基于SPOT遥感数据的甘蔗叶面积指数反演和产量估算  

Estimation of LAI and Yield of Sugarcane Based on SPOT Remote Sensing Data

作　　者：何亚娟[1,2] 潘学标[1] 裴志远[2] 马尚杰[2] Heather McNirn Jiali Shang 

机构地区：[1]中国农业大学资源与环境学院,北京100091 [2]农业部规划设计研究院,北京100125 [3]加拿大农业部谷物和油料研究中心

出　　处：《农业机械学报》2013年第5期226-231,共6页Transactions of the Chinese Society for Agricultural Machinery

基　　金：农业部农业信息预警财政专项资助项目(2130111);高分辨率对地观测重大专项农业遥感监测与评价子系统先期攻关项目(E0201/1112-1)

摘　　要：利用SPOT遥感数据进行甘蔗叶面积指数LAI反演,建立最佳NDVI-LAI反演模型,同时结合不同生育期甘蔗叶面积指数的时序变化规律,建立各生育期甘蔗叶面积指数LAI与产量的相关关系,得到甘蔗叶面积指数LAI-产量最佳估产模型。在验证甘蔗叶面积指数LAI的基础上,利用遥感反演的甘蔗叶面积指数LAI进行甘蔗单产估算。结果表明:甘蔗叶面积指数LAI与NDVI之间存在显著的正相关关系,全生育期二者的相关性最高,以二次函数模型拟合效果最佳,决定系数R2为0.842 9。将遥感数据反演得到的平均叶面积指数LAI数据代入甘蔗叶面积LAI-产量模型得到全县平均单产,与统计数据相比,相对误差仅为2.6%。说明该模型具有较好的估产效果,可以为甘蔗区域估产提供重要参考。By using retrieved LAI from SPOT remote sensing data, the relationship between leaf area index and the normalized difference vegetation index was studied. The regular pattern of LAI in deference growth stages was combined to estimate models between LAI from remote sensing data and yield of sugarcane. After optimizing the models, the best model for sugarcane yield estimation was determined. The results showed that a strong positive correlation between LAI and NDVI was obtained. A quadratic function model was the best regression model for the whole growth stage （R^2 = 0. 842 9）. Statistical yield were compared with yield simulated with LAI. The relative error was 2.6%. The estimation of sugarcane yield estimates could be improved by combining remotely sensed data. This study provided the reference for estimating the regional yield of sugarcane in China.

关 键 词：甘蔗 SPOT遥感数据 归一化植被指数 叶面积指数 产量 

分 类 号：S127[农业科学—农业基础科学]