As a kind of crucial data which was able to reflect the continuous coverage of vegetation on the earth surface, the long time-series MODIS NDVI products have already become a reliable data source used in remote sensing for crop measurement. In this paper, a long time-series and high-resolution (250m) MODIS data in 2008 was used to extract the area of the paddy land in Jiangsu Province, China. In the beginning, an annual time-series NDVI dataset of the study area was built up by pre-processing,and a reconstruction of time-series based on Savitzky-Golay filter provided this study excellent images with the better visual effect and NDVI temporal profile. Considering the paddy phenological calendar, the identifiers of paddy were parameterized as starting time, range, extent, and maximum of NDVI during the growth period. In the end, through comparing the phenological key values, a reasonable classification rule was generated based on the thresholds of phenological key values, and a decision tree classifier was constructed to extract Paddy land area, whose precision was 87.5%. It turned out the feasibilities of long time-series MODIS NDVI data and our classification strategy adapted to the extraction of crop land area.
MIAO Cuicui, JIANG Nan, PENG Shikui, LV Heng, LI Yang, ZHANG Yu, WANG Ni, LI Jun
. Extraction of Paddy Land Area Based on NDVI Time-series Data: Taking Jiangsu Province as an Example[J]. Journal of Geo-information Science, 2011
, 13(2)
: 273
-280
.
DOI: 10.3724/SP.J.1047.2011.00273
[1] 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.
[2] 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).
[3] 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).
[4] 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.
[5] 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
[6] 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.
[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] 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).
[9] Jnsson 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.
[10] 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.
[11] Jin Chen, Per Jnsson, 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.
[12] Savitzky A, Golay M J E. Smoothing and Differentiation of Data by Simpl-ified Least Squares Procedures [J]. Analytical Chemistry, 1964, 36:1627-1639.
[13] Jonsson P and Eklundh L. TIMESAT: A Program for Analyzing Time-series of Satellite Sensor Data[J]. Computers and Geosciences,2004,30,833-845.
[14] 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.
[15] 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).
[16] 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).
[17] 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.
[18] 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.
