Geospatial Data & Spatial Analysis for Agriculture and Food Security Training Workshop

Course overview

The Geospatial Data & Spatial Analysis for Agriculture and Food Security Training Workshop equips agricultural professionals, GIS specialists, food security analysts, researchers, development practitioners and decision-makers with practical skills in collecting, processing, analysing and visualising geospatial data to support agricultural planning, crop monitoring, food security assessment and sustainable land management.

The workshop explores Geographic Information Systems (GIS), remote sensing, satellite imagery, spatial databases, agricultural mapping, crop suitability modelling, vegetation monitoring, rainfall analysis, drought assessment, land-use and land-cover classification, yield estimation and food insecurity mapping. Participants learn to integrate satellite observations, climate information, soil characteristics, agricultural statistics and field survey data to generate actionable insights for agricultural productivity, early warning systems and food security interventions.

Course objectives

Acquire, organise and manage geospatial datasets from satellite imagery, agricultural surveys, climate databases, soil maps and other relevant sources.
Produce professional agricultural maps, spatial models, dashboards and technical reports that support evidence-based planning, monitoring and food security interventions.
Integrate geospatial, climatic, soil, socioeconomic and agricultural data to develop decision-support maps, indicators and analytical outputs.
Conduct spatial analysis for food security assessment, drought monitoring, agricultural vulnerability mapping and identification of at-risk communities.
Apply GIS and remote sensing techniques to analyse crop distribution, vegetation health, land suitability, agricultural productivity and environmental conditions.

Who should attend

GIS specialists, remote sensing professionals, agricultural officers, agronomists, agricultural economists, food security analysts, climate change specialists, environmental scientists, soil scientists, crop production specialists, agricultural extension officers, development practitioners, humanitarian professionals, disaster risk management officers, food security programme managers, agricultural researchers, rural development planners, geospatial data analysts, monitoring and evaluation specialists, natural resource management professionals, precision agriculture practitioners, irrigation planners, land-use planners, agricultural policy analysts and professionals involved in agricultural development, food security monitoring and climate resilience.

Course content

Module 1: Introduction to Geospatial Data for Agriculture and Food Security Fundamentals of GIS and remote sensing, applications of geospatial intelligence in agriculture, relationship between spatial analysis and food security, geographic data types and
Module 2: Geospatial Data Acquisition and Management Sources of agricultural and geospatial data, downloading satellite imagery from Copernicus Data Space and USGS EarthExplorer, accessing Sentinel-1 and Sentinel-2 imagery, Landsat satellite datasets, MOD
Module 3: GIS Software for Agricultural Spatial Analysis Introduction to QGIS for agricultural mapping, project setup and coordinate reference systems, importing vector and raster datasets, managing spatial layers and attribute tables, symbology and thema
Module 4: Remote Sensing and Satellite Image Processing for Agriculture Principles of satellite remote sensing, electromagnetic spectrum and spectral signatures of crops, understanding multispectral imagery, Sentinel-2 bands and agricultural applications,
Module 5: Vegetation Indices and Crop Health Monitoring Principles of vegetation indices, Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil-Adjusted Vegetation Index (SAVI), Normalised Difference Water Index (NDWI), calc
Module 6: Agricultural Land-Use and Crop Type Mapping Agricultural land-use and land-cover classification, supervised and unsupervised classification, training sample preparation, spectral signatures and class selection, distinguishing cropland from other
Module 7: Soil Mapping, Land Suitability and Agricultural Zoning Soil characteristics and agricultural productivity, integrating soil texture, pH, organic carbon and drainage information, terrain and slope analysis, digital elevation models and terrain de
Module 8: Climate, Rainfall and Drought Analysis for Agriculture Accessing gridded rainfall and climate datasets, rainfall distribution and seasonal variability, rainfall anomaly analysis, precipitation time series, temperature and evapotranspiration data
Module 9: Crop Production Estimation and Agricultural Productivity Analysis Agricultural productivity indicators, crop area estimation from satellite imagery, integrating crop maps with agricultural statistics, vegetation indices as indicators of crop con
Module 10: Spatial Analysis for Food Security Assessment Food security dimensions of availability, access, utilisation and stability, mapping food production and agricultural resource availability, spatial distribution of food insecurity indicators, integ
Module 11: Agricultural Vulnerability, Climate Resilience and Risk Mapping Concepts of exposure, sensitivity and adaptive capacity, identifying climate hazards affecting agricultural systems, mapping drought, flood and erosion exposure, combining environm
Module 12: Google Earth Engine for Large-Scale Agricultural Analysis Introduction to cloud-based geospatial processing, accessing satellite datasets in Google Earth Engine, filtering Sentinel-2 imagery by date and cloud cover, selecting geographic areas o
Module 13: Precision Agriculture, Field Mapping and Agricultural Resource Management Principles of precision agriculture, GPS-based field boundary mapping, agricultural field data collection, mapping crop variability within fields, integrating soil sampli
Module 14: Spatial Data Visualisation, Dashboards and Reporting Principles of agricultural cartography, selecting appropriate thematic map types, choropleth and graduated-symbol maps, crop distribution and suitability maps, vegetation health and drought m
Module 15: Integrated Agricultural Geospatial Analysis Capstone Defining an agricultural or food security problem, identifying relevant spatial and non-spatial datasets, preparing a GIS project and data inventory, mapping agricultural land and crop distri

General notes

Using industry-relevant software and open geospatial datasets, the course emphasises hands-on analysis of crop conditions, agricultural resources, climate-related risks and food security indicators. Participants develop practical skills to produce thematic maps, spatial analysis outputs, agricultural monitoring dashboards and evidence-based reports for agricultural programmes, research projects, humanitarian operations and development planning.
5. Training Tools and Software The workshop uses a combination of open-source GIS software, satellite data platforms and analytical tools. - QGIS: Spatial data management, geoprocessing, thematic mapping, suitability analysis and cartographic reporting. - Google Earth Engine: Cloud-based satellite image processing, vegetation monitoring, land-cover classification and time-series analysis. - ESA Copernicus Data Space Ecosystem: Access to Sentinel satellite imagery. - USGS EarthExplorer: Access to Landsat imagery and other Earth observation datasets. - Microsoft Excel: Agricultural statistics, indicator calculations, data cleaning and summary analysis. - Python: Geospatial data analysis using GeoPandas, Rasterio, Xarray, NumPy, Pandas and Matplotlib. - Power BI: Agricultural monitoring dashboards and visual reporting. - KoboToolbox or ODK: Field data collection, crop surveys and georeferenced agricultural observations. - Google Earth Pro: Visual interpretation, location exploration and preliminary agricultural mapping.
Practical Exercises and Expected Outputs Participants will work with realistic agricultural, satellite, climate, soil and food security datasets. Exercises will include downloading and preparing satellite imagery, mapping agricultural land, calculating NDVI, assessing crop conditions, analysing rainfall patterns, identifying drought-affected areas, modelling crop suitability, mapping food security vulnerability and creating agricultural monitoring dashboards.
Expected practical outputs include: - Agricultural geospatial data inventory and acquisition plan - GIS project containing agricultural and environmental datasets - Agricultural land-use and land-cover map - Sentinel-2 vegetation index map using NDVI or EVI - Crop health and vegetation condition assessment - Crop type classification and accuracy assessment - Soil and terrain suitability assessment - Crop suitability and agricultural zoning map - Rainfall distribution and anomaly maps - Agricultural drought monitoring map - Crop production or productivity analysis - Food security vulnerability and hotspot map - Agricultural climate risk and resilience assessment - Google Earth Engine agricultural monitoring workflow - Agricultural field mapping and GPS data collection exercise - Interactive agricultural monitoring dashboard - Final geospatial analysis report with maps, findings and recommendations
The Geospatial Data & Spatial Analysis for Agriculture and Food Security Training Workshop equips agricultural professionals, GIS specialists, food security analysts and development practitioners with practical skills in GIS, remote sensing, satellite image processing, crop monitoring, land suitability modelling, rainfall analysis, drought assessment and food security vulnerability mapping. Participants learn to use QGIS, Google Earth Engine, Sentinel satellite imagery, agricultural datasets and spatial analysis tools to assess crop conditions, map agricultural resources, identify climate risks and produce evidence-based maps, dashboards and reports that support agricultural planning, food security programmes and climate-resilient development.

Frequently asked questions

1. 1. Who should attend the Geospatial Data & Spatial Analysis for Agriculture and Food Security Training Workshop?

The workshop is suitable for GIS and remote sensing specialists, agronomists, agricultural researchers, food security analysts, climate specialists, development practitioners, agricultural planners, humanitarian professionals and monitoring and evaluation officers.

2. 2. Do participants need prior GIS or programming experience?

Basic computer skills are sufficient for introductory GIS exercises. Participants with existing GIS knowledge can progress to satellite image analysis, spatial modelling and agricultural monitoring. Python and Google Earth Engine programming activities can be adapted to different experience levels.

3. 3. Which software will participants learn?

The core tools are QGIS and Google Earth Engine, supported by satellite data platforms, Excel and selected geospatial Python libraries. Power BI, KoboToolbox and ODK may be incorporated for reporting and field data collection.

4. 4. Can the course be used for crop monitoring and drought assessment?

Yes. Participants learn to calculate vegetation indices, analyse rainfall and vegetation trends, identify crop stress, compare seasonal conditions and develop spatial indicators that support agricultural drought monitoring and early warning. These indicators complement field observations and other relevant evidence.

5. 5. Will participants learn to map food insecurity and vulnerable agricultural areas?

Yes. The workshop covers the integration of agricultural production, rainfall, vegetation, market access, socioeconomic and household survey information to map vulnerability and identify areas that may require further assessment or targeted interventions.

Schedule & fees

Dates	Location	Duration	Fee (USD)
05/04/2027 - 09/04/2027	Naivasha,Kenya	10 Days	$1,500
11/10/2027 - 15/10/2027	Nairobi,kenya or Virtual	10 Days	$1,500