Course Outline:

Module 1: Introduction to GIS, Remote Sensing, and Their Applications in Agriculture

• Basic GIS and RS concepts

• Overview of spatial data types and sources

• Applications of geospatial technologies in agriculture and climate monitoring
  Case Study: Mapping agricultural zones and land use classification in a developing country

Module 2: Satellite Data Sources and Image Acquisition

• Overview of satellite platforms (Sentinel, Landsat, MODIS)

• Accessing open satellite imagery (Copernicus, USGS Earth Explorer)

• Understanding spatial, spectral, and temporal resolution
  Project: Downloading and selecting appropriate imagery for crop monitoring in a semi-arid area

Module 3: Image Preprocessing and Enhancement

• Radiometric and atmospheric correction

• Image mosaicking and clipping

• Enhancement techniques for better interpretation
  Case Study: Preparing imagery for NDVI analysis in a drought-prone region

Module 4: Vegetation Indices and Crop Monitoring

• NDVI, EVI, SAVI, and other indices

• Time-series analysis of vegetation health

• Detecting crop stress and anomalies
  Project: Mapping crop vigor using NDVI across growing seasons

Module 5: Land Use and Land Cover (LULC) Classification

• Supervised and unsupervised classification methods

• Accuracy assessment and confusion matrix

• LULC change detection techniques
  Case Study: Monitoring agricultural expansion and forest loss over 10 years

Module 6: Soil and Water Resource Mapping

• Mapping soil types and moisture using RS data

• Identifying water bodies and irrigation potential

• Integration of field data with spatial datasets
  Project: Delineating potential irrigation zones using DEM and RS imagery

Module 7: Climate Change Analysis Using GIS & Remote Sensing

• Mapping temperature and rainfall trends

• Climate anomaly and variability visualization

• Use of climate models and downscaled data
  Case Study: Assessing the impact of changing rainfall patterns on crop yield

Module 8: Food Security and Agricultural Risk Mapping

• Identifying food-insecure areas using spatial indicators

• Risk mapping for drought, pests, and market access

• Linking remote sensing with household and survey data
  Project: Developing a spatial risk map for early warning systems

Module 9: GIS-Based Decision Support Tools and Dashboards

• Creating interactive maps and dashboards

• Using ArcGIS Online, QGIS Web, and other platforms

• Data storytelling and stakeholder communication
  Case Study: Building a food security monitoring dashboard for a humanitarian agency

Module 10: Capstone Project and Presentation

• Group or individual final projects based on real datasets

• Integration of remote sensing, GIS, and climate data

• Presentation of findings and recommendations
  Capstone Project: Develop a complete GIS solution for monitoring climate impacts on agricultural production in a specific region