Rangel Daroya
Papers
1
Total Citations
17
H-Index
1
About
Rangel Daroya’s research lies at the intersection of precision agriculture, remote sensing, and autonomous systems, with a focus on using unmanned aerial vehicles (UAVs) to monitor crop health. His most cited work, “NDVI image extraction of an agricultural land using an autonomous quadcopter with a filter-modified camera” (2017, 17 citations), demonstrates a practical, low-cost method for capturing Normalized Difference Vegetation Index (NDVI) data. By modifying a standard camera and integrating it with an autonomous quadcopter, Daroya enabled efficient aerial surveys of agricultural fields, providing farmers with actionable estimates of crop conditions. This contribution is notable for making precision agriculture more accessible, reducing reliance on expensive satellite imagery or manual scouting. His work has been cited by researchers exploring UAV-based vegetation monitoring, sensor calibration, and field-scale phenotyping. Daroya’s approach exemplifies how engineering and agronomy can converge to address real-world food production challenges, offering a scalable tool for sustainable farming. His research continues to inspire students and practitioners interested in low-altitude remote sensing and automated agricultural assessment.
Research Focus
Key Achievements
Top Papers
- 1