
Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery
Precision in Every Pixel: Elevating Agriculture with Satellite Imagery and AI
Skills you will gain:
About Workshop:
Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery is a hands-on workshop that teaches how to use satellite data and AI to optimize agriculture. Participants will learn to analyze NDVI time-series data for crop health monitoring, yield prediction, and precision farming.
Aim: The workshop aims to teach participants how to use satellite imagery and NDVI time-series analysis, combined with AI, to monitor crop health, predict yields, and implement sustainable farming practices for improved productivity.
Workshop Objectives:
What you will learn?
📡 Day 1 — Introduction to NDVI and Satellite Imagery
- Focus: Introduction to NDVI and satellite imagery for crop monitoring
- Key Topics:
- Understanding NDVI and its role in crop health monitoring
- Introduction to remote sensing and satellite platforms (Sentinel, Landsat)
- Exploring the importance of time-series analysis in agriculture
- Hands-on (Google Colab):
- Task: Access and process satellite imagery, perform basic NDVI calculation using Google Earth Engine and Python
🌾 Day 2 — Time-Series Analysis and Crop Monitoring
- Focus: Time-series analysis for monitoring crop health and growth patterns
- Key Topics:
- Overview of time-series data and its significance in agriculture
- Analyzing NDVI time-series data to monitor seasonal changes and crop health
- Hands-on (Google Colab):
- Task: Process and analyze multi-temporal NDVI data, identify crop stress, growth patterns, and yield forecasts using Python and Google Earth Engine
🌱 Day 3 — AI in Agri-Tech and Predictive Modeling
- Focus: Introduction to AI and machine learning for precision agriculture
- Key Topics:
- AI techniques for crop yield prediction, disease detection, and resource management
- Applying machine learning models to NDVI data for actionable insights in agriculture
- Hands-on (Google Colab):
- Task: Build predictive models for crop yield and disease detection using Python, explore case studies on AI applications in agriculture
Mentor Profile
Fee Plan
Important Dates
07 Mar 2026 Indian Standard Timing 4 : 30 PM
07 Mar 2026 to 09 Mar 2026 Indian Standard Timing 5 :30 PM
Get an e-Certificate of Participation!

Intended For :
- Agriculture Professionals: Those involved in precision agriculture, crop monitoring, and farm management.
- Data Scientists & Engineers: Individuals with an interest in applying machine learning, AI, and remote sensing to agriculture.
- Researchers & Academicians: Those working in the fields of agricultural science, environmental science, and Agri-Tech innovation.
- Students: Graduate and postgraduate students specializing in agriculture, environmental science, data science, or related fields.
- Industry Professionals: From sectors including Agri-Tech, sustainable farming, and remote sensing technology.
Career Supporting Skills
Workshop Outcomes
- Analyze NDVI Data to assess crop health and growth.
- Apply AI to predict yields and detect diseases.
- Use Remote Sensing Tools like Google Earth Engine and Python for data analysis.
- Implement Sustainable Practices to optimize resources and enhance productivity.
- Translate Insights into Action for precision agriculture and smarter farming solutions.
