Gupta et al. (2025) AI Driven Spatio-Temporal Modeling for Climate-Resilient Crop Yield Prediction in Indian Agro Ecosystems

Identification

• Journal: Knowledge Commons (Lakehead University)
• Year: 2025
• Date: 2025-12-03
• Authors: Gupta, Dr. Sandeep, Hamid, Abu Bakar Abdul, Nyamasvisva, Dr.Tadiwa Elisha, Rastogi, Dr. Ritesh, Singh, Abhishek, Awasthi, Dr. Satya Prakash
• DOI: 10.17613/v67qb-fts78

Research Groups

Not specified in the provided text.

Short Summary

This paper focuses on developing AI-driven spatio-temporal models to predict climate-resilient crop yields within Indian agro ecosystems.

Objective

• To develop and apply AI-driven spatio-temporal models for predicting climate-resilient crop yields in Indian agro ecosystems.

Study Configuration

• Spatial Scale: Indian agro ecosystems (regional to national scale within India).
• Temporal Scale: Spatio-temporal modeling for climate-resilient prediction, implying analysis over multiple seasons or years.

Methodology and Data

• Models used: AI-driven spatio-temporal models.
• Data sources: Not specified in the provided text.

Main Results

• Not specified in the provided text.

Contributions

• Development and application of AI-driven spatio-temporal models specifically tailored for climate-resilient crop yield prediction in Indian agro ecosystems.

Funding

• National Science Foundation (Grant No. OAC-2226271)

Citation

@article{Gupta2025AI,
  author = {Gupta, Dr. Sandeep and Hamid, Abu  Bakar  Abdul and Nyamasvisva, Dr.Tadiwa  Elisha and Rastogi, Dr. Ritesh and Singh, Abhishek and Awasthi, Dr. Satya Prakash},
  title = {AI Driven Spatio-Temporal Modeling for Climate-Resilient Crop Yield Prediction in Indian Agro Ecosystems},
  journal = {Knowledge Commons (Lakehead University)},
  year = {2025},
  doi = {10.17613/v67qb-fts78},
  url = {https://doi.org/10.17613/v67qb-fts78}
}