiation correction of airborne hyperspectral image by adding elevation factor[J]. Remote Sensing for Land & Resources, 2019, 31(2): 66-72.
[7] Bin YANG, Dan LI, Guisheng GAO, Cai CHEN, Lei WANG. Processing analysis of Sentinel-2A data and application to arid valleys extraction[J]. Remote Sensing for Land & Resources, 2018, 30(3): 128-135.
[8] Jiaojiao DIAO, Xinye GONG, Mingshi LI. A comprehensive change detection method for updating land cover data base[J]. Remote Sensing for Land & Resources, 2018, 30(1): 157-165.
[9] ZHAO Feifei, BAO Nisha, WU Lixin, SUN Rui. Retrieving land surface temperature and soil moisture from HJ-1B data: A case study of Yimin open-cast coal mine region in Hulunbeier grassland[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(3): 1-9.
[10] KONG Jinling, YANG Jing, SUN Xiaoming, YANG Shu, LIU Futian, DU Dong. Atmospheric correction and suspended sediment concentration retrieval based on multi-spectral remote sensing images: A case study of Caofeidian offshore area[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 130-137.
[11] 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.
[12] ZHANG Yue, XIAO Yu, CHANG Jingjing, LIU Jian, WANG Yaqiong, HE Chunyan, HE Bing. Effects of atmospheric correction on extracting cyanobacteria bloom information based on remote sensing indices[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(3): 7-12.
[13] DIAN Yuanyong, FANG Shenghui, XU Yongrong. An atmospheric correction algorithm for hyperspectral imagery with collaborative retrieval of aerosol optical thickness and water vapor content[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(2): 22-28.
[14] GAI Yingying, ZHOU Bin, SUN Yuanfang, ZHOU Yan. Study of extraction methods for ocean surface oil spill using HJ-CCD data[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(2): 99-104.
[15] XIONG Pan, ZHU Li, GU Xingfa, ZHAO Limin, YU Tao, MENG Qingyan, LI Jiaguo, ZHANG Feng. Sea water temperature retrieval model for Daya Bay based on HJ-1B thermal infrared remote sensing data and its application[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(1): 132-138.
Viewed
Full text


Abstract

Cited

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