基于遥感指数的水稻结实率估算模型

发布时间：2018-06-13 13:36

本文选题：低温冷害 + 区域产量监测　；参考：《江苏农业科学》2017年16期

【摘要】：水稻结实率是水稻产量构成因素中的重要组成,其受气象环境影响较大,因此,建立水稻结实率估算模型对区域水稻产量监测具有重要作用。在2012、2013年水稻光谱观测试验的基础上,以遥感影像为数据源,提出了能够在水稻抽穗至成熟阶段反映低温冷害影响的遥感指数(cold vegetation index,CVI),并分析了CVI值与水稻产量要素、温度因子的关系。在此基础上,以抽穗至成熟阶段的CVI和平均气温为自变量,采用线性回归方法,构建水稻结实率估算模型。为验证该模型,选择苏皖2省一季稻为研究对象,并以MOD09A1产品为遥感数据源,对水稻结实率估算模型进行了点和面上的模拟和评价。结果显示,抽穗开花至成熟阶段CVI和在此期间的温度条件与水稻结实率存在显著的相关关系,是影响结实率的2个重要因素。站点估算的结实率相对误差小于11%,平均相对误差为4%,估算值空间分布与观测值基本一致,表明该模型的模拟结果能够较好地反映水稻结实率的空间分布情况和不同气候年景下结实率的变化。综上所述,提出的CVI和建立的结实率估算模型适用于区域水稻低温冷害监测和灾损评估。
[Abstract]:Rice seed setting rate is an important component of rice yield components, which is greatly affected by meteorological environment. Therefore, the establishment of rice seed setting rate estimation model plays an important role in regional rice yield monitoring. On the basis of rice spectral observation experiment in 2012 and 2013, a new remote sensing index cold vegetation index CVII was proposed based on remote sensing images to reflect the effects of low temperature chilling injury from heading to mature stage of rice, and the CVI value and rice yield factors were analyzed. The relationship between temperature factors. On the basis of this, using CVI and mean temperature from heading to maturity as independent variables, a linear regression model was established to estimate the seed setting rate of rice (Oryza sativa L.). In order to verify the model, the model of rice seed setting rate in Jiangsu and Anhui provinces was simulated and evaluated with MOD09A1 as remote sensing data source. The results showed that there was a significant correlation between CVI from heading flowering to maturation stage and the temperature conditions during this period, which were two important factors affecting the seed setting rate of rice (Oryza sativa L.). The relative error of the seed setting rate estimated by the station is less than 11 and the average relative error is 4. The spatial distribution of the estimated value is basically consistent with the observed value. The results show that the simulation results of this model can reflect the spatial distribution of rice seed setting rate and the variation of seed setting rate under different climatic conditions. In conclusion, the proposed CVI and the established seed setting rate estimation model are suitable for regional rice chilling damage monitoring and damage assessment.
【作者单位】：南京信息工程大学气象灾害预报预警与评估协同创新中心/江苏省农业气象重点实验室;中国人民解放军94592部队气象台;
【基金】：国家科技支撑计划(编号:2011BAD32B01) 国家公益性行业(气象)科研专项(编号:GYHY201306036;GYHY201306035;GYHY201506055) 江苏高校优势学科建设工程
【分类号】：S127;S511

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