Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery
Precision in Every Pixel: Elevating Agriculture with Satellite Imagery and AI
About This Course
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 Structure
📡 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
Who Should Enrol?
- 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.
Important Dates
Registration Ends
03/07/2026
IST 4 : 30 PM
Workshop Dates
03/07/2026 – 03/09/2026
IST 5 :30 PM
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.
Fee Structure
Student
₹2499 | $75
Ph.D. Scholar / Researcher
₹3499 | $85
Academician / Faculty
₹4499 | $95
Industry Professional
₹6499 | $115
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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