Precision Agriculture and ICT Applications
Precision Agriculture and ICT Applications tests how sensing, mapping, variable-rate technology and digital advisory services improve farm decisions. Expect GPS, GIS, remote sensing, yield monitoring, drones, soil sensors, IoT and mobile platforms, with attention to accuracy and interpretation.
Core rules
- GPS/GNSS gives position; differential correction or RTK improves accuracy from metres to centimetres for guidance and section control.
- GIS stores and overlays spatial layers such as soil, yield, slope and irrigation; overlay analysis identifies management zones.
- Remote sensing uses reflectance bands. NDVI = (NIR − Red) ÷ (NIR + Red); values near +1 indicate dense green vegetation, values near 0 bare soil, negative values water or snow.
- Variable-rate application (VRA) adjusts seed, fertiliser or pesticide to management zones; it requires calibration and a prescription map.
- Yield monitors and moisture sensors need calibration; raw data are noisy and should be cleaned before mapping.
- ICT advisories, e-NAM, soil health cards and weather alerts support decisions but depend on connectivity, local language and data quality.
Worked example
A drone image gives NIR = 0.80 and red = 0.20. NDVI = (0.80 − 0.20) ÷ (0.80 + 0.20) = 0.60 ÷ 1.00 = 0.60. That indicates moderately dense, healthy vegetation. If a field zone has NDVI 0.25, it may need investigation for poor emergence, nutrient deficiency or waterlogging. Reasoning: apply the formula band by band, then interpret relative to the crop stage; do not compare NDVI across different dates or sensors without care.
Traps
Do not read high NDVI as guaranteed high yield; weeds, disease and saturation can mislead. Do not use NDVI outside its −1 to +1 range. RTK guidance is not the same as yield mapping accuracy. A prescription map is not a variable-rate application unless the controller is calibrated and the machine responds correctly.