AI in Space Science: Predictive Analytics for Satellite Data Interpretation
Transform Satellite Data into Actionable Insights with AI for Climate, Agriculture, and Urban Planning.
About This Course
This 3-day hands-on workshop explores the integration of AI with satellite data for weather forecasting, climate monitoring, and practical applications in agriculture and urban planning. Participants will learn how to preprocess satellite imagery for AI-based analysis, build predictive models for weather patterns and climate trends, and apply AI tools to translate satellite data into actionable insights for agriculture and urban development. Real-world case studies and practical exercises using Python (OpenCV, scikit-image, etc.) will be covered.
Aim
To provide participants with the skills to preprocess satellite imagery, build predictive models for weather forecasting and climate monitoring, and apply AI for decision-making in agriculture and urban planning.
Workshop Objectives
- Understand the types of satellite data (remote sensing, multispectral, hyperspectral imagery) and their applications in space science.
- Learn AI techniques for preprocessing satellite imagery (filtering, normalization, feature extraction) and preparing data for machine learning models.
- Build predictive weather models using satellite data, AI, and machine learning techniques (regression, neural networks, LSTMs).
- Monitor climate patterns using satellite data to predict future climate trends.
- Apply AI tools to satellite data for agricultural applications (crop health, land-use analysis) and urban planning (urban growth, environmental management).
- Develop a decision-support tool for interpreting satellite data and making informed decisions in agriculture and urban planning.
Workshop Structure
📅 Day 1 — Introduction to Satellite Data and AI for Image Processing
- Satellite data types: Overview of remote sensing, multispectral and hyperspectral imagery, and sensor types used in space science
- AI in image processing: Techniques for preprocessing satellite imagery (filtering, normalization, feature extraction)
- Data preparation: How to prepare satellite imagery for machine learning models
- Hands-on: Preprocess and analyze satellite imagery using Python (e.g., OpenCV, scikit-image) for AI-based interpretation
📅 Day 2 — Predictive Models for Weather Forecasting and Climate Monitoring
- Weather forecasting models: AI and machine learning techniques (regression, neural networks, LSTMs) for predicting weather patterns from satellite data
- Climate monitoring: Using satellite data to monitor long-term climate trends and predict future patterns
- Model evaluation: Assessing model accuracy and robustness for real-time weather predictions
- Hands-on: Build a predictive model for weather forecasting using satellite data and evaluate its performance with real-world examples
📅 Day 3 — AI Tools for Satellite Data Interpretation in Agriculture and Urban Planning
- Agriculture: AI applications for crop health monitoring, land-use analysis, and precision agriculture through satellite data
- Urban planning: AI tools for analyzing urban growth, land cover, and environmental management using satellite imagery
- Decision support systems: How to translate satellite data into actionable insights for policy and planning
- Hands-on: Develop a decision-support tool using AI to interpret satellite data for agricultural and urban planning applications
Who Should Enrol?
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Researchers, data scientists, environmental engineers, urban planners, and professionals interested in AI applications in satellite data interpretation.
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Basic knowledge of Python and machine learning is helpful, but not required.
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Participants should have an interest in utilizing satellite data for climate, agriculture, or urban planning applications.
Important Dates
Registration Ends
02/10/2026
IST 4 : 30 PM
Workshop Dates
02/10/2026 – 02/12/2026
IST 5 : 30 PM
Workshop Outcomes
- Preprocess and analyze satellite imagery using Python (OpenCV, scikit-image) for AI-based interpretation.
- Build and evaluate predictive models for weather forecasting and climate monitoring using machine learning techniques.
- Develop AI applications for satellite data interpretation in agriculture (precision farming, crop health monitoring) and urban planning (land-use analysis, environmental management).
- Create a decision-support tool that uses satellite data to provide actionable insights for policy and planning in agriculture and urban development.
Fee Structure
Student
₹2499 | $65
Ph.D. Scholar / Researcher
₹3499 | $75
Academician / Faculty
₹4499 | $85
Industry Professional
₹6499 | $105
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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