中文摘要：

条件植被温度指数（VTCI）综合了地表主要参数——归一化植被指数（NDVI）和地表温度（LST）,能够较为准确地对干旱进行监测,可为抗旱救灾、作物估产等提供科学依据。为了提高VTCI的区域估产精度,以陕西省关中平原为研究区域,将遥感反演的VTCI与CERES-Wheat小麦生长模型模拟的土壤浅层含水率相结合,通过四维变分（4D-VAR）同化算法实现2008—2014年冬小麦主要生育期旬尺度VTCI的同化。将同化和未同化的VTCI分别运用改进的层次分析法、熵值法及两者组合赋权法建立冬小麦单产估测模型,选择最优估测模型对2011年关中平原各县（区）进行单产估测和精度评价,并分析2008—2014年关中平原冬小麦单产的时空分布特征,结果表明：无论是在单点尺度还是区域尺度,同化的VTCI均能更好地响应外部观测数据,区域VTCI纹理性更好,更符合VTCI的先验知识。与未同化VTCI构建的估测模型相比,应用同化的VTCI所建的估测模型的估测精度明显提高,相关系数达到0.784（P〈0.001）。应用最优估测模型对2011年关中平原29个县（区）估产结果中,有16个县（区）的估测单产相对误差小于10%,28个县（区）的估测单产相对误差小于15%,总体平均相对误差为8.68%,均方根误差为421.9 kg/hm^2。近年来关中平原的冬小麦单产呈现个别年份波动、总体增长的年际变化规律,且呈现出中部单产最高、西部次之、东部最低的空间分布特征,与实际情况符合。

英文摘要：

Vegetation temperature condition index（ VTCI） combines the main parameters of normalized difference vegetation index（ NDVI） and land surface temperature（ LST）,and is applicable to a more accurate monitoring of droughts in the Guanzhong Plain,Shaanxi,China. VTCI also provides a scientific basis for drought relief and crop yield estimation by using remotely sensed data. This study chose Guanzhong Plain as the study area,and was to combine the remote sensed VTCI and simulated soil surface moisture by the CERES-Wheat（ Crop environment resource synthesis for wheat） model to get a high regional yield estimation accuracy by using the four-dimensional variational（ 4D-VAR） data assimilation approach. The improved analytic hierarchy process,the entropy method and the joint the two weighting methods were used to establish winter wheat yield estimation models by using the monitored VTCI and the assimilated ones respectively. The optimal model for estimating winter wheat yields in the study area from 2008 to 2014 was selected,and the measured wheat yield of the year 2011 was used to validate the accuracies of the optimal model. The results showed that no matter at the sampling sites or at the regional scale,the assimilated VTCIs were all better able to respond the monitored VTCIs and thesurface moisture data,and the texture of assimilated VTCI images was better and more consistent with the regional drought distribution. Compared the yield estimation models with the monitored VTCIs,the accuracies of the yield estimation models with the assimilated VTCIs were improved,and the correlation coefficients of the optimal yield estimation model with the weighted VTCIs of 0. 784（ P 0. 001）. The optimal yield estimation model was applied to estimate wheat yields in 29 counties of the Guanzhong Plain,and the results showed that except for the Pucheng County,the estimated yields＇ relative errors of other 28 counties in Guanzhong Plain were less than 15%,and the errors were less than 10% in 16 counties of Guanzhon