AD-803 (A) · AI for Remote Sensing/Official Syllabus
AI for Remote Sensing (AD-803 (A)) - Official Syllabus
1
Unit 1
Introduction to Remote Sensing and AI
- Definition of Remote sensing
- Principles of Remote Sensing
- Introduction to Artificial Intelligence
- Integration of AI in Remote Sensing
2
Unit 2
Types of Remote Sensing Platforms and Sensors
- Sensors: Types and classification of sensors
- Platforms: Types of platforms, ground, airborne, and space born platforms
- Data acquisition techniques and image resolution
- Data pre-processing and feature extraction techniques
- Radiometric and geometric corrections
- Data fusion and enhancement methods
3
Unit 3
AI for Remote Sensing
- Supervised Learning for Remote Sensing Analysis
- Unsupervised Learning for Remote Sensing Analysis
- Deep Learning for Remote Sensing Analysis
- Image Image Classification Techniques in Remote Sensing
4
Unit 4
AI-Assisted Image Interpretation and Feature Extraction
- Object detection and tracking in remote sensing imagery
- Change detection and time-series analysis
- Hyperspectral and LiDAR data analysis
- Fusion of multi-modal remote sensing data
5
Unit 5
Applications of AI in Remote Sensing
- Land cover and land use mapping
- Environmental monitoring and assessment
- Disaster management and response
- Precision agriculture and crop monitoring
Reference Books
- Deep Learning for Remote Sensing Images with Open Source Software
- Deep Learning Methods for Remote Sensing
- Remote Sensing Data Analysis Using R
- Remote Sensing with ArcGIS Pro
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