基于环境卫星数据的水稻面积空间抽样研究
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摘要
如何及时、准确地获取农作物的种植面积历来都是国家统计部门的研究重点之一。常规的统计学方法因其固有的局限性已无法满足现代农业统计工作对效率与精度的需求;遥感信息提取技术的不确定性也导致其无法独立完成具备完善统计学意义的面积测量工作。综合二者优势发展起来的空间抽样技术在农作物种植面积测算方面已得到广泛应用。但是,对大尺度研究区,由于遥感技术还不够成熟以及天气的影响,无法准确获得现势全覆盖的遥感影像。对此,如何综合二者优势利用遥感数据资源进行农作物种植面积测量,是解决我国农情遥感预报的关键所在。
本文根据大范围水稻种植面积遥感测量业务化运行要求,针对现阶段研究中遥感数据获取的问题及遥感作为辅助数据对抽样方法和总体精度之间相互制约与影响的关系,选择典型的研究区,采用环境卫星遥感数据作为辅助数据源,以分层抽样为核心,研究探讨种植结构复杂的大范围水稻种植面积空间抽样调查的方法体系。研究过程中,环境遥感数据提供抽样总体及分层参数,增强分层抽样的可信度,并以野外调查样本和高分辨率空间样方提高样本的可靠性。研究结果表明:
(1)环境卫星(HJ-A/B)进行大尺度的监测农作物种植面积,其高时间分辨率可以弥补其数据质量上与Landsat-TM数据在质量上存在的差异,解决了农作物种植面积测量时遥感数据受云雾雪等天气影响难以获取的问题。同时其700km的幅宽避免了数据预处理时裁剪拼接中产生的误差,为农作物种植面积的遥感监测和抽样估计提供了一种新的数据源。结合耕地地块和野外调查资料的ISODATA非监督分类方法可以有效地从环境卫星数据中获取研究区的水稻种植范围,为空间抽样提供抽样总体。
(2)分层抽样采用的分层因子与调查目标之间的相关性直接影响分层抽样设计的效率。使用历史遥感数据生成的分层因子或者现势遥感数据分层因子与调查目标间的空间相关性较弱,在达到相同抽样精度的情况下,需要比使用高质量的数据源提供更多的样本。研究表明景观特征边缘密度(Li)优于抽样框内面积直接作为分层因子的分层抽样,有效地提高抽样效率和实际调查的工作效率。
(3)在我国各省复杂的水稻种植结构下,采用基于遥感数据的分区及分层与实际调查目标相关性高,抽样样本数量和结构都得到了优化,同时引入高分辨率遥感数据辅助调查可以减少野外工作量,及时准确地提供实时预报,为政府部门决策提供重要的参考依据。
How to timely and accurately access the crop area has been the focus of the study of the national statistical office. The normal statistical techniques can no longer meet the needs of current agricultural statistical work for efficiency and accuracy due to its inherent limits. The uncertain characteristics of remote sensing information also make it unable to independently fulfill area estimation in the sense of statistics. Which integrate the strengths of both statistics and remote sensing are being widely used. However, the remote sensing technology is not mature enough, and sometimes it is unable to obtain the full coverage of the remote sensing images, which cannot be used to provide the basis for sampling. At this moment, how to take full advantage of the remote sensing images to build a sample survey program is the key of the crop area survey for China Crop Watch System with Remote Sensing.
According to a wide range of remote sensing measurements of rice planting area requirements, This paper aims at the mutual limits and affects among the problem of remote sensing data acquisition and the overall accuracy of the sampling method, and takes HJ remote sensing images as auxiliary data for the stratified sampling methods.
The spatial sampling plan for rice planting area estimation in the study site was designed, and then applied the more relevant parameters in the design stage and the estimate stage of the spatial sampling. Following are the conclusions drawn from this study:
(1) HJ remote sensing images provides a new data source for the crop planting area of remote monitoring. The same resolution and high time resolution can make up for quality with the Landsat-TM data. While the width of its 700km is good for wide range of remote monitoring.
(2) The correlations between stratified parameters and survey objects will directly affect the efficiency of stratification. The use of images in the past or the stratified parameters of HJ images with weak correlation other than the most ideal ones will degrade correlations, decrease the efficiency of stratification and need more samples for survey. The results also show that landscape features Edge Density (Li) is better than area directly as a stratified sampling frame.
(3) The spatial stratified sampling methods based on the HJ remote sensing images and Field survey plots can effectively improve efficiency and sampling accuracy. Provide timely and accurate real-time forecasting, and decision-making for government departments.
