中高分辨率遥感协同反演冬小麦覆盖度

为了开展高精度、高时空分辨率的植被覆盖度(fraction vegetation cover,FVC)监测,该文以华北地区冬小麦地为研究对象,采用4期高分一号卫星多光谱(GF1-PMS)、多光谱宽幅(GF1-WFV)与环境一号卫星多光谱(HJ1-CCD)3种传感器同期影像数据集,基于像元二分法模型,研究多源中高分辨率遥感影像协同估算FVC方法。以基于高空间分辨率GF1-PMS影像反演的FVC作为检验数据,对单源直接获取法、多源全生育期法、多源分期法3种反演模型进行了分析比较。研究结果表明:HJ1-CCD、GF1-WFV数据与GF1-PMS数据的FVC直接反演结果具有较高的一致性,但在冬小麦的初...

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Published in农业工程学报 Vol. 33; no. 16; pp. 161 - 167
Main Author 孙中平 刘素红 姜俊 白雪琪 陈永辉 朱程浩 郭文婷
Format Journal Article
LanguageChinese
Published 遥感科学国家重点实验室,北京师范大学地理科学部,北京100875 2017
环境保护部卫星环境应用中心,北京100094%遥感科学国家重点实验室,北京师范大学地理科学部,北京100875%环境保护部卫星环境应用中心,北京,100094%北京林业大学精准林业北京市重点实验室,北京,100083
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ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2017.16.021

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Summary:为了开展高精度、高时空分辨率的植被覆盖度(fraction vegetation cover,FVC)监测,该文以华北地区冬小麦地为研究对象,采用4期高分一号卫星多光谱(GF1-PMS)、多光谱宽幅(GF1-WFV)与环境一号卫星多光谱(HJ1-CCD)3种传感器同期影像数据集,基于像元二分法模型,研究多源中高分辨率遥感影像协同估算FVC方法。以基于高空间分辨率GF1-PMS影像反演的FVC作为检验数据,对单源直接获取法、多源全生育期法、多源分期法3种反演模型进行了分析比较。研究结果表明:HJ1-CCD、GF1-WFV数据与GF1-PMS数据的FVC直接反演结果具有较高的一致性,但在冬小麦的初期生长阶段,受卫星观测角度效应的影响,GF1-WFV与HJ1-CCD的FVC结果偏高,偏差随冬小麦的成熟封垄而逐渐减弱;多源分期法的时空反演得到的FVC精度最高,GF1-WFV的决定系数为0.984,均方根误差为0.030;HJ1-CCD的决定系数为0.978,均方根误差为0.034;而在缺少GF1-PMS匹配数据时,可通过多源全生育期法提高GF1-WFV与HJ1-CCD数据的反演精度,GF1-WFV的决定系数为0.964,均方根误差为0.044;HJ1-CCD的决定系数为0.950,均方根误差为0.052。通过多传感器的联合反演获取时间序列的高精度的FVC数据,可为研究植被生长状况及生态环境动态变化提供数据基础。
Bibliography:11-2047/S
remote sensing; crops; monitoring; multi-source; fraction vegetation cover; winter wheat; dimidiate pixel model; GF-1
Fraction vegetation cover(FVC)can be used to indicate the growing status of vegetation,which is an important input for some ecological models,hydrological models,meteorological models,and so on.And FVC data set with high precision,high temporal resolution,and high spatial resolution is critical to global change monitoring.Unfortunately,current FVC products are produced using only one kind of remote sensing image,and thus their spatial coverage and temporal coverage are limited.Aiming at acquiring continuous FVC data in space and time,we explored the estimation methods of FVC of winter wheat in North China Plain using high and medium resolution images jointly.This study focused on dimidiate pixel model by combining multi-source images including GF1-PMSimages with spatial resolution of 8m,GF1-WFVwithspatial resolution of 16 m,and HJ1-CCD with spatial resolution of 30 m.Four phases of rem
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2017.16.021