Boro Rice Yield Estimation Model Using Modis Ndvi Data for Bangladesh

Md Samiul Alam, Kazi Kalpoma, Md Sanaul Karim, Abdullah Al Sefat, Jun Ichi Kudoh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The aim of this study is to construct a rice yield estimation model for Bangladesh. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) images have been used. The MODIS NDVI images and ground truth data are acquired for the years 2011 to 2016. since Bangladesh is divided into 8 divisions, several regression models are applied to predict rice yield for each division rather than a single model for the entire country, in order to get improved result in rice yield prediction. Firstly the rice field area is predicted by using NDVI threshold values. An improvised algorithm has been implemented to determine the NDVI threshold values. Four regression models (Linear, Ridge, Lasso, Decision Tree) are performed to estimate total Boro production of each district of Bangladesh. Among the regression models, maximum R2 (co-effiecient of determination) values of 0.492, 0.790, 0.899, 0.891, 0.848, 0.942, 0.777 and 0.848 are acquired for Barisal, Chittagong, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur and Sylhet divisions respectively. Ridge regression worked better for Barisal and Chittagong divisions. For Mymensingh and Rangpur divisions Lasso regression performed the best. Decision Tree regression worked best for the four other divisions.

Original languageEnglish
Title of host publication2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7330-7333
Number of pages4
ISBN (Electronic)9781538691540
DOIs
Publication statusPublished - 2019 Jul
Event39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan
Duration: 2019 Jul 282019 Aug 2

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
CountryJapan
CityYokohama
Period19/7/2819/8/2

Keywords

  • MODIS
  • NDVI
  • production estimation
  • regression analysis
  • Rice model

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

Fingerprint Dive into the research topics of 'Boro Rice Yield Estimation Model Using Modis Ndvi Data for Bangladesh'. Together they form a unique fingerprint.

Cite this