河北省中部平原玉米长势遥感综合监测
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摘要
为了提高玉米的遥感长势监测的准确度,以河北省中部平原地区为研究区域,以MODIS遥感数据反演的条件植被温度指数(Vegetation Temperature Condition Index, VTCI)与叶面积指数(Leaf Area Index, LAI)作为玉米长势监测指标,通过灰色关联度分析法确定玉米各生育时期(出苗—拔节期、拔节—抽雄期、抽雄—灌浆期与灌浆—成熟期)VTCI与LAI作为相应生育时期长势监测指标的权重值,以及4个生育时期的玉米长势在总体长势与产量形成中的权重值,并基于权重结果分别构建玉米在4个生育时期与主要生育期的长势综合监测指标,进而评估研究区域2011—2016年间的玉米长势。结果表明,各生育时期VTCI作为长势监测指标的权重值均大于LAI,且以拔节—抽雄期最大,抽雄—灌浆期次之,说明玉米各生育时期的长势与最终产量较易受到水分胁迫的影响,并以拔节—抽雄期与抽雄—灌浆期对水分胁迫最为敏感;而玉米长势综合监测指标在4个生育时期的权重值较为接近,并以灌浆—成熟期略大,说明该时期的玉米长势与最终产量之间的关系较为密切。研究区域5市的县域尺度玉米长势综合监测指标与单产之间的决定系数(R2)介于0.247～0.598之间,均达到了极显著水平(P<0.001),优于单一的VTCI或LAI指标,表明基于长势综合监测指标的玉米长势监测结果准确度较高。研究年份间该区域的玉米长势以2011年的长势最好,2014年与2015年长势最差,且西部长势优于东部。
In order to improve maize growth monitoring accuracy, the central plain of Hebei Province(PR China) was chosen as the study area. The gray correlation analysis method was implemented to calculate the weight coefficients of vegetation temperature condition index(VTCI)and leaf area index(LAI) at four maize growth stages(emergence-jointing, jointing-booting,booting-filling, and filling-mature), as well as the weight coefficients of growth at the 4 stages during maize growth and yield formation. Thus, the integrated growth monitoring indices(G) at the4 stages and main growth stage could be derived. Linear regression models between maize yields and Gs of counties in the years from 2011 to 2015 were established to analyze the precision of maize growth monitoring. The results showed that the weight coefficients of VTCI at the 4 stages were greater than those of LAI, and the joint-booting stage was the highest, the booting-filling stage was followed. The results further indicated that maize growth and yield formation were likely impacted by water stress, especially at the joint-booting and the booting-filling stage. The weight coefficients of maize growth at the 4 stages were similar. It is noted that growth at the fillingmature stage was the highest. It illustrated that maize growth at the filling-mature stage was most closely related to maize production. Coefficients of determination(R~2) of the linear regression analysis between Gs and maize yields of counties in 5 cities all passed the significant test at 0. 01 level, and R~2 values were greater than those between maize yields and VTCIs or LAIs. The findings of current study demonstrated a high accuracy of the gs derived from gray correlation analysis method. Based on the maize growth monitoring data, this study implies that the best year was 2011,the worst year were 2014 and 2015, and the maize growth in the western plain was better than the eastern part.
In order to improve maize growth monitoring accuracy, the central plain of Hebei Province(PR China) was chosen as the study area. The gray correlation analysis method was implemented to calculate the weight coefficients of vegetation temperature condition index(VTCI)and leaf area index(LAI) at four maize growth stages(emergence-jointing, jointing-booting,booting-filling, and filling-mature), as well as the weight coefficients of growth at the 4 stages during maize growth and yield formation. Thus, the integrated growth monitoring indices(G) at the4 stages and main growth stage could be derived. Linear regression models between maize yields and Gs of counties in the years from 2011 to 2015 were established to analyze the precision of maize growth monitoring. The results showed that the weight coefficients of VTCI at the 4 stages were greater than those of LAI, and the joint-booting stage was the highest, the booting-filling stage was followed. The results further indicated that maize growth and yield formation were likely impacted by water stress, especially at the joint-booting and the booting-filling stage. The weight coefficients of maize growth at the 4 stages were similar. It is noted that growth at the fillingmature stage was the highest. It illustrated that maize growth at the filling-mature stage was most closely related to maize production. Coefficients of determination(R~2) of the linear regression analysis between Gs and maize yields of counties in 5 cities all passed the significant test at 0. 01 level, and R~2 values were greater than those between maize yields and VTCIs or LAIs. The findings of current study demonstrated a high accuracy of the gs derived from gray correlation analysis method. Based on the maize growth monitoring data, this study implies that the best year was 2011,the worst year were 2014 and 2015, and the maize growth in the western plain was better than the eastern part.
引文
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[9]江东,王乃斌,杨小唤,等.NDVI曲线与农作物长势的时序互动规律[J].生态学报,2002,22(2):247-253.[Jiang D,Wang N B,Yang X H,et al.Principles of the interaction between NDVI profile and growing situation of crops[J].Acta Ecologiac Sinica,2002,22(2):247-253.]
[10]李军玲,张弘,曹淑超.夏玉米长势卫星遥感动态监测指标研究[J].玉米科学,2013,21(3):149-153.[Li J L,Zhang H,Cao S C.Dynamic monitoring on the summer maize growth based on satellite remote sensing[J].Journal of Maize Sciences,2013,21(3):149-153.]
[11]Wu B F,Meng J H,Li Q Z,et al.Remote sensing-based global crop monitoring:experiences with China’s cropwatch system[J].International Journal of Digital Earth,2014,7(2):113-137.
[12]王鹏新,龚健雅,李小文.条件植被温度指数及其在干旱监测中的应用[J].武汉大学学报:信息科学版,2001,26(5):412-418.[Wang P X,Gong J Y,Li X W.Vegetation temperature condition index and its application for drought monitoring[J].Geomatics and Information Science of Wuhan University,2001,26(5):412-418.]
[13]Sun W,Wang P X,Zhang S Y,et al.Using the vegetation temperature condition index for time series drought occurrence monitoring in the Guanzhong Plain,PR China[J].International Journal of Remote Sensing,2008,29(17-18):5133-5144.
[14]Patel N R,Parida B R,Venus V,et al.Analysis of agricultural drought using vegetation temperature condition index(VTCI)from Terra/MODIS satellite data[J].Environmental Monitoring and Assessment,2012,184(12):7153-7163.
[15]李艳,王鹏新,刘峻明,等.基于条件植被温度指数的冬小麦主要生育时期干旱监测效果评价III-干旱对冬小麦产量的影响评估[J].干旱地区农业研究,2014,32(5):218-222.[Li Y,Wang P X,Liu J M,et al.Evaluation of drought monitoring effects in the main growth and development stages of winter wheat using vegetation temperature condition index III-impact evaluation of drought on wheat yield[J].Agricultural Research in the Arid Areas,2014,32(5):218-222.]
[16]田苗,王鹏新,张树誉,等.基于条件植被温度指数的冬小麦产量预测[J].农业机械学报,2014,45(2):239-245.[Tian M,Wang P X,Zhang S Y,et al.Winter wheat yield forecasting based on vegetation temperature condition index[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(2):239-245.]
[17]苏涛,王鹏新,刘翔舸,等.基于熵值组合预测和多时相遥感的春玉米估产[J].农业机械学报,2011,42(1):186-192.[Su T,Wang P X,Liu X G,et al.Spring maize yield estimation based on combination of forecasting of entropy method and multi-temporal remotely sensed data[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(1):186-192.]
[18]de Wit A J W,Van Diepen C A.Crop model data assimilation with the ensemble Kalman filter for improving regional crop yield forecasts[J].Agricultural and Forest Meteorology,2007,146(1-2):38-56.
[19]解毅,王鹏新,刘峻明,等.基于四维变分和集合卡尔曼滤波同化方法的冬小麦单产估测[J].农业工程学报,2015,31(1):187-195.[Xie Y,Wang P X,Liu J M,et al.Winter wheat yield estimation based on assimilation method combined with 4DVAR and EnKF[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(1):187-195.]
[20]徐玲玲,吕厚荃,方利.气候变化对黄淮海地区下玉米气候适宜度的影响[J].资源科学,2014,36(4):782-787.[Xu L L,Lv H Q,Fang L.Effect of climate on the climate suitability of summer maize on the Huang-Huai-Hai Plain[J].Resources Science,2014,36(4):782-787.]
[21]陈超,于强,王恩利,等.华北平原作物水分生产力区域分异规律[J].资源科学,2009,31(9):1477-1485.[Chen C,Yu Q,Wang E L,et al.Modeling the spatial distribution of crop water productivity in the North China Plain[J].Resources Science,2009,31(9):1477-1485.]
[22]河北省人民政府办公厅,河北省统计局.河北农村统计年鉴[M].北京:中国统计出版社,2007-2016.[General office of the people’s government of Hebei province,Hebei provincial bureau of statistics.Hebei Rural Year Book[M].Beijing:China Statistics Press,2007-2016.]
