植物生态学报 ›› 2005, Vol. 29 ›› Issue (6): 918-926.DOI: 10.17521/cjpe.2005.0127
收稿日期:
2004-07-29
接受日期:
2004-12-20
出版日期:
2005-07-29
发布日期:
2005-09-30
作者简介:
E-mail:mayp@cams.cma.gOV.cn
基金资助:
MA Yu-Ping1(), WANG Shi-Li1, ZHANG Li1, HOU Ying-Yu2
Received:
2004-07-29
Accepted:
2004-12-20
Online:
2005-07-29
Published:
2005-09-30
摘要:
作物模型与遥感信息的结合有助于利用遥感监测的大范围植被信息解决作物模型区域应用时模型初始状态和参数值难以确定的问题。该文借助叶面积指数(LAI)将经过华北冬小麦(Triticum aestivium)适应性调整的WOFOST模型与经参数调整检验的SAIL-PROSPECT模型相嵌套,利用嵌套模型模拟作物冠层的土壤调整植被指数(SAVI),在代表点上借助FSEOPT优化程序使模拟SAVIs与MODIS遥感数据合成SAVIm的差异达到最小,从而对WOFOST模型重新初始化。结果表明,借助于遥感信息,出苗期的重新初始化使模拟成熟期与按实际出苗期模拟的结果相差在2天以内,模拟的LAI和总干重的误差比按实际出苗期模拟结果的误差降低3~8个百分点;返青期生物量的重新初始化使模拟LAI和地上总干重在关键发育时刻的误差降至16%以内,模拟LAI和贮存器官重在整个生育期内都更加接近实测值;对返青期生物量的动态调整显示返青到抽穗期间较少次数的遥感数据即能有效地提高作物模型的模拟效果。与国外同类研究相比,该文在作物模型本地化、重新初始化变量和优化比较对象的选择上都有所不同,而利用遥感数据动态调整作物模型初始状态或参数值更具有新意。该文对区域尺度上利用遥感信息优化作物模型的研究具有基础性、探讨性意义。
马玉平, 王石立, 张黎, 侯英雨. 基于遥感信息的作物模型重新初始化/参数化方法研究初探. 植物生态学报, 2005, 29(6): 918-926. DOI: 10.17521/cjpe.2005.0127
MA Yu-Ping, WANG Shi-Li, ZHANG Li, HOU Ying-Yu. A PRELIMINARY STUDY ON THE RE-INITIALIZATION/RE-PARAMETERIZATION OF A CROP MODEL BASED ON REMOTE SENSING DATA. Chinese Journal of Plant Ecology, 2005, 29(6): 918-926. DOI: 10.17521/cjpe.2005.0127
2001~2002 | |||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
月-日 Month-day | 10-2 | 11-20 | 3-7 | 3-12 | 3-19 | 4-2 | 4-8 | 4-15 | 5-2 | ||||||||||||||||||||||||||
年内天数 Day of the year | 275 | 324 | 66 | 71 | 78 | 92 | 98 | 105 | 122 | ||||||||||||||||||||||||||
2002~2003 | |||||||||||||||||||||||||||||||||||
月-日 Month-day | 11-5 | 11-12 | 11-17 | 11-27 | 3-10 | 3-20 | 3-28 | 4-4 | 4-9 | 4-27 | 5-11 | ||||||||||||||||||||||||
年内天数 Day of the year | 309 | 316 | 321 | 331 | 69 | 79 | 87 | 94 | 99 | 117 | 131 |
表1 本研究收集到的MODIS遥感图象的日期
Table 1 The date of MODIS data
2001~2002 | |||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
月-日 Month-day | 10-2 | 11-20 | 3-7 | 3-12 | 3-19 | 4-2 | 4-8 | 4-15 | 5-2 | ||||||||||||||||||||||||||
年内天数 Day of the year | 275 | 324 | 66 | 71 | 78 | 92 | 98 | 105 | 122 | ||||||||||||||||||||||||||
2002~2003 | |||||||||||||||||||||||||||||||||||
月-日 Month-day | 11-5 | 11-12 | 11-17 | 11-27 | 3-10 | 3-20 | 3-28 | 4-4 | 4-9 | 4-27 | 5-11 | ||||||||||||||||||||||||
年内天数 Day of the year | 309 | 316 | 321 | 331 | 69 | 79 | 87 | 94 | 99 | 117 | 131 |
图1 SAIL-PROSPECT模型模拟的LAI-NDVI曲线与实测情况(右图为实测数据:张仁华,山东禹城,1987~1991,小麦(1996))
Fig.1 Relationship between LAI and NDVI simulated by SAIL-PROSPECT model compared with measured situation (The curve in right firure is measured situation: Zhang Renhua, Yucheng Shandong, 1987-1991, wheat (1996))
出苗期(DOY) Emergence date | 模拟开花期(DOY) Simulated anthsis date | 模拟成熟期(DOY) Simulated mature date | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
a | e | ri | e | nri | e | ari | e | nri | e | ari | e |
275 | -33 | 324 | 16 | - | - | - | - | - | - | - | - |
288 | -20 | 312 | 4 | 106 | -10 | 117 | 1 | 148 | -5 | 154 | 1 |
293 | -15 | 308 | 0 | 110 | -6 | 116 | 0 | 150 | -3 | 153 | 0 |
298 | -10 | 306 | -2 | 112 | -4 | 115 | -1 | 151 | -2 | 152 | -1 |
303 | -5 | 303 | -5 | 114 | -2 | 115 | -1 | 152 | -1 | 152 | -1 |
308 | 0 | 305 | -3 | 116 | 0 | 115 | -1 | 153 | 0 | 152 | -1 |
313 | 5 | 306 | -2 | 118 | 2 | 115 | -1 | 154 | 1 | 152 | -1 |
318 | 10 | 311 | 3 | 119 | 3 | 117 | 2 | 155 | 2 | 154 | 1 |
320 | 12 | 312 | 4 | 120 | 4 | 117 | 1 | 156 | 2 | 154 | 1 |
表2 利用遥感信息对出苗期重新初始化后模拟冬小麦发育期的误差(郑州,2002~2003)
Table 2 Errors of simulated development stage of winter wheat after re-initializing emergence date by remote sensing data (Zhengzhou,2002-2003)
出苗期(DOY) Emergence date | 模拟开花期(DOY) Simulated anthsis date | 模拟成熟期(DOY) Simulated mature date | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
a | e | ri | e | nri | e | ari | e | nri | e | ari | e |
275 | -33 | 324 | 16 | - | - | - | - | - | - | - | - |
288 | -20 | 312 | 4 | 106 | -10 | 117 | 1 | 148 | -5 | 154 | 1 |
293 | -15 | 308 | 0 | 110 | -6 | 116 | 0 | 150 | -3 | 153 | 0 |
298 | -10 | 306 | -2 | 112 | -4 | 115 | -1 | 151 | -2 | 152 | -1 |
303 | -5 | 303 | -5 | 114 | -2 | 115 | -1 | 152 | -1 | 152 | -1 |
308 | 0 | 305 | -3 | 116 | 0 | 115 | -1 | 153 | 0 | 152 | -1 |
313 | 5 | 306 | -2 | 118 | 2 | 115 | -1 | 154 | 1 | 152 | -1 |
318 | 10 | 311 | 3 | 119 | 3 | 117 | 2 | 155 | 2 | 154 | 1 |
320 | 12 | 312 | 4 | 120 | 4 | 117 | 1 | 156 | 2 | 154 | 1 |
图3 利用遥感数据对出苗期重新初始化后的模拟叶面积指数(LAI)和总干重(郑州,2002~2003) a. 按实际出苗期模拟Simulating with measured emergence date b. 按假定出苗期模拟Simulating with assumed emergence date c. 重新初始化后模拟Simulating with re-initializing emergence date
Fig.3 Simulated LAI and gross above-ground dry matter weight after re-initializing emergence date by remote sensing data (Zhengzhou, 2002-2003)
图4 利用遥感数据重新初始化冬小麦返青期生物量后的模拟结果与实测值(郑州,2002~2003) nri, ari: 同表2 See Table 2 m: 实测 Measurement
Fig.4 Simulated results after re-initializing emergence date by remote sensing data and measured values (Zhengzhou, 2002-2003)
项目 Items | 平均拟合优度 Average goodness of fit | 相对误差 Relative error(%) | ||||||
---|---|---|---|---|---|---|---|---|
nri | SAVI-2 | SAVI-4 | SAVI-7 | nri | SAVI-2 | SAVI-4 | SAVI-7 | |
a | 0.352 | 0.826 | 0.559 | 0.559 | 24.42 | 14.65 | 15.26 | 15.26 |
b | 0.348 | 0.893 | 0.634 | 0.634 | 16.06 | 52.81 | 42.32 | 42.32 |
c | 0.436 | 1.203 | 0.872 | 0.872 | 32.4 | 4.56 | 9.78 | 9.78 |
d | 0.304 | 0.308 | 0.295 | 0.295 | 18.16 | 17.7 | 15.91 | 15.91 |
e | 0.397 | 0.572 | 0.348 | 0.348 | 31.66 | 24.53 | 15.8 | 15.8 |
f | 0.367 | 0.760 | 0.545 | 0.545 | 24.54 | 22.85 | 19.81 | 19.81 |
表3 利用不同次数遥感数据重新初始化返青期生物量后模拟 Q ? 值与相对误差值(郑州,2003)
Table 3 Average goodness of fit ( Q ? ) and relative error of simulated results after dynamic re-initializing emergence date by remote sensing data for different times (Zhengzhou, 2003)
项目 Items | 平均拟合优度 Average goodness of fit | 相对误差 Relative error(%) | ||||||
---|---|---|---|---|---|---|---|---|
nri | SAVI-2 | SAVI-4 | SAVI-7 | nri | SAVI-2 | SAVI-4 | SAVI-7 | |
a | 0.352 | 0.826 | 0.559 | 0.559 | 24.42 | 14.65 | 15.26 | 15.26 |
b | 0.348 | 0.893 | 0.634 | 0.634 | 16.06 | 52.81 | 42.32 | 42.32 |
c | 0.436 | 1.203 | 0.872 | 0.872 | 32.4 | 4.56 | 9.78 | 9.78 |
d | 0.304 | 0.308 | 0.295 | 0.295 | 18.16 | 17.7 | 15.91 | 15.91 |
e | 0.397 | 0.572 | 0.348 | 0.348 | 31.66 | 24.53 | 15.8 | 15.8 |
f | 0.367 | 0.760 | 0.545 | 0.545 | 24.54 | 22.85 | 19.81 | 19.81 |
图5 利用不同时次遥感数据对冬小麦返青期生物量重新参数化后的模拟LAI、地上总干重与实测值(郑州,2003) 2: 2次数据 Using remote sensing data twice 4: 4次数据Using remote sensing data four 7: 7次数据Using remote sensing data seven nri:同表2 See Table 2, m: 同图4 See Fig.4
Fig.5 Comparison of measured and Simulated LAI and gross above-ground dry matter weight after dynamic re-initializing emergence date by remote sensing data in different times (Zhengzhou, 2003)
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