基于时序MODIS-NDVI的油菜种植面积变化趋势分析——以江汉平原为例

doi:10.11870/cjlyzyyhj201603007

长江流域资源与环境 >> 2016, Vol. 25 >> Issue (03): 412-419.doi: 10.11870/cjlyzyyhj201603007

基于时序MODIS-NDVI的油菜种植面积变化趋势分析——以江汉平原为例

张煦, 马驿, 郑雯, 汪善勤

华中农业大学资源与环境学院农业部长江中下游耕地保育重点实验室, 湖北武汉 430070

收稿日期:2015-07-03 修回日期:2015-09-07 出版日期:2016-03-20
通讯作者: 汪善勤 E-mail:sqwang@mail.hzau.edu.cn
作者简介:张煦(1989~),男,硕士研究生,主要从事作物遥感监测方面研究. E-mail: freedomzx0911@webmail.hzau.edu.cn
基金资助:
十二五农村领域国家科技计划课题(2013AA102401-3)

VARIATION TREND OF RAPE CULTIVATION AREA BASED ON MODIS-NDVI TIME SERIES DATA——A CASE IN JIANGHAN PLAIN

ZHANG Xu, MA Yi, ZHEN Wen, WANG Shan-qin

Resources and Environment College, Huazhong Agricultural University, Key Laboratory of Arable Land Conservation in Middle and Lower Reaches of Yangtze River, Ministry of Agriculture, Wuhan 430070, China

Received:2015-07-03 Revised:2015-09-07 Online:2016-03-20
Supported by:
Twelfth-five Rural Area of National Science and Technology Support Program(2013AA102401-3)

摘要/Abstract

摘要： 油菜是我国主要油料作物,其种植与监测对于保障食油生产安全具有重要意义。本文以江汉平原作为研究区,利用2002~2014年250 m分辨率的MODIS-NDVI时序数据,采用经验模态分解(EMD)方法,结合地面调查数据以及作物物候数据等辅助数据,获取主要地物覆盖类型的端元信息,然后利用线性光谱混合模型(LSMM)进行混合像元分解,得到油菜种植面积丰度的空间分布。结果表明,EMD方法较好地过滤了时序数据的噪声;经年鉴统计数据验证,油菜提取面积精度达到了92.5%以上,R < sup>2大于0.9。油菜种植面积的时空变化结果很好地反映出江汉平原油菜种植面积总体呈增长态势。此外,政策导向和市场价格对油菜种植面积的影响明显。

关键词: 时序MODIS-NDVI, 经验模态分解, 线性光谱混合模型, 江汉平原, 油菜种植面积

Abstract: As the major oil crop in China, rape has gained great significance in terms of the safety of cooking oil production. In this study, the temporal and spatial variation of rape cultivation in the Jianghan Plain, Hubei Province from 2002 to 2014 were investigated utilizing the MODIS NDVI time series data at 250 m resolution. The Empirical Mode Decomposition (EMD) method was used to derive endmembers of land cover types in the study area referring to auxiliary data including ground survey data and crop phenological data. Then, the Linear Spectral Mixture model was used to calculate area abundance in each pixel of decomposition. The spatial distribution of rape cultivation area in each year was then obtained. The results showed that the EMD method well filtered the noise of time series data as verified by yearbook statistics. The accuracy for extracted rape acreage was over 92.5% with R < sup>2 greater than 0.9. Furthermore, the spatial and temporal changes in the rape cultivated area indicated the overall positive growth and significantly effects of government policy and the variance of market price of rapeseed.

Key words: MODIS-NDVI time series data, empirical mode decomposition, linear spectral mixture model, Jianghan Plain, rape cultivation area

中图分类号:

S127

张煦, 马驿, 郑雯, 汪善勤. 基于时序MODIS-NDVI的油菜种植面积变化趋势分析——以江汉平原为例[J]. 长江流域资源与环境, 2016, 25(03): 412-419.

ZHANG Xu, MA Yi, ZHEN Wen, WANG Shan-qin. VARIATION TREND OF RAPE CULTIVATION AREA BASED ON MODIS-NDVI TIME SERIES DATA——A CASE IN JIANGHAN PLAIN[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2016, 25(03): 412-419.

参考文献

[1] 佘宝, 黄敬峰, 石晶晶, 等. 基于红边位置变化特征的油菜种植区域提取[J]. 农业工程学报, 2013, 29(15):145-152.[SHE B, HUANG J F, SHI J J, et al. Extracting oilseed rape growing regions based on variation characteristics of red edge position[J]. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(15):145-152.]
[2] 蔡博峰, 于嵘. 基于遥感的植被长时序趋势特征研究进展及评价[J]. 遥感学报, 2009, 13(6):1170-1186.[CAI B F, YU R. Advance and evaluation in the long time series vegetation trends research based on remote sensing[J]. Journal of Remote Sensing, 2009, 13(6):1170-1186.]
[3] 杨啸. 基于时序NDVI的湖北省植被覆盖动态变化监测分析[J]. 长江流域资源与环境, 2013, 22(2):226-231.[YANG X. Dynamic change monitoring and analysis of vegetation cover in Hubei province based on time series ndvi data[J]. Resources and Environment in the Yangtze Basin, 2013, 22(2):226-231.]
[4] 苏荣瑞, 熊勤学, 耿一风, 等. 利用多时相HJ-CCD影像监测江汉平原南部地区棉花和中稻种植面积[J]. 长江流域资源与环境, 2013, 22(11):1441-1448.[SU R R, XIONG Q X, GENG Y F, et al. Cotton and mid-season rice area extraction based on multi-temporal HJ satellite CCD data in southern Jianghan Plain[J]. Resources and Environment in the Yangtze Basin, 2013, 22(11):1441-1448.]
[5] 许文波, 张国平, 范锦龙, 等. 利用MODIS遥感数据监测冬小麦种植面积[J]. 农业工程学报, 2007, 23(12):144-149.[XU W B, ZHANG G P, FAN J L, et al. Remote sensing monitoring of winter wheat areas using MODIS data[J]. Transactions of the CSAE, 2007, 23(12):144-149.]
[6] REN J Q, CHEN Z X, ZHOU Q B, et al. Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China[J]. International Journal of Applied Earth Observation and Geoinformation, 2008, 10(4):403-413.
[7] CHEN C F, SON N T, CHANG L Y. Monitoring of rice cropping intensity in the upper Mekong Delta, Vietnam using time-series MODIS data[J]. Advances in Space Research, 2012, 49(2):292-301.
[8] 李卫国, 王纪华, 赵春江, 等. 基于TM影像的冬小麦苗期长势与植株氮素遥感监测研究[J]. 遥感信息, 2007(2):12-15, 19.[LI W G, WANG J H, ZHAO C J, et al. Study on monitoring the winter wheat growth and nitrogen based on land-sat TM image[J]. Remote Sensing Information, 2007(2):12-15, 19.]
[9] 彭代亮, 周炼清, 黄敬峰, 等. 基于抽样调查地块实测数据的省级水稻单产遥感估算[J]. 农业工程学报, 2011, 27(9):106-114.[PENG D L, ZHOU L Q, HUANG J F, et al. Rice yield estimation based on MODIS EVI and measured data derived from statistical sampling plots at province level[J]. Transactions of the CSAE, 2011, 27(9):106-114.]
[10] 钱永兰, 杨邦杰, 焦险峰. 基于遥感抽样的国家尺度农作物面积统计方法评估[J]. 农业工程学报, 2007, 23(11):180-187.[QIAO Y L, YANG B J, JIAO X F. Accuracy assessment on the crop area estimating method based on RS sampling at national scale[J]. Transactions of the CSAE, 2007, 23(11):180-187.]
[11] 王立辉, 黄进良, 孙俊英. 基于线性光谱混合模型的油菜种植面积遥感监测方法研究[J]. 遥感信息, 2010(3):61-66.[WANG L H, HUANG J L, SUN J Y. Study on remote sensing monitoring of rape acreage based on linear spectral mixture model[J]. Remote Sensing Information, 2010(3):61-66.]
[12] HUANG N E, SHEN Z, LONG S R. A new view of nonlinear water waves:the Hilbert Spectrum1[J]. Annual Review of Fluid Mechanics, 1999, 31(1):417-457.
[13] HUANG N E, SHEN Z, LONG S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society A, 1998, 454(1971):903-995.
[14] HUANG N E, WU M L, QU W D, et al. Applications of Hilbert-Huang transform to non-stationary financial time series analysis[J]. Applied Stochastic Models in Business and Industry, 2003, 19(3):245-268.
[15] 李二森, 朱述龙, 周晓明, 等. 高光谱图像端元提取算法研究进展与比较[J]. 遥感学报, 2011, 15(4):659-679.[LI E S, ZHU S L, ZHOU X M, et al. The development and comparison of endmember extraction algorithms using hyperspectral imagery[J]. Journal of Remote Sensing, 2011, 15(4):659-679.]
[16] 吕长春, 王忠武, 钱少猛. 混合像元分解模型综述[J]. 遥感信息, 2003(3):55-58, 60.[LV C C, WANG Z W, QIAN S M. A review of pixel unmixing models[J]. Remote Sensing Information, 2003(3):55-58, 60.]
[17] 熊勤学, 胡佩敏. 基于HJ卫星混合像元分解法的湖北省四湖地区夏收作物种植信息提取[J]. 长江流域资源与环境, 2014, 23(6):869-874.[XIONG Q X, HU P M. Extracting planting information of summer harvesting crops in Shihu region from HJ CCD data using unmixing algorithm data[J]. Resources and Environment in the Yangtze Basin, 2014, 23(6):869-874.]
[18] ELMORE A J, MUSTARD J F, MANNING S J, et al. Quantifying vegetation change in semiarid environments:precision and accuracy of spectral mixture analysis and the normalized difference vegetation index[J]. Remote Sensing of Environment, 2000, 73(1):87-102.
[19] WANG L, UCHIDA S. Use of linear spectral mixture model to estimate rice planted area based on MODIS data[J]. Rice Science, 2008, 15(2):131-136.
[20] 《湖北农村统计年鉴》编辑委员会. 湖北农村统计年鉴(2002-2013)[M]. 北京:中国统计出版社, 2002-2013.
[21] 国家统计局农村社会经济调查司. 中国农产品价格调查年鉴(2002-2013)[M]. 北京:中国统计出版社, 2003-2014.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed