首页 >  2004, Vol. 8, Issue (6) : 551-569

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全文摘要次数: 5125 全文下载次数: 37
引用本文:

DOI:

10.11834/jrs.20040605

收稿日期:

2003-09-30

修改日期:

2003-12-12

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基于两个独立抽样框架的农作物种植面积遥感估算方法
中国科学院 遥感应用研究所,北京 100101
摘要:

通过分析遥感技术在中国农作物种植面积估算中所遇到的难点 ,针对运行化的农作物遥感估产系统对主要农作物种植面积估算的需求 ,提出在农作物种植结构区划的基础上 ,采用整群抽样和样条采样技术相结合的方法 ,进行农作物种植面积估算。整群抽样技术利用遥感影像估算农作物总种植成数 ,样条采样是一种适合中国农作物种植结构特征的采样技术 ,用于调查不同农作物类别在所有播种作物中的分类成数。在中国现有的耕地数据库基础上 ,根据两次抽样获得的成数 ,计算得到具体某一种农作物类别的种植面积。最后给出了 2 0 0 3年早稻种植面积估算的实例。

Crop Acreage Estimation Using Two Individual Sampling Frameworks with Stratification
Abstract:

Crop plots are very small in China due to special farm-use rules.Image classification techniques are limited in crop acreage survey using remote sensing.In this paper,we analyze this problem and provide a substitute methodology to estimate crop acreage. In this methodology,crop statification is fundamentd.Proportional of main crop types as well as physical factors of temperature,precipitation,soil type and sun radiation are considered.There are about 11 strata in China at the first level based on physical factors,44 strata at the second level based on crop proportion and 102 strata at the third level based on arable land intensity. Two indicidual sampling frameworks are uesd.The cluster sampling is used to estimate the proportion of planted area on arable land with remote sensing data,mostly Landsat and Radarsat data,currently also ENVISAT ASAR data are used.The clusters are defined as a map sheet at a scale of 1:1:100 000 (about1/16 Landsat TM scene).And images are selected based on cluster sample randomly for each crop season.After atmospheric correction,geometric correction nonarable land masking,remotely sensed images are classified by ISODATA unsuoervised classification,and then the planted areas are labeled by considering NDVI value.The planted area proportions are calculated for each stratum. The transect sampling framework is used to estimate the proportions of different crop type within planted area.To identify the crop proportion of a small parcel,field works should be used since it is impossible to make crop classfication with remote sensing data cost-effectively.The transect sampling actually is a two-stage sampling.In the first stage,PSUs are selected randomly on a 4km*4km area frame.In the second stage,the selected PSUs are sampled only along the road within PSUs,called transect line.The sampling works in the field are to take pictures along the road within PSUs with 100m buffer,and a GVC system is designed for this purpose.Proportions of every crop type are calculated for each stratum. Crop acreages are calculated under the support of current arable database.For every crop type,the palnted acreage is the arable area multiply by planted proportion and crop type proportion of syratum. The estimation of early rice acreage in 2003 in China is presented as a case syudy.Results show this methodology is feasible.This methodology has adopted in China since 1998.And the experience shows that the stratification schema is efficiency,and the two individual sample frameworks can generate accurate estimation of crop acreage.

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