摘要
为提高卫星遥感对裸土期土壤盐渍化的监测精度,以河套灌区沙壕渠灌域为研究区域,利用无人机多光谱遥感和GF-1卫星遥感分别获取图像数据,并同步采集土壤表层含盐量;将实测含盐量与无人机和GF-1卫星两种数据的光谱因子进行相关性分析,引入多元线性回归模型(Multivariable linear regression,MLR)、逐步回归模型(Stepwise regression,SR)和岭回归模型(Ridge regression,RR),分别构建盐渍化监测模型;采用改进的TsHARP尺度转换方法,将无人机数据建立的趋势面应用到GF-1卫星尺度上,经过转换残差校正,对升尺度结果进行定性和定量分析。结果表明:在两种遥感数据的光谱波段和盐分指数中,蓝波段B1、近红外波段B5、盐分指数SI、盐分指数S5和改进的光谱指数NDVI-S1与表层土壤盐分的相关性较好,相关系数均在0.3以上;在3种回归模型中,利用无人机多光谱影像数据和GF-1多光谱影像数据反演表层土壤含盐量的最优模型分别是SRU模型和MLRS模型;升尺度后土壤含盐量的反演精度高于直接采用卫星遥感数据反演的精度。本研究可为裸土期土壤盐渍化的大范围快速精准监测提供参考。
Improving the accuracy of salinization monitoring by satellite remote sensing plays a crucial role in salinization.A synthesized model for assessment of regional soil salinity was established based on UAV and GF-1 satellite remote sensing data.Applying the trend surface of the UAV data creation to the GF-1 satellite scale,through the improved TsHARP scale conversion method,after the conversion residual correction,the up-scaling results were quantitatively and qualitatively analyzed.The results showed that the blue band B1,the near-infrared band B5,the salt index SI,the salt index S5,and the improved spectral index NDVI S1 had a good correlation with the measured soil salinity data in two remote sensing data.Correlation coefficients were more than 0.3.In the three regression models,the best model for monitoring soil salinization by UAV data was the SRU model,the optimal model of GF 1 data was the MLR S model.After up-scale conversion,the inversion accuracy of soil salinity was much higher than that of direct satellite data inversion.The optimal model after ascending scale was obviously improved with the optimal model by directly using GF-1 data inversion,the former R^2 c was 0.338 higher than that of the latter,R^2 v was 0.369 higher,but RMSE was 0.057 percentage points lower.The research results can provide a reference for large-scale rapid monitoring of salinization in the bare soil period of irrigation districts.
作者
陈俊英
王新涛
张智韬
韩佳
姚志华
魏广飞
CHEN Junying;WANG Xintao;ZHANG Zhitao;HAN Jia;YAO Zhihua;WEI Guangfei(The Key Laboratory of Agricultural Soil and Water Engineering in Arid Areas,Ministry of Education,Northwest A&F University,Yangling,Shaanxi 712100,China;College of Water Resources and Architectural Engineering,Northwest A&F University,Yangling,Shaanxi 712100,China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2019年第12期161-169,共9页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家重点研发计划项目(2017YFC0403302)
陕西省自然科学基础研究计划项目(2019JM-066)
关键词
土壤盐渍化
裸土期
多光谱遥感
NDVI
S1
尺度转换
soil salinization
bare soil period
multispectral remote sensing
NDVI-S1
scales transformation
