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基于NDVI时序数据的水稻种植面积遥感监测分析——以江苏省为例

DOI: 10.3724/SP.J.1047.2011.00273, PP. 273-280

Keywords: NDVI时间序列,S-G滤波,生长周期关键值,决策树分类

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Abstract:

MODIS植被指数时间序列产品能够连续反映植被的覆盖情况,是农作物遥感测量的重要数据源。本文选取江苏省为研究区,利用2008年23个时相的MODISNDVI数据,采用S-G滤波法进行时间序列的重构,提高NDVI时间序列信息的真实性。另结合农作物物候历、种植结构、地面调查样本等辅助资料,将水稻植被指数时间序列曲线参量化为水稻物候生长期的关键值——生长周期的起始时间、生长幅度、生长长度以及生长过程的NDVI最大值。最后,利用这些关键值确定分类规则,采取决策树分类器,建立区域水稻种植面积提取模型,总体提取精度为87.5%,其表明MODIS植被指数时序数据及本文研究方法在农作物信息提取中的有效性。

References

[1]  周清波.国内外农情遥感现状与发展趋势[J].中国农业资源与区划,2004,25(5).
[2]  范磊,程永政,刘婷,等.基于MODIS数据的河南省冬小麦长势监测研究[J],河南农业科学,2008(8).
[3]  Young S S and Wang C Y. Land-cover Changes Analysis of China Using Global-scale Pathfinder AVHRR Land Cover (PAL) Data [J]. Int J Remote Sensing, 2001, 22(2):1457-1477.
[4]  Running S W, Loveland T R, Pierce L L, et al. A Remote Sensing Based Vegetation Classification Logic for Global Land Cover Analysis [J]. Remote Sensing of Environment,1995,51(1):39-48
[5]  张明伟,周清波,陈仲新,等. 基于MODIS时序数据分析的作物识别方法 [J].中国农业资源与区划,2008,29(1).
[6]  杨小唤,张香平,江东. 基于MODIS时序NDVI特征值提取多作物播种面积的方法[J].资源科学,2004,26(6).
[7]  Wu B F, Zhang F, Liu C L, et al. An Integrated Method for Crop Condition Monitoring [J]. Journal of Remote Sensing,2004,8(6):498-514.
[8]  Running S W, Loveland T R, Pierce L L, et al. A Remote Sensing Based Vegetation Classification Logic for Global Land Cover Analysis [J]. Remote Sens-ing of Environment, 1995,51(1):39-48.
[9]  唐华俊.农作物空间格局遥感监测研究进展[J].中国农业科学,2010,43(14):2879-2888.
[10]  Reed B C, Brown J F, Vander zee D, et al. Measuring Phonological Variability from Satellite Imagery[J]. Journal of Vegetation Science,1994,5(5):703-710.
[11]  Wu B F, Zhang F, Liu C L, et al. An Integrated Method for Crop Condition Monitoring [J]. Journal of Remote Sensing, 2004,8(6):498-514.
[12]  曹云峰,王正兴,等.3种滤波算法对NDVI高质量数据保真性研究[J].遥感技术与应用,2010,25(1).
[13]  Jnsson P, Eklundh L. Seasonality Extraction by Function-fitting to Time Series of Satellite Sensor Data [J]. IEEE Transactions on Geoscience and Remote Sensing, 2002,40(8):1824-1832.
[14]  Sellers P, Tucker C, Collatz G, et al. A Global 10 by10 NDVI Data Set for Global Studies. Part 2: The Generation of Global Fields of Terrestrial Biophysical Parameters from the NDVI [J]. International Journal of Remote Sensing,1994,15(17):3519-3545.
[15]  Jin Chen, Per Jnsson, Masayuki Tamura, et al. A Simple Method for Reconstructing a High-quality NDVI Time-series Data Set Based on the Savitzky-Golay Filter [J]. Remote Sensing of Environment,2004,91:332-344.
[16]  Savitzky A, Golay M J E. Smoothing and Differentiation of Data by Simpl-ified Least Squares Procedures [J]. Analytical Chemistry, 1964, 36:1627-1639.
[17]  Jonsson P and Eklundh L. TIMESAT: A Program for Analyzing Time-series of Satellite Sensor Data[J]. Computers and Geosciences,2004,30,833-845.
[18]  Jonsson P and Eklundh L. Seasonality Extraction by Function Fitting to Time-series of Satellite Sensor Data[J]. IEEE Transactions on Geosci-ence and Remote Sensing, 2002, 40(8),1824-1832.

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