Application of principal component analysis to MODIS ndvi for estimation of paddy rice yields in gyeonggi, South Korea

Minyoung Jung, Youkyung Han, Yongil Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

MODIS NDVI is generally used for the estimation of various kinds of crop yields including paddy rice. Efforts have been made to estimate paddy rice yield using MODIS NDVI and meteorological data in Korea. However, the choice of a representative MODIS NDVI as an independent variable for the model to estimate paddy rice yields is ambiguous due to high correlations among multi-temporal MODIS NDVI data. This study proposed a method to produce representative values from MODIS NDVI by applying a PCA technique. The method was used to develop an estimation model for paddy rice yield in Gyeonggi, one of the South Korea provinces. Application of this PCA method increased the correlation between the representatives and rice yields from 0.411 to 0.524. The robustness was also improved, as the RMSE of the models decreased from 17.32% to 5.05% by comparing estimations and actual statistics from 2012.

Original languageEnglish
Title of host publication34th Asian Conference on Remote Sensing 2013, ACRS 2013
PublisherAsian Association on Remote Sensing
Pages3281-3287
Number of pages7
ISBN (Print)9781629939100
StatePublished - 2013
Event34th Asian Conference on Remote Sensing 2013, ACRS 2013 - Bali, Indonesia
Duration: 20 Oct 201324 Oct 2013

Publication series

Name34th Asian Conference on Remote Sensing 2013, ACRS 2013
Volume4

Conference

Conference34th Asian Conference on Remote Sensing 2013, ACRS 2013
Country/TerritoryIndonesia
CityBali
Period20/10/1324/10/13

Keywords

  • Crop yield model
  • MODIS NDVI
  • Principal component analysis

Fingerprint

Dive into the research topics of 'Application of principal component analysis to MODIS ndvi for estimation of paddy rice yields in gyeonggi, South Korea'. Together they form a unique fingerprint.

Cite this