AI and Remote Sensing for Yield Prediction and Crop Health Monitoring in Bangladesh
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Abstract
Bangladesh's agricultural output has been severely hampered by restrictions and pest infestations. AI and remote sensing have created new opportunities for crop health evaluation and crop yield forecasting. This study looks at the effects and efficacy in Bangladesh's major agricultural regions between 1995 and 2024. We used a descriptive statistical approach that contain retrospective data survey and combination from 30 years of satellite-derived NDVI indices, pest infestation reports, crop yield measurements, and remote sensing analytics. The analysis concentrated on inter-annual trends and variability, with variables including NDVI, crop yield, pest infestation index, and the number of satellite images analyzed. Cross-validation was conducted via ground-truth reports and published agricultural records, with all outliers from crisis years contextualized and, when warranted, excluded from interpretation. The average NDVI index was 46.1, with a considerable yield variability ranging from 5.6 to 99.8 tons/ha over the dataset. The mean yearly crop yield was 60.6 tons/ha, and pest infestation guide varied widely, with an average of 55.8. A useful association was observed between higher NDVI and inclined yields, while years of high pest infestation typically corresponded to yield decreased. The use of AI and remote sensing show to earlier detection of crop stress, more precise resource allotment, and inclined productivity, as reflected in the improved yield statistics and targeted pest control comebacks. Bangladesh's agricultural management has undergone a digital transformation with measurable gains in crop production prediction, timely pest control, and resource efficiency. The extensive application of these advanced technologies has been found to be advantageous, scalable, and suitable for both commercial and smallholder farms. The results indicate the model's use for repeating solutions in similar Farming environment, which helps to ensure a sustainable food supply in the future and lowering production unpredictability.
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Publication Details
- Type of Publication:
- Conference Name: Gazipur Agricultural University International Conference (GAUIC) 2025
- Date of Conference: 12/12/2025 - 12/12/2025
- Venue: Gazipur Agricultural University, Gazipur, Bangladesh
- Organizer: Gazipur Agricultural University