摘要
水资源一直是制约我国西北干旱区农业发展的关键因素。以新疆渭库绿洲为研究区域,选取41个土壤含水率与干旱区绿洲植被实测高光谱样本,以植被指数为桥梁,采用支持向量机回归(SVR)方法,建立干旱区绿洲土壤含水率与植被指数之间的拟合方程模型,并与多元回归(MLSR)、偏最小二乘回归(PLS)2种模型进行对比。实验结果表明:不同模型的精度各异,拟合效果由优到劣为:改进的SVR模型、PLS模型、MLSR模型,其中基于干旱区绿洲实测的植被光谱数据改进的SVR模型对土壤含水率具有较好的拟合效果,通过最优参数的定值与最优测试集的抽取,R2高达0.891 6,RMSE仅为2.004,在干旱区绿洲的土壤含水率拟合中获得比较高的预测精度。而MLSR模型与PLS模型,R^2分别为0.630 0、0.654 9,RMSE分别为3.001与2.749。研究结果表明,因地制宜开展合理的土壤含水率反演模型规则制定是提高干旱区绿洲土壤浅层含水率监测精度的有效手段,也可为干旱区农业作物生长提供更精准的数据积累。
Water resources have become a key factor for restricting the social,economic and agricultural development of arid area in Northwest China. In recent years,agriculture in arid oasis has developed rapidly,and human activities have seriously affected balance on the regional soil moisture,resulting in a large area of salinization. Therefore,the monitoring of soil moisture is of great practical significance to the development of oasis agriculture and economy. Taking the oasis of Weiku in Xinjiang as the study area,totally 41 soil moisture samples and hyperspectral data of the oasis vegetation in arid area were collected,and the vegetation index was taken as bridge. Multiple regression（ MLSR）,partial least squares（ PLS）regression and support vector machine regression（ SVR） were used to establish the inversion model of soil water content in oasis,respectively,the regression models were tested respectively. The experimental results showed that the accuracy of different models was different. Through the optimization of parameters and extraction of optimal test set,the fitting effect from good to bad was improved SVR model,PLS model and MLSR model,which were based on the vegetation The improved SVR model had a good fitting effect,R^2 was 0. 891 6,RMSE was only 2. 004,the analysis accuracy in the oasis of arid area reached the practical prediction accuracy. The R^2 values of MLSR model and PLS model were 0. 630 0 and 0. 654 9,and RMSE were 3. 001 and 2. 749,respectively. The results showed that it was an effective method to improve the monitoring accuracy of shallow soil water content in oasis,and it can also provide more data for monitoring soil moisture in arid area.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2017年第12期229-236,共8页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家自然科学基金项目(U1303381
41261090)
自治区重点实验室专项基金项目(2016D03001)
自治区科技支疆项目(201591101)
教育部促进与美大地区科研合作与高层次人才培养项目
新疆大学优秀博士生科技创新项目(XJUBSCX-2016014)
关键词
高光谱
植被指数
土壤含水率
改进SVR
hyperspectra
vegetation index
soil water content
improved SVR
