地球信息科学学报 ›› 2012, Vol. 14 ›› Issue (3): 382-388.doi: 10.3724/SP.J.1047.2012.00382

• 遥感技术与应用 • 上一篇    下一篇

HJ卫星图像水稻种植面积的识别分析

魏新彩1, 王新生1,2, 刘海1, 徐静1   

  1. 1. 湖北大学资源环境学院,武汉 430062;
    2. 农业部遥感应用中心武汉分中心,武汉 430062
  • 收稿日期:2012-02-15 修回日期:2012-05-03 出版日期:2012-06-25 发布日期:2012-06-25
  • 通讯作者: 王新生(1965-),男,安徽太湖人,博士,教授,主要从事地理信息系统、农业遥感和LUCC研究。 E-mail:wxs818@hubu.edu.cn E-mail:wxs818@hubu.edu.cn
  • 作者简介:魏新彩(1988-),女,湖北襄阳人,硕士研究生,主要从事水稻遥感方面的研究。E-mail:huangwenbee@163.com
  • 基金资助:

    武汉市科技攻关计划项目(200910321099);湖北省教育厅科学技术研究项目(D20091001);国家自然科学基金项目(41071240)。

Extraction of Paddy Rice Coverage Based on the HJ Satellite Data

WEI Xincai1, WANG Xinsheng1,2, LIU Hai1, XU Jing1   

  1. 1. Faculty of Resources and Environment, Hubei University, Wuhan 430062, China;
    2. Wuhan Branch, Remote Sensing Application Center, Ministry of Agriculture, Wuhan 430062, China
  • Received:2012-02-15 Revised:2012-05-03 Online:2012-06-25 Published:2012-06-25

摘要:

HJ-1A/1B卫星具有较高时空分辨率,是提取水稻等农作物种植面积的潜力数据源。本文以江汉平原腹地的监利县及周边相邻区域为研究区,根据水稻物候历,选取样区水稻生长关键期的多时相HJ-1A/1B卫星数据,利用水稻移栽期的水分信息和生长期的归一化植被指数(NDVI)变化信息,结合陆表水系数(LSWI)、短波红外波段的反射率(RIRS-B2)、差归一化植被指数(DNDVI),构建了HJ卫星数据的水稻种植面积识别方法,提取了研究区2009-2011年水稻种植面积,得到面积精度和样本点精度均不小于90%,Kappa值不小于0.80的结果。

关键词: 遥感, 种植面积, 水稻, HJ卫星

Abstract:

HJ-1A/1B satellite has high spatial and temporal resolution, so it is a potential data source for extraction of the planting area of rice and other crops. This paper we took Jianli County and its adjacent area, located on the hinterland of Jianghan Plain, as the study area. According to the growth period duration of rice, we selected multi-temporal HJ-1A/1B images in critical period of rice growth including transplanting stage and heading and seeding stage. Because land surface water index (LSWI) is sensitive to the increased surface moisture, so we use LSWI to distinguish cotton plants and construction land in paddy rices transplanting period. There are large differences between normalized difference vegetation index (NDVI) of water and plant, then we choose NDVI in paddy rices heading and seeding stage to distinguish moisture content. The time variation of NDVI of forest with paddy rice and lotus root is different, and paddy rices shortwave infrared reflectance (RIRS-B2) is smaller than lotus roots, so we use difference normalized vegetation index (DNDVI) and RIRS-B2 to differentiate paddy rice from forest and lotus root. We obtained a method to extract the planting area of rice based on the HJ satellite data. Then taking SPOT images as reference, the area accuracy and sample point accuracy are not less than 90%, and Kappa is not less than 0.80. So this proposed method can extract the rice planting area exactly.

Key words: planting area, HJ satellite, remote sensing, paddy rice