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遥感技术与应用  2020, Vol. 35 Issue (2): 406-415    DOI: 10.11873/j.issn.1004-0323.2020.2.0406
遥感应用     
基于CASA-WOFOST耦合模型的大豆单产遥感估算研究
纪甫江1,2(),蒙继华1(),方慧婷1,2
1.中国科学院空天信息创新研究院 数字地球重点实验室,北京 100101
2.中国科学院大学,北京 100049
Study on Soybean Yield Estimation Using the CoupledCASA and WOFOST Model
Fujiang Ji1,2(),Jihua Meng1(),Huiting Fang1,2
1.Key Laboratory of Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101 China
2.University of Chinese Academy of Sciences, Beijing, 100049 China
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摘要:

中国是一个农业大国,在田块甚至是亚田块尺度上进行快速、准确的作物产量估算,不仅可以对农民田间管理进行指导,对于农田生态系统对全球变化的响应评价、制定科学合理的粮食政策、对外粮食贸易和国家粮食安全都具有重要意义。目前主流的估产模型主要有经验统计模型、光能利用率模型、作物生长模型等,每一类模型在各自研究领域相对完整,但是都形成了固定的局限性,为了研究利用遥感技术在小区域范围内田块尺度的作物估产,选取黑龙江省双山农场为研究区,以大豆为研究对象,基于CASA-WOFOST耦合估产模式,利用覆盖作物生长季的时间序列HJ-1A/B遥感影像数据构建高时间分辨率归一化植被指数(Normalized Difference Vegetation Index, NDVI),实现逐日连续监测,分别利用CASA模型和CASA-WOFOST耦合模型对作物进行单产模拟,结果表明:耦合得到的新模型能够具有光能利用率模型较高的运行速度,同时还能发挥作物生长模型模型的机理优势,克服CASA模型在小区域田块尺度上应用的局限性。大豆单产模拟线性回归判定系数(R2)由0.668 53上升到0.844 72,均方根误差(RMSE) 由51.41 kg/hm2下降到29.52 kg/hm2,说明耦合后的模型可以综合考虑光能利用与作物生长生态生理全过程,从而提高作物估产的精度、可靠性和稳定性,为区域田块尺度作物估产提供理论支持,更好地服务于精准农业发展。

关键词: CASA?WOFOST模型单产估算遥感高时间分辨率NDVI    
Abstract:

China is an agricultural country. Yield estimating on field scales rapidly and accurately is not only instructional to farmers’ field management, but also important for the response evaluation of farmland ecosystems to climate change, making scientific and rational food policies, external food trade and so on. The current primary estimation models include empirical statistical model, light use efficiency model, and crop growth model. Each type of model is relatively complete in its individual research filed, but all of them have certain amount of limitations. Remote sensing technology was used to estimate crop yield on a field scale within small regional areas. A farm of Heilongjiang Province was selected as the study area, and the soybean was as the research object. Based on the coupled CASA-WOFOST model and time-series HJ-1A/B remotely sensed data which covering the entire growing season of soybean to generate high temporal resolution Normalized Difference Vegetation Index (NDVI), we achieved daily continuous monitoring of crop and simulating crop yield by CASA model and CASA-WOFOST model respectively. The results indicated that the coupled model had a faster running speed of the light use efficiency model, it could also give full play to mechanism advantages of crop growth model and overcome the limitations of the CASA model applied to field scales. The R2 of soybean yields increased from 0.668 53 to 0.844 72 and RMSE decreased from 51.41 to 29.52 kg/ha. It is indicated that the coupled mode of light use efficiency model and crop growth model could simultaneously consider the light utilization and the whole physiological and ecological process of crop growth. So that the coupled model could improve the precision, reliability, and stability of crop yield estimation, and provide theoretical support for the estimation of crop yields in regional field scales and better serve the development of precision agriculture.

Key words: CASA-WOFOST coupled model    Yield estimation    Remote sensing    High temporal resolution NDVI
收稿日期: 2018-12-29 出版日期: 2020-07-10
ZTFLH:  S2  
基金资助: 国家自然科学基金面上项目(41871261);高分辨率对地观测系统重大专项(30?Y20A03?9003?17/18);绿洲生态农业重点实验室开放课题(201701)
通讯作者: 蒙继华     E-mail: jifj@radi.ac.cn;mengjh@radi.ac.cn
作者简介: 纪甫江(1997-)男,江西抚州人,硕士研究生,主要从事农业与生态环境遥感研究。E?mail: jifj@radi.ac.cn
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引用本文:

纪甫江,蒙继华,方慧婷. 基于CASA-WOFOST耦合模型的大豆单产遥感估算研究[J]. 遥感技术与应用, 2020, 35(2): 406-415.

Fujiang Ji,Jihua Meng,Huiting Fang. Study on Soybean Yield Estimation Using the CoupledCASA and WOFOST Model. Remote Sensing Technology and Application, 2020, 35(2): 406-415.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.2.0406        http://www.rsta.ac.cn/CN/Y2020/V35/I2/406

图1  双山农场位置及地块分布
影像编号获取时间成像传感器轨道编号影像质量
N12016-05-22HJ-1B CCD1451-53
N22016-06-01HJ-1A CCD2450-56
N32016-06-27HJ-1B CCD2449-56良(薄云)
N42016-07-06HJ-1B CCD1449-55良(薄云)
N52016-07-19HJ-1B CCD1453-53
N62016-07-31HJ-1B CCD1450-53
N72016-08-20HJ-1B CCD2452-56
N82016-09-30HJ-1B CCD2450-56良(薄云)
表1  研究区时间序列HJ-CCD数据列表
图2  研究方法流程图
图3  大豆NDVI时间序列曲线图
参数名称参数定义数值单位
TSUM1出苗到开花所需积温1 062.39
TSUM2开花到成熟所需积温1 230.94
Q10温度升10 ℃呼吸消耗相对变化量2
FO1(DVS=0.1)DVS=0.1存储器官分配系数0kg/kg
FO2(DVS=0.5)DVS=0.5存储器官分配系数0kg/kg
FO3(DVS=1.1)DVS=1.1存储器官分配系数0.23kg/kg
FO4(DVS=1.7)DVS=1.7存储器官分配系数0.76kg/kg
CVL叶片干物质转换效率0.76kg/kg
CVS茎干物质转换效率0.72kg/kg
CVO存储器官干物质转换效率0.45kg/kg
CVR根干物质转换效率0.76kg/kg
表2  WOFOST模型参数标定值
图4  大豆单产模拟结果分布图
图5  大豆单产统计像元值频率分布直方图
地块名称实测单产/(kg/hm2)CASA模型/(kg/hm2)CASA-WOFOST模型/(kg/hm2)CASA模型CASA-WOFOST模型
绝对误差(kg/hm2)相对误差绝对误差(kg/hm2)相对误差
一队大头1 713.621 644.471 704.2569.144.20%9.370.55%
一分部1#1 704.571 730.421 696.5025.841.49%8.080.48%
一队副4#1 823.641 807.281 763.2616.360.91%60.383.42%
一队4#下1 662.371 779.451 705.93117.076.58%43.552.55%
一队5#3区1 863.631 793.761 872.8569.873.89%9.220.49%
一队三条田1 731.701 690.881 723.1640.822.41%8.540.50%
一队2#上1 693.521 643.581 665.9549.943.04%27.571.65%
一队7#1 773.401 788.881 818.4615.480.87%45.062.48%
一队8#1 694.531 701.441 729.986.920.41%35.452.05%
一分部10#1 805.051 725.681 779.3179.364.60%25.741.45%
一分部9#1 544.821 504.081 594.7040.742.71%49.883.13%
二分部2#1 762.851 721.711 817.0041.142.39%54.152.98%
一队6#南1 962.801 968.481 992.675.690.29%29.881.50%
一分部2#1 660.871 592.081 667.8668.784.32%7.000.42%
一队10#1 783.951 653.801 727.90130.147.87%56.053.24%
一队11#1 734.721 670.501 715.7764.223.84%18.951.10%
一队5#1区1 835.191 793.541 840.1541.662.32%4.960.27%
一队12#1 766.871 832.171 763.1265.303.56%3.750.21%
一队5#2区1 807.061 815.551 814.288.490.47%7.220.40%
一队5#大区1 593.051 664.251 678.6671.204.28%85.625.10%
表3  地块尺度下双山农场基地2016年大豆单产模拟精度分析
图6  单产模拟结果精度分析
精度评价指标CASA模型CASA-WOFOST模型
均方根误差(RMSE)/(kg/hm2)61.3937.31
Nash-Sutcliffe效率系数0.6140.813
线性回归判定系数(R2)0.668 530.844 72
绝对误差/(kg/hm2)51.4129.52
相对误差3.021.70
表4  双山农场基地2016年大豆单产模拟精度分析
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