A logistic-based method for rice monitoring from multi-temporal MODIS-landsat fusion data

Nguyen Thanh Son, Chi Farn Chen, Ly Yu Chang, Cheng Ru Chen, Shin Ichi Sobue, Vo Quang Minh, Shou Hao Chiang, Lam Dao Nguyen, Ya Wen Lin

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Information on rice cropping activities and growing areas is critical for crop management. This study developed a logistic-based method to monitor rice sowing and harvesting activities and, accordingly, to map rice growing areas from the MODIS–Landsat fusion data in An Giang Province, Vietnam. The EVI2 data derived from the fusion data compared with that of Landsat data indicated a close correlation (R2 = 0.93). The comparisons between the estimated sowing and harvesting dates and the field survey data revealed the RMSE values of around 8 and 5 days for the winter–spring crop and 9 and 12 days for the summer–autumn crop, respectively. The rice mapping results compared with the ground reference data indicated an overall accuracy and Kappa coefficient of 93.2% and 0.86 for the winter–spring crop, and 91.7% and 0.83 for the summer–autumn crop, respectively. These results were reaffirmed by the government’s rice areas statistics, with the relative error in area values smaller than 3.3%.

Original languageEnglish
Pages (from-to)39-56
Number of pages18
JournalEuropean Journal of Remote Sensing
Volume49
DOIs
StatePublished - 4 Mar 2016

Keywords

  • Data fusion
  • Double logistic
  • Rice monitoring
  • Vietnam

Fingerprint

Dive into the research topics of 'A logistic-based method for rice monitoring from multi-temporal MODIS-landsat fusion data'. Together they form a unique fingerprint.

Cite this