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From Satellite to Field: Assessing Rice Yield Variability in Bangladesh Using NDVI and Weather Data

Students & Supervisors

Student Authors
Intisar Jaman Chowdhoury
Bachelor of Science in Computer Science & Engineering, FST
Umme Fahmida Sultana
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FST

Abstract

Considering the impact of weather conditions and the health of plants on crop production is crucial for forecasting and food security. This research examines rice production across four districts of Bangladesh-Rajshahi, Dinajpur, Satkhira and Khulna during the 2023–24 cropping year, covering the Aus, Aman and Boro seasons. The aim was to explore how climatic factors and vegetation indices relate to seasonal yields and to provide insights for better agricultural management. This study employed the quantitative method in analyzing the combination of daily weather variables, solar radiation, precipitation, and temperature, collected from satellite’s NDVI (Normalized Difference Vegetation Index) values to represent crop health. In the analysis, seasonal metrics, determined to represent each district, were compared to yield data in the terms of area production and yield per hectare. The results highlight clear seasonal and regional differences. For example, Rajshahi’s Boro season gained the highest yield (4.456 t/ha) under moderate temperatures (24.94°C) and NDVI of 0.188 whereas Khulna’s Aus season recorded the lowest yield (1.907 t/ha) despite high solar radiation and NDVI. Dinajpur’s Aman and Boro seasons performed well, showing that vegetation health and balanced rainfall are key to higher yields. This research shows that the combination of weather events and NDVI information has an application for assessing the performance of crops throughout different seasons and different geographical areas. Extending the findings of the 2023–24 season, we will assist farmers, policymakers, and researchers in making informed decisions. Future research will focus on predictive modeling for the purpose of early warning and climate-smart agriculture to improve the food security situation in Bangladesh and to enhance yield.

Keywords

Weather variability crop health assessment NDVI rice yield Bangladesh.

Publication Details

  • Type of Publication:
  • Conference Name: Gazipur Agricultural University International Conference 2025 (GAUIC 2025)
  • Date of Conference: 12/12/2025 - 12/12/2025
  • Venue: Gazipur Agricultural University Bangladesh
  • Organizer: Gazipur Agricultural University Bangladesh
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