Nandhini et al. (2025) Harnessing Satellite Data for Sustainable Agriculture: An Overview of Remote Sensing in Crop Health Monitoring

Identification

• Journal: The Dawn Journal
• Year: 2025
• Date: 2025-06-30
• Authors: R Nandhini
• DOI: 10.56602/tdj/14.1.1734-1738

Research Groups

• SRM Institute of Science and Technology, Tiruchirappalli (Department of Computer Science and Engineering)

Short Summary

This paper provides an overview of using satellite-based remote sensing and vegetation indices, specifically NDVI, to monitor crop health and optimize agricultural inputs for sustainable farming.

Objective

• To evaluate the role of satellite imagery in real-time crop health monitoring, yield forecasting, and the optimization of irrigation, fertilization, and pest control.

Study Configuration

• Spatial Scale: Farm-level (10 m to 20 m resolution) and regional-scale (30 m resolution).
• Temporal Scale: Revisit times of 5 days (Sentinel-2) and 16 days (Landsat-8).

Methodology and Data

• Models used: Normalized Difference Vegetation Index (NDVI).
• Data sources: Open-access satellite imagery from Sentinel-2 and Landsat-8.

Main Results

• Vegetation Health Classification: NDVI values are categorized into healthy vegetation (0.6–1.0), moderate stress (0.2–0.5), severe stress (0.1–0.2), and non-vegetated areas (<0.1).
• Operational Efficiency: The integration of satellite data allows for variable-rate fertilizer management and precision irrigation, reducing waste and environmental impact.
• Regional Impact: Remote sensing enables large-scale objective data collection for crop area estimation, drought monitoring, and evidence-based agricultural policymaking.
• Identified Constraints: Effectiveness is limited by cloud cover (especially in monsoon regions), spatial resolution limits for small fields, and the saturation of NDVI in dense canopies.

Contributions

• The article synthesizes a conceptual workflow for translating raw satellite imagery into actionable agricultural intelligence and outlines the transition from traditional field-based monitoring to AI-driven precision agriculture.

Funding

• Not specified

Citation

@article{Nandhini2025Harnessing,
  author = {Nandhini, R and Prakash, Avishna K},
  title = {Harnessing Satellite Data for Sustainable Agriculture: An Overview of Remote Sensing in Crop Health Monitoring},
  journal = {The Dawn Journal},
  year = {2025},
  doi = {10.56602/tdj/14.1.1734-1738},
  url = {https://doi.org/10.56602/tdj/14.1.1734-1738}
}