中国南方双季稻春季冷害动态监测

doi:10.3864/j.issn.0578-1752.2014.24.003

摘要/Abstract

摘要： 【目的】利用星地多源数据，在南方双季稻种植区空间信息提取、双季稻发育期动态图组制作及研究区逐日平均温度反演的基础上，结合冷害监测指标，实现多要素相协同的南方双季稻春季冷害动态监测，为农业部门及时准确地应对双季稻冷害，减少冷害损失提供技术支持。【方法】利用南方双季稻区190个气象站点1951—2011年逐日气温数据，计算各站点≥10℃的多年平均积温。根据各站点多年平均积温与其地理因子的相关关系，建立多年平均积温推算模型。通过所获模型得到研究区积温空间分布图。按照南方双季稻安全生产积温阈值≥5 300℃·d的指标，扣除研究区内积温小于该值的区域，制作南方双季稻积温区划图。利用 MODIS MCD12Q1 分类产品获取了 2001—2010 年 10 年的谷类作物分布图。将以上两步结果叠加求交集，提取南方双季稻种植区空间信息；利用南方双季稻区167个农业试验观测站点1981—2011年的水稻发育期资料，计算各个站点双季早稻主要发育期出现的多年平均日期。依据发育期多年平均日期与地理因子的相关性，获取各主要发育期回归拟合分布图。在拟合结果残差订正的基础上，将南方双季稻春季冷害重点监测时段前后两幅发育期静态图，通过EVNI+IDL编程，制作双季早稻发育期动态图；利用AMSR_E_L2A 89 GHz升轨和降轨垂直极化亮温、地理因子与气象站日平均气温建立多元混合回归拟合模型，通过所获模型反演研究区2010年2—5月逐日平均气温。【结果】对研究所建多年平均积温推算模型，利用未参与建模的90个气象站观测数据进行验证，观测值与模型模拟结果之间的均方根误差（RMSE）为289℃，这一估测精度能够满足研究所需。双季稻积温区划与MODIS土地利用分类结果叠加求交集，提取的双季稻种植区面积占研究区总面积的29.26%。通过该步骤一方面提升了双季稻冷害监测结果的使用价值。另一方面，可使双季稻冷害实时监测在还没有获取当年准确种植位置信息前就能有效开展起来；对研究所获南方双季稻春季冷害重点监测时段（早稻播种期至返青期）两幅发育期静态图，采用未参与建模的 59 个农业试验站观测数据进行验证，观测值与模型模拟结果之间的均方根误差（RMSE）分别为5.68和4.24 d，模型精度符合要求，试验结果可以于后续分析；研究将遥感数据与地面数据相结合通过混合建模反演逐日气温，该方法充分利用了微波遥感受天气影响小的特点，克服了南方常年多云的天气条件，使模拟的日平均气温的RMSE为1.69℃。微波数据的加入使日平均气温估计精度提高了0.35℃。研究对2010年南方双季稻春季冷害的动态监测结果与农业统计部门报道的当年南方双季早稻冷害在发生时间和空间上相吻合。【结论】本研究建立的冷害监测方法具有普适性，能够实现对南方双季稻大范围冷害的同步跟踪监测，对其他作物大范围冷害监测同样也适用。

关键词: 双季稻, 春季冷害, 动态监测

Abstract: 【Objective】Satellites and ground multi-source data were used in this study to achieve dynamic monitoring of cold damage of double cropping rice by combining with extraction result of double cropping rice planting area, dynamic development phase maps, daily mean temperature maps and monitoring index of cold damage. The result can provide technical supports for the agricultural production sectors to make quick response to cold damage and to reduce the loss of cold damage.【Method】Using daily mean temperature of 190 meteorological stations located in southern China from 1951 to 2011, the annual average accumulated temperature (≥10℃) was obtained for each station. According to correlativity between annual average accumulated temperature and geographical factors, the accumulated temperature prediction model was established, and according to the model, the spatial distribution map of accumulated temperature was obtained. Using accumulated temperature threshold of 5 300 ℃.d for double cropping rice production, the area that average accumulated temperature less than the value was removed from research area. The result was as accumulated temperature zone of double cropping rice. The 10 years distribution of grain crops was obtained by using the classification products of MODIS MCD12Q1 from 2001 to 2010. Finally, the information of double cropping rice planting area was extracted by calculating the intersection of accumulated temperature zone of double cropping rice and grains classification products of MODIS MCD12Q1. This research used development phase data of 167 agricultural experiment stations in southern China from 1981 to 2011, according to the correlation between many years average date of development phase and geographical factors, the regression fitting distribution map of development phase was obtained for double cropping early rice. On the basis of residual error correction of the fitting results, the maps of dynamic development phase were made by using two static maps before and after through EVNI + IDL programming. Multivariate regression model of daily mean temperature was established by using the correlation between AMSR_E_L2A 89 GHz bright temperature, geological factors and daily mean temperature of meteorological stations, as a result to complete the calculation of February 2010 to May daily mean temperature. 【Result】Using 90 meteorological stations observation data that were not involved in modeling to validate the accumulated temperature prediction model, and the results showed that there was no significant difference between estimated and measured values, the root mean square error is 289℃. The estimate accuracy can meet the needs of the research. By calculating the intersection between the accumulated temperature zone of double cropping rice and MODIS grains classification products, the extractive planting area of double cropping rice accounted for 29.26% of total of the study area. Through the steps, on the one hand, improved the use value of monitoring results of cold damage. On the other hand, can make the real-time monitoring of cold damage of double cropping rice be launched before haven't get the accurate planting location information about double cropping rice; Using observation data of 59 agricultural experiment stations that were not involved in modeling to validate development phase simulated results of double cropping early rice seeding and reviving period, the results indicated that the root mean square errors were, respectively, 5.68 days and 4.24 days between real and fitted many year average date of development phase. Model accuracy meets the requirements, the experimental results can be used to subsequent analysis; Daily mean temperature was obtained by hybrid modeling method, the method makes full use of the characteristics of microwave remote sensing, the data is affected little by the weather, and can overcome the south year-round cloudy weather conditions, root mean square error (RMSE) of simulative daily mean temperature is 1.69℃. Estimated precision of daily mean temperature was increased by 0.35℃ because of the addition of microwave data. Monitoring results for 2010 spring cold damage of double corpping rice highly corresponds to reported content of agricultural statistic department in time and space.【Conclusion】The method constructed by this paper can realize the large-scale synchronous monitoring of cold damage of double cropping rice. The method has universality. It can also be applied to large scale cold damage dynamic monitoring of other crops.

Key words: double cropping rice, spring cold damage, dynamic monitoring

程勇翔，王秀珍，郭建平，赵艳霞，黄敬峰. 中国南方双季稻春季冷害动态监测[J]. 中国农业科学, 2014, 47(24): 4790-4804.

CHENG Yong-xiang, WANG Xiu-zhen, GUO Jian-ping, ZHAO Yan-xia, HUANG Jing-feng. Dynamic Monitoring of Spring Cold Damage of Double Cropping Rice in Southern China[J]. Scientia Agricultura Sinica, 2014, 47(24): 4790-4804.

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