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Program Overview:

 

The program offers a comprehensive foundation in acquiring, processing, and analyzing geospatial data from satellite and aerial sensors. Participants will explore the principles of remote sensing, sensor technologies, image classification, and data integration with GIS. Emphasis is placed on practical applications in environmental monitoring, land use mapping, and biodiversity conservation, particularly within the AFOLU sectors. Through hands-on exercises and a final project, learners will develop essential skills to apply remote sensing technologies in real-world environmental and land management projects.

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Program Structure:

Course Duration: 12 Weeks
Total Hours: 48 (4 hours/week)
Target Audience: Beginners in Remote Sensing, environmental science students, professionals in AFOLU sectors
Mode of Delivery: Blended (Lectures, Hands-on Labs, Assignments)

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Course Modules:

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Month 1: Fundamentals of Remote Sensing (Basics)

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Week 1: Introduction to Remote Sensing

• Definition and Principles of Remote Sensing

• History and Evolution of Remote Sensing

• Electromagnetic Spectrum and Its Role in Remote Sensing

Week 2: Remote Sensing Platforms and Sensors

• Types of Sensors (Passive and Active)

• Satellite and Aerial Platforms

• Sensor Resolutions (Spatial, Spectral, Temporal, Radiometric)

Week 3: Data Acquisition and Preprocessing

• Data Acquisition Methods

• Radiometric and Geometric Corrections

• Image Enhancement Techniques

Week 4: Introduction to Remote Sensing Software

• Overview of Software Tools (ENVI, ERDAS Imagine, QGIS)

• Importing and Visualizing Remote Sensing Data

• Basic Image Processing Operations

 

Month 2: Image Processing and Analysis (Intermediate)

 

Week 5: Image Classification Techniques

• Supervised vs. Unsupervised Classification

• Training Data Collection

• Accuracy Assessment and Error Matrix

Week 6: Image Interpretation and Feature Extraction

• Visual Interpretation Elements

• Object-Based Image Analysis (OBIA)

• Change Detection Techniques

Week 7: Multispectral and Hyperspectral Remote Sensing

• Differences between Multispectral and Hyperspectral Data

• Applications in Environmental Monitoring

Week 8: Thermal and Microwave Remote Sensing

• Principles of Thermal Infrared Remote Sensing

• Radar and LiDAR Technologies

• Applications in Earth Observation

 

Month 3: Advanced Applications and Project Work (Advance)

 

Week 9: Remote Sensing in Environmental and Land Use Applications

• Land Cