基于抽样调查地块实测数据的省级水稻单产遥感估算

利用统计局抽样调查地块实割实测标准单位面积产量数据及空间位置信息,在研究水稻种植区MOD09GA、MYD09GA EVI(enhanced vegetation index)数据结合使用可行性分析的基础上,进行湖南省省级水稻单产遥感估算。结果表明:在水稻种植区,水稻生长期间有超过50%、85%、95%的MOD09GA与MYD09GA EVI偏差绝对值分别小于0.03、0.08、0.1。水稻遥感估产模型以二次非线性模型或回归模型精度较高,且时相集中在水稻生长的孕穗期到抽穗期。在省级水平上,与实测值相比,基于统计局统计抽样调查地块实割实测标准单位面积产量数据的水稻单产遥感拟合结果相对误差小于2%,...

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Published in农业工程学报 Vol. 27; no. 9; pp. 106 - 114
Main Author 彭代亮 周炼清 黄敬峰 周斌 王福民
Format Journal Article
LanguageChinese
Published 中国科学院对地观测与数字地球科学中心,北京100094%浙江大学农业遥感与信息技术应用研究所,杭州,310058%杭州师范大学遥感与地球科学研究院,杭州,310036%浙江大学建筑工程学院,杭州,310058 2011
浙江大学农业遥感与信息技术应用研究所,杭州310058
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ISSN1002-6819
DOI10.3969/j.issn.1002-6819.2011.09.020

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Summary:利用统计局抽样调查地块实割实测标准单位面积产量数据及空间位置信息,在研究水稻种植区MOD09GA、MYD09GA EVI(enhanced vegetation index)数据结合使用可行性分析的基础上,进行湖南省省级水稻单产遥感估算。结果表明:在水稻种植区,水稻生长期间有超过50%、85%、95%的MOD09GA与MYD09GA EVI偏差绝对值分别小于0.03、0.08、0.1。水稻遥感估产模型以二次非线性模型或回归模型精度较高,且时相集中在水稻生长的孕穗期到抽穗期。在省级水平上,与实测值相比,基于统计局统计抽样调查地块实割实测标准单位面积产量数据的水稻单产遥感拟合结果相对误差小于2%,预测结果的相对误差接近5%,且实测值与模拟值集中分布在1∶1线附近,说明预测结果与统计值在空间分布上具有较好的一致性。
Bibliography:11-2047/S
remote sensing; estimation; statistics; measurements; rice; sampling plots
Peng Dailiang,Zhou Lianqing,Huang Jingfeng,Zhou Bin,Wang Fumin (1.Institute of Agricultural Remote Sensing and Information Application,Zhejiang University,Hangzhou 310058,China;2.Center for Earth Observation and Digital Earth,Chinese Academy of Sciences,Beijing 100194,China;3.Institute of Remote Sensing and Earth Sciences,Hangzhou Normal University,Hangzhou,310036,China;4.College of Architectural and Civil Engineering,Zhejiang University,Hangzhou 310058,China)
Rice yield estimation by remote sensing is very important for making agricultural decisions and food security in China and worldwide. Based on the feasibility analysis of combination of MOD09GA and MYD09GA EVI(enhanced vegetation index), provincial unit rice yield was estimated using rice standard yield per area from statistical sampling survey plots. The results showed that more than 50%, 85% and 95% absolute difference between MOD09GA and MYD09GA EVI for rice sampling pl
ISSN:1002-6819
DOI:10.3969/j.issn.1002-6819.2011.09.020