Pannonian University pu.edu.rs

Climate & Land / AGT-202

Remote Sensing for Climate-Smart Agriculture

Interpreting crop vigor, field stress, irrigation signals, and UAV imagery for farm and policy decisions.

Course detail

Research connection

Uses PU field plots near Novi Sad to compare Sentinel-2 vegetation indices, UAV imagery, and farmer-reported irrigation stress.

Imagery Processing Quota18 scenes
Lab affiliateAgriTech Remote Sensing Lab
Studio intensity66/100

Learning outcomes

What students should be able to do.

  • Process remote sensing imagery into an agronomic interpretation.
  • Compare satellite and UAV signals without overstating precision.
  • Translate climate risk evidence into farm and policy recommendations.

Readiness

Prerequisites and assessment.

PU-101 or equivalentMethods readiness

Imagery notebook 30%, field protocol 20%, decision memo 30%, peer critique 20%.

Weekly syllabus

Four-week intensive module structure.

  1. 01
    Vegetation Indices and Ground Truth

    NDVI, NDRE, soil moisture proxies, and the limits of spectral interpretation.

  2. 02
    UAV Mission Planning

    Flight planning, image stitching, control points, and field safety procedures.

  3. 03
    Irrigation Stress Detection

    Temporal comparison of crop vigor, heat exposure, and water availability.

  4. 04
    Decision Memo Lab

    A farm-facing advisory note with maps, uncertainty, and recommended next measurements.

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