CAJ | 학술논문

选择以水稻为传统优势粮食产业的江苏省作为研究区,采用MODIS09数据作为数据源,根据水稻移栽期稻田土壤湿度较大的特点,利用不同植被指数间的关系,按照一定的算法排除地表干扰像元,提取水稻像元,并在此基础上结合统计资料,分析水稻单产与提取的水稻植被指数之间的关系,并利用水稻植被指数预测全省水稻单产.研究表明,在条件时间序列插值算法(CTIF)处理的基础上提取水稻像元,并基于提取的水稻像元进行遥感估产的方法能取得较好的估算效果.拟合的2004-2006年单产平均精度高于99%,预测的2007年各地级市水稻单产精度在95%左右,全省平均单产相对误差为0.38%,精度较高,具有一定可行性,可利用该方法对不同年份和不同地区进行水稻产量估算.
선택이수도위전통우세양식산업적강소성작위연구구,채용MODIS09수거작위수거원,근거수도이재기도전토양습도교대적특점,이용불동식피지수간적관계,안조일정적산법배제지표간우상원,제취수도상원,병재차기출상결합통계자료,분석수도단산여제취적수도식피지수지간적관계,병이용수도식피지수예측전성수도단산.연구표명,재조건시간서렬삽치산법(CTIF)처리적기출상제취수도상원,병기우제취적수도상원진행요감고산적방법능취득교호적고산효과.의합적2004-2006년단산평균정도고우99%,예측적2007년각지급시수도단산정도재95%좌우,전성평균단산상대오차위0.38%,정도교고,구유일정가행성,가이용해방법대불동년빈화불동지구진행수도산량고산.
Based on the unique characteristic of high soil moisture in the "flooding and transplanting" period of rice, rice pixels in Jiangsu Province, China were extracted by vegetation index algorithm. The unique characteristic could be reflected by relationship between different vegetation indexes derived from MODIS09 data. Then, the relationship between statistical yield data and vegetation index of rice extracted previously in 2004-2006 was analyzed. Finally, rice yield in 2007 was predicted. The results showed that the method based on MODIS data can estimate yield effectively. The accuracy of predicted yield of each city in 2007 was about 95% and the relative error was 0.38% at the provincial level.