Development of a Multi-Sensor System for Agricultural Land and Crop Monitoring in Bangladesh using Remote Sensing and UAV Technology.

This UGC funded project focuses on developing a multi-sensor system to enhance agricultural land and crop monitoring in Bangladesh by integrating remote sensing and UAV (Unmanned Aerial Vehicle) technology. The system aims to provide actionable insights into vegetation health and crop conditions using advanced image analysis techniques.

Key Components and Methodology:

1. Sensor System Assembly:
- Two Sony H90 digital cameras form the core of the sensor system.
- One camera remains unmodified to capture standard RGB (Red, Green, Blue) images, while the other is modified to capture Near-Infrared (NIR) images in the 830-850 nm range.
- Modification involves removing the IR cut filter from the second camera and replacing it with an 850 nm IR pass filter, enabling the capture of NIR images.
- Both cameras are further adapted for remote control via the UAV's controller for seamless operation.

2. Drone Integration:
- The sensor assembly is mounted on a UAV, which is programmed to fly over agricultural fields and capture high-resolution aerial images of crops.

3. Image Alignment and Processing:
- Post-flight, the captured images are processed to align the fields of view (FOV) of both cameras.
- Overlapping regions are isolated by cropping out non-common areas, ensuring consistent data across the spectral bands.

4. NDVI Analysis with GIS Software:
- Aligned images are analyzed using GIS tools to calculate the Normalized Difference Vegetation Index (NDVI), a widely used metric for vegetation health.
- The NDVI formula, NDVI = (NIR - Red) / (NIR + Red), utilizes the NIR band from the modified camera and the Red band from the unmodified camera.

Outcomes:
The multi-sensor system delivers detailed vegetation health assessments and crop condition data, enabling better agricultural management and decision-making. This technology holds promise for improving crop yields, monitoring land use, and addressing agricultural challenges in Bangladesh.

This project showcases the integration of hardware modification, remote sensing, UAV technology, and GIS-based data analysis to provide innovative solutions for sustainable agriculture.