[23]杜栋,庞庆华,吴炎,等.现代综合评价方法与案例精选[M].北京:清华大学出版社,2008.[Du D,Pang Q H,Wu Y,et al.Modern Comprehensive Evaluation Method and Case Selection[M].Beijing:Tsinghua University Press,2008.]
[24]谭凯炎,宋迎波,刘涛.QX/T 335-2016,主要粮食作物产量年景等级[M].北京:气象出版社,2016.[Tan K Y,Song Y B,Liu T.QX/T 335-2016,The Grade of Year’s Harvest in Grain Yields of Staple Crops[M].Beijing:China Meteorological Press,2016.]
[25]Yilmaz E,Akcay S,Gurbuz T,et al.Effect of different water stress on the yield and yield components of second crop corn in semiarid climate[J].Journal of Food Agriculture and Environment,2010,8(3-4):415-421.
[26]李德,祁宦,马晓群.安徽省淮北平原下玉米主要生育时期旱涝指标与影响评估[J].中国农学通报,2013,29(17):208-216.[Li D,Qi C,Ma X Q.The climate index and assessment about drought and flood in maize’s key growth stage in Huaibei Plain in Anhui province[J].Chinese Agricultural Science Bulletin,2013,29(17):208-216.]
[2]吴炳方,张峰,刘成林,等.农作物长势综合遥感监测方法[J].遥感学报,2004,8(6):498-514.[Wu B F,Zhang F,Liu C L,et al An integrated method for crop condition monitoring[J].Journal o Remote Sensing,2004,8(6):498-514.]
[3]刘红辉.资源遥感-从区域调查到全球变化研究[J].资源科学2000,22(3):34-38.[Liu H H.Resources remote sensing-from regional inventory to global change studies[J].Resources Science2000,22(3):34-38.]
[4]Doraiswamy P C,Hatfield J L,Jackson T J,et al.Crop condition and yield simulations using Landsat and MODIS[J].Remote Sensing of Environment,2004,92(4):548-559.
[5]Doraiswamy P C,Moulin S,Cook P W,et al.Crop yield assessment from remote sensing[J].Photogrammetric Engineering and Remote Sensing,2003,69(6):665-674.
[6]高林,李长春,王宝山,等.基于多源遥感数据的大豆叶面积指数估测精度对比[J].应用生态学报,2016,27(1):191-200.[Gao L,Li C C,Wang B S,et al.Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data[J].Chinese Journal of Applied Ecology,2016,27(1):191-200.]
[7]赵虎,杨正伟,李霖,等.作物长势遥感监测指标的改进与比较分析[J].农业工程学报,2011,27(1):243-249.[Zhao H,Yang ZW,Li L,et al.Improvement and comparative analysis of indices of crop growth condition monitoring by remote sensing[J].Transactions of the Chinese Society of Agricultural Engineering,2011,27(1):243-249.]
[8]吴文斌,杨桂霞.用NOAA图像监测冬小麦长势的方法研究[J].中国农业资源与区划,2001,22(2):58-61.[Wu W B,Yang G X.A study of method of monitoring the winter wheat growth by using NOAA image[J].Chinese Journal of Agricultural Resources and Regional Planning,2001,22(2):58-61.]
[9]江东,王乃斌,杨小唤,等.NDVI曲线与农作物长势的时序互动规律[J].生态学报,2002,22(2):247-253.[Jiang D,Wang N B,Yang X H,et al.Principles of the interaction between NDVI profile and growing situation of crops[J].Acta Ecologiac Sinica,2002,22(2):247-253.]
[10]李军玲,张弘,曹淑超.夏玉米长势卫星遥感动态监测指标研究[J].玉米科学,2013,21(3):149-153.[Li J L,Zhang H,Cao S C.Dynamic monitoring on the summer maize growth based on satellite remote sensing[J].Journal of Maize Sciences,2013,21(3):149-153.]
[11]Wu B F,Meng J H,Li Q Z,et al.Remote sensing-based global crop monitoring:experiences with China’s cropwatch system[J].International Journal of Digital Earth,2014,7(2):113-137.
[12]王鹏新,龚健雅,李小文.条件植被温度指数及其在干旱监测中的应用[J].武汉大学学报:信息科学版,2001,26(5):412-418.[Wang P X,Gong J Y,Li X W.Vegetation temperature condition index and its application for drought monitoring[J].Geomatics and Information Science of Wuhan University,2001,26(5):412-418.]
[13]Sun W,Wang P X,Zhang S Y,et al.Using the vegetation temperature condition index for time series drought occurrence monitoring in the Guanzhong Plain,PR China[J].International Journal of Remote Sensing,2008,29(17-18):5133-5144.
[14]Patel N R,Parida B R,Venus V,et al.Analysis of agricultural drought using vegetation temperature condition index(VTCI)from Terra/MODIS satellite data[J].Environmental Monitoring and Assessment,2012,184(12):7153-7163.
[15]李艳,王鹏新,刘峻明,等.基于条件植被温度指数的冬小麦主要生育时期干旱监测效果评价III-干旱对冬小麦产量的影响评估[J].干旱地区农业研究,2014,32(5):218-222.[Li Y,Wang P X,Liu J M,et al.Evaluation of drought monitoring effects in the main growth and development stages of winter wheat using vegetation temperature condition index III-impact evaluation of drought on wheat yield[J].Agricultural Research in the Arid Areas,2014,32(5):218-222.]
[16]田苗,王鹏新,张树誉,等.基于条件植被温度指数的冬小麦产量预测[J].农业机械学报,2014,45(2):239-245.[Tian M,Wang P X,Zhang S Y,et al.Winter wheat yield forecasting based on vegetation temperature condition index[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(2):239-245.]
[17]苏涛,王鹏新,刘翔舸,等.基于熵值组合预测和多时相遥感的春玉米估产[J].农业机械学报,2011,42(1):186-192.[Su T,Wang P X,Liu X G,et al.Spring maize yield estimation based on combination of forecasting of entropy method and multi-temporal remotely sensed data[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(1):186-192.]
[18]de Wit A J W,Van Diepen C A.Crop model data assimilation with the ensemble Kalman filter for improving regional crop yield forecasts[J].Agricultural and Forest Meteorology,2007,146(1-2):38-56.
[19]解毅,王鹏新,刘峻明,等.基于四维变分和集合卡尔曼滤波同化方法的冬小麦单产估测[J].农业工程学报,2015,31(1):187-195.[Xie Y,Wang P X,Liu J M,et al.Winter wheat yield estimation based on assimilation method combined with 4DVAR and EnKF[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(1):187-195.]
[20]徐玲玲,吕厚荃,方利.气候变化对黄淮海地区下玉米气候适宜度的影响[J].资源科学,2014,36(4):782-787.[Xu L L,Lv H Q,Fang L.Effect of climate on the climate suitability of summer maize on the Huang-Huai-Hai Plain[J].Resources Science,2014,36(4):782-787.]
[21]陈超,于强,王恩利,等.华北平原作物水分生产力区域分异规律[J].资源科学,2009,31(9):1477-1485.[Chen C,Yu Q,Wang E L,et al.Modeling the spatial distribution of crop water productivity in the North China Plain[J].Resources Science,2009,31(9):1477-1485.]
[22]河北省人民政府办公厅,河北省统计局.河北农村统计年鉴[M].北京:中国统计出版社,2007-2016.[General office of the people’s government of Hebei province,Hebei provincial bureau of statistics.Hebei Rural Year Book[M].Beijing:China Statistics Press,2007-2016.]
[23]杜栋,庞庆华,吴炎,等.现代综合评价方法与案例精选[M].北京:清华大学出版社,2008.[Du D,Pang Q H,Wu Y,et al.Modern Comprehensive Evaluation Method and Case Selection[M].Beijing:Tsinghua University Press,2008.]
[24]谭凯炎,宋迎波,刘涛.QX/T 335-2016,主要粮食作物产量年景等级[M].北京:气象出版社,2016.[Tan K Y,Song Y B,Liu T.QX/T 335-2016,The Grade of Year’s Harvest in Grain Yields of Staple Crops[M].Beijing:China Meteorological Press,2016.]
[25]Yilmaz E,Akcay S,Gurbuz T,et al.Effect of different water stress on the yield and yield components of second crop corn in semiarid climate[J].Journal of Food Agriculture and Environment,2010,8(3-4):415-421.
[26]李德,祁宦,马晓群.安徽省淮北平原下玉米主要生育时期旱涝指标与影响评估[J].中国农学通报,2013,29(17):208-216.[Li D,Qi C,Ma X Q.The climate index and assessment about drought and flood in maize’s key growth stage in Huaibei Plain in Anhui province[J].Chinese Agricultural Science Bulletin,2013,29(17):208-216.]