利用时序合成孔径雷达数据监测水稻叶面积指数  

Monitoring rice leaf area index using time-series SAR data

作　　者：张晓倩[1] 郭琳[1] 马尚杰[1] 赵占营[1] 裴志远[1] 

机构地区：[1]农业部规划设计研究院农业资源监测站,北京100125

出　　处：《农业工程学报》2014年第13期185-193,共9页Transactions of the Chinese Society of Agricultural Engineering

基　　金：高分多载荷协同农业应用技术研究(GF13/15-311-003)项目资助

摘　　要：为了确定全极化雷达数据监测水稻叶面积指数动态变化的精度,该文对水稻叶面积指数与后向散射系数进行了各生长阶段建模比较。采用广东雷州地区多时相多入射角精细全极化Radarsat-2数据,结合水稻全生育期地面样方实测数据,首先分析多入射角归一化后四极化(vertical-horizontal polarization,VH;vertical-vertical polarization,VV;horizontal-horizontal polarization,HH;horizontal-vertical polarization,HV)、比值极化HH/VV后向散射系数与水稻叶面积指数(leaf area index,LAI)随时间变化特征以及在营养生长阶段、生殖生长阶段和全生育期的相关关系,提取相关系数高于0.8的极化与生长阶段进行水云模型建模,最终生成多期水稻LAI反演分布图,并验证该数据反演水稻各生长阶段LAI的精度,探索SAR数据追踪区域尺度水稻长势的可行性。结果表明,在地形较为平坦的水稻集中连片种植区,VV、HH/VV后向散射系数与LAI在营养生长期、全生育期极显著相关(P<0.01),相关系数均高于0.83。营养生长阶段VV、HH/VV水云模型拟合决定系数分别为0.77、0.87,全生育期VV、HH/VV水云模型拟合决定系数分别为0.73、0.8,营养生长阶段模型优于全生育期模型。精细四极化SAR数据监测区域尺度水稻LAI动态变化具有应用潜力,优选的极化模型为进一步的水稻长势监测提供依据。Rice is one of the most important food crops in China, so timely obtaining accurate rice growth information in regional scale is highly significant for crop management and decision making. However, there are plenty of rain and dense cloud cover in rice growth season, that makes it difficult to monitor rice paddy information by optical remote sensing data. It is an accepted fact that Synthetic Aperture Radar（SAR） data is a suitable alternative for crop monitoring in cloud-prone and raining area. In this paper, we investigated the potential of Radarsat-2 SAR data for rice paddy growth monitoring at regional scale. Four C-band SAR backscattering coefficients（VH, VV, HH, HV） and HH/VV ratio backscattering coefficient were employed for setting up the relationship with leaf area index（LAI） in rice growing season. The test site located in Leizhou（20°52′N, 110°05′E）, Guangdong province. Four Radarsat-2 products in fine quad polarization mode were acquired during the critical rice growth stage. In situ measurement in year 2013 was also made concurrently with the satellite pass. 25 plots were selected for measuring the rice growth parameters, such as LAI, plant height, sowing date, etc. The backscattering coefficients with multi-incidence angle were extracted from multi-temporal SAR images and then normalized to same angle. Firstly, the study analyzed the temporal behavior of microwave backscattering coefficients（VH, VV, HH, HV, HH/VV） and LAI in rice growth season. Secondly, correlation analyses between the backscattering coefficients in different polarization and LAI were also carried out in vegetative stage, reproductive stage and whole growth period respectively, then picking the polarization and growth stage corresponding with high correlation coefficient which was above 0.8 to build water cloud model and evaluate the performance of each model. Finally, based on the previous result, the LAI distribution map in time domain was generated using the best model of entire growth period. The results

关 键 词：雷达 极化 监测 SAR 水稻 叶面积指数 时序分析 生育期 

分 类 号：S127[农业科学—农业基础科学]