研究报告

Estimating Rice Yield by HJ-1A Satellite Images

Expand
  • 1Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China; 2College of Agriculture, Anhui Agricultural University, Hefei 230036, China

Received date: 1900-01-01

  Revised date: 1900-01-01

  Online published: 2010-07-10

Abstract

With Xuyi County, Jinhu County and Hongze County in Jiangsu Province, China as examples, monitoring and forecasting of rice production were carried out by using HJ1A satellite remote sensing images. The handhold GPS machines were used to measure the geographical position and some other information of these samples such as areas shapes. The GPS data and the interpretation mark were used to correct HJ1 image, assist humancomputer interactive interpretation, and other operations. The test data had been participated in the whole classification process. The accuracy of interpreted information on rice planting area was more than 90%. By using the leaf area index got from the normalized difference vegetation index inversion, and the biomass got from the ratio vegetation index inversion, combined with the rice yield estimation model, the rice yield was estimated. Further the thematic map of rice production classification was made based on the rice yield data. According to the comparison results between measured and fitted values of the yields and areas of sample sites, the accuracy of the yield estimation was more than 85%. The results suggest that HJ1A/B images could basically meet the demand of rice growth monitoring and yield forecasting, and could be widely applied to rice production monitoring.

Cite this article

LI Wei-guo, LI Hua, . Estimating Rice Yield by HJ-1A Satellite Images [J]. Chinese Journal OF Rice Science, 2010 , 24(4) : 385 -390 . DOI: 10.3969/j.issn.1001-7216.2010.04.009

References


[1]夏德深,李华. 国外灾害遥感应用研究现状. 国土资源遥感, 1996, 29(3): 1-8.
[2]Lobell D B, Asner G P, Ortiz-Monasterio J I, et al. Remote sensing of regional crop production in the Yaqui Valley, Mexico: Estimates and uncertainties. Agric, Ecosyst & Environ, 2003, 94: 205-220.
[3]陈沈斌, 孙九林. 建立我国主要农作物卫星遥感估产运行系统的主要技术环节及解决途径. 自然资源学报, 1997, 12(4): 363-369.
[4]齐腊, 赵春江, 李存军, 等. 基于多时相中巴资源卫星影像的冬小麦分类精度. 应用生态学报, 2008, 19(10): 2201-2208.
[5]秦元伟, 赵庚星, 姜曙千, 等. 基于中高分辨率卫星遥感数据的县域冬小麦估产. 农业工程学报, 2009, 25(7): 118-123.
[6]杨武德, 宋艳暾, 宋晓彦, 等. 基于3S和实测相结合的冬小麦估产研究. 农业工程学报, 2009, 25(2): 131-135.
[7]高亮之, 金之庆, 黄耀, 等. 水稻栽培计算机模拟优化决策系统(RCSODS). 北京: 中国农业科技出版社, 1992: 29-33.
[8]李卫国, 王纪华, 赵春江. 基于定量遥感反演与生长模型耦合的水稻产量估测研究. 农业工程学报, 2008, 24: 128-131.
[9]李卫国. 基于TM 遥感信息和产量形成过程的水稻估产模型. 江苏农业科学, 2007(4): 12-13.
[10]程乾. 基于MOD13产品水稻遥感估产模型研究. 农业工程学报, 2006, 22(3): 79-83.
[11]刘良云, 王纪华, 黄文江,等. 利用新型光谱指数改善冬小麦估产精度. 农业工程学报, 2004, 20(1): 172-175.
[12]唐延林, 王纪华, 黄敬峰, 等. 利用水稻成熟期冠层高光谱数据进行估产研究. 作物学报, 2004, 30(8): 780-785.
[13]Chen J Y, Pan D L, Mao Z H. Optimum segmentation of simple objects in high-resolution remote sensing imagery in coastal areas . Sci China: Series D, 2006, 49(11): 1195-1203.
[14]张浩, 姚旭国, 张小斌, 等. 基于多光谱图像的水稻叶片叶绿素和籽粒氮素含量检测研究. 中国水稻科学, 2008, 22(5): 555-558.
Outlines

/

Tel: 0571-63370278 E-mail: cjrs@263.net
Supported by Beijing Magtech Co., Ltd.