本文根据大范围水稻种植面积遥感测量业务化运行要求,针对现阶段研究中遥感数据获取的问题及遥感作为辅助数据对抽样方法和总体精度之间相互制约与影响的关系,选择典型的研究区,采用环境卫星遥感数据作为辅助数据源,以分层抽样为核心,研究探讨种植结构复杂的大范围水稻种植面积空间抽样调查的方法体系。研究过程中,环境遥感数据提供抽样总体及分层参数,增强分层抽样的可信度,并以野外调查样本和高分辨率空间样方提高样本的可靠性。研究结果表明:
(1)环境卫星(HJ-A/B)进行大尺度的监测农作物种植面积,其高时间分辨率可以弥补其数据质量上与Landsat-TM数据在质量上存在的差异,解决了农作物种植面积测量时遥感数据受云雾雪等天气影响难以获取的问题。同时其700km的幅宽避免了数据预处理时裁剪拼接中产生的误差,为农作物种植面积的遥感监测和抽样估计提供了一种新的数据源。结合耕地地块和野外调查资料的ISODATA非监督分类方法可以有效地从环境卫星数据中获取研究区的水稻种植范围,为空间抽样提供抽样总体。
(2)分层抽样采用的分层因子与调查目标之间的相关性直接影响分层抽样设计的效率。使用历史遥感数据生成的分层因子或者现势遥感数据分层因子与调查目标间的空间相关性较弱,在达到相同抽样精度的情况下,需要比使用高质量的数据源提供更多的样本。研究表明景观特征边缘密度(Li)优于抽样框内面积直接作为分层因子的分层抽样,有效地提高抽样效率和实际调查的工作效率。
(3)在我国各省复杂的水稻种植结构下,采用基于遥感数据的分区及分层与实际调查目标相关性高,抽样样本数量和结构都得到了优化,同时引入高分辨率遥感数据辅助调查可以减少野外工作量,及时准确地提供实时预报,为政府部门决策提供重要的参考依据。
How to timely and accurately access the crop area has been the focus of the study of the national statistical office. The normal statistical techniques can no longer meet the needs of current agricultural statistical work for efficiency and accuracy due to its inherent limits. The uncertain characteristics of remote sensing information also make it unable to independently fulfill area estimation in the sense of statistics. Which integrate the strengths of both statistics and remote sensing are being widely used. However, the remote sensing technology is not mature enough, and sometimes it is unable to obtain the full coverage of the remote sensing images, which cannot be used to provide the basis for sampling. At this moment, how to take full advantage of the remote sensing images to build a sample survey program is the key of the crop area survey for China Crop Watch System with Remote Sensing.
According to a wide range of remote sensing measurements of rice planting area requirements, This paper aims at the mutual limits and affects among the problem of remote sensing data acquisition and the overall accuracy of the sampling method, and takes HJ remote sensing images as auxiliary data for the stratified sampling methods.
The spatial sampling plan for rice planting area estimation in the study site was designed, and then applied the more relevant parameters in the design stage and the estimate stage of the spatial sampling. Following are the conclusions drawn from this study:
(1) HJ remote sensing images provides a new data source for the crop planting area of remote monitoring. The same resolution and high time resolution can make up for quality with the Landsat-TM data. While the width of its 700km is good for wide range of remote monitoring.
(2) The correlations between stratified parameters and survey objects will directly affect the efficiency of stratification. The use of images in the past or the stratified parameters of HJ images with weak correlation other than the most ideal ones will degrade correlations, decrease the efficiency of stratification and need more samples for survey. The results also show that landscape features Edge Density (Li) is better than area directly as a stratified sampling frame.
(3) The spatial stratified sampling methods based on the HJ remote sensing images and Field survey plots can effectively improve efficiency and sampling accuracy. Provide timely and accurate real-time forecasting, and decision-making for government departments.
引文
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[4]杨邦杰,陆登槐,裴志远,等.国家级农情监测系统结构设计[J].农业工程学报,1997,13(1) :16219.
[5] MacDonald, RB.; Hall, F.G.. Global Crop Forecasting, Science, 16 May 1980, Vol. 208. no. 4445,pp. 670-679.
[6] Baker D N,Smike D E,Black A L,et al.Winter wheat: a model for the simulation of growth and yield in winter wheat.AGRISTARS,A Joint Program for Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing,Publ.Lyndon B Houston:Johnson Space Center,1981.
[7]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): 9-14.
[8] NageswaraP P,RaoV R.Rice crop identification and area estimation using remotely sensed data from Indian cropping patterns [J].International Journal of Remote Sensing,1987,8(4):639-650.
[9] Okamoto K, Kawashima H. Estimation of Rice Land Planted Area in the Tropical Zone using a Combination of Optical and Microwave Satellite Sensor Data [J].International Journal of Remote Sensing,1999,20(5) :1045 -1048.
[10] Hong SY, Lee K S, Rim S K, et al. Estimation of rice field area using two-date Landsat TM images.In: IEEE international geoscience and remote sensing symposium. 1999,6(2): 732-734.
[11]孙九林.中国农作物遥感动态监测与估产总论[M].北京:中国科学技术出版社,1996.
[12]李卫国等.基于模型和遥感的水稻长势监测研究进展[J].中国农学通报,2006, 22 (9): 457-461.
[13]赵锐,王延颐,等.中国水稻遥感动态监测与估产[M].北京:中国科学技术出版社,1996.
[14] Pavi N K, Navalgund R P. Estimation of rice yield using IRS-1A digital data in coastal tract of Orissa [J].International journal of remote sensing, 1991, 12 (11):2259-2266.
[15]张峰,吴炳方.泰国水稻种植面积月变化的遥感监测[J].遥感学报, 2004(11): 664-671.
[16]李红卫等.全球稻谷主产国遥感估产可行性研究[J].应用气象学报,1998(5):251-256.
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