地球信息科学学报 ›› 2016, Vol. 18 ›› Issue (8): 1141-1149.doi: 10.3724/SP.J.1047.2016.01141

• 遥感科学与应用技术 • 上一篇    

基于多时相中分辨率时间过程特征的江汉平原棉花种植面积变化监测

尤慧1(), 高华东1, 苏荣瑞1, 刘凯文1, 肖玮钰2   

  1. 1. 湖北省荆州农业气象试验站,荆州 434025
    2. 武汉区域气候中心,武汉 430074
  • 收稿日期:2015-10-28 修回日期:2016-01-31 出版日期:2016-08-10 发布日期:2016-08-10
  • 作者简介:

    作者简介:尤 慧(1987-),女,硕士生,主要从事农业遥感的研究。E-mail:youhuinuist@hotmail.com

  • 基金资助:
    湖北省气象局科技发展基金项目(2015Q08);荆州市气象局科技课题项目(JZ201402)

Monitoring the Changes of Cotton Plantation Area Based on the Multi-temporal Middle Resolution Features of Temporal Process in Jianghan Plain

YOU Hui1,*(), GAO Huadong1, SU Rongrui1, LIU Kaiwen1, XIAO Weiyu2   

  1. 1. Jingzhou Agriculture Meteorological Trial Station of Hubei Province, Jingzhou 434025, China
    2. Wuhan Regional Climate Center, Wuhan 430074, China
  • Received:2015-10-28 Revised:2016-01-31 Online:2016-08-10 Published:2016-08-10
  • Contact: YOU Hui E-mail:youhuinuist@hotmail.com

摘要:

棉花是中国重要的经济作物,快速、准确地提取棉花的种植面积和分布信息,对于优化棉花种植空间格局、科学指导棉花生产及提高其管理水平具有十分重要的意义。为了探讨多时相中高分辨率影像在棉花种植面积监测中的可行性,本文以江汉平原为研究区,根据棉花物候特征,选取2012年、2014年江汉平原棉花生长关键期的多时相HJ-1A/1B卫星数据,通过分析研究区棉花不同生育期的光谱特征和归一化植被指数(NDVI)时序变化特征,对分类影像进行阈值分割、掩膜处理,最后利用决策树算法提取研究区2012年、2014年棉花种植面积。通过计算混淆矩阵评价分类精度的方法和提取面积精度方法对棉花提取结果进行评价,总体精度达到95.96%,Kappa系数为0.93,以农业局统计数据为参考,2012年、2014年HJ数据提取的棉花种植面积精度分别达到了97.91%、91.27%。因此,在不受云和降水等因素的影响下,基于江汉平原区域关键时相HJ卫星CCD影像数据,可利用该方法进行棉花种植面积监测。

关键词: HJ卫星, 棉花, 种植面积, 江汉平原

Abstract:

Cotton is an important economic crop in our country, and also it is one of the main sources of income to the farmers of Jianghan plain in Hubei Province. Therefore, it is very important to obtain the information about cotton planting area, and accurately and timely get the spatial distribution for optimizing the cotton planting spatial pattern, scientifically guiding the cotton production and improving the management level. To explore the feasibility of middle and high resolution remote sensing images in monitoring the cotton plantation area, we took Jianghan plain as the study area in this paper. According to the growth period duration and the phonological characteristics of cotton, we selected the multi-temporal HJ-1A/1B images during the critical period of cotton growth of Jianghan plain in 2012 and 2014 as the data source. By analyzing the spectral property and normalized difference vegetation index (NDVI) time series variation during the cotton growing period in the study area, we use the threshold configurations and the mask processes to build the decision trees for the estimation of cotton planting area. Finally, the planting areas of cotton were extracted using the decision trees method in 2012 and 2014. With respect to the confusion matrix calculations, the overall accuracy of the study area reached 95.96% and the Kappa coefficient was 0.93. Then, by taking the statistics data provided by the Agricultural Bureau as a reference, the accuracies of area extraction results from HJ data are 97.91% and 91.27% in 2012 and 2014, respectively. Results indicated that this method can accurately reflect the distribution of the cotton area in Jianghan plain. In addition, it is concluded that the cotton planting area can be accurately extracted as long as we have the HJ satellite CCD data for the critical period of cotton growth and the image data is not affected by factors such as clouds and precipitation.

Key words: HJ satellite, cotton, planting area, Jianghan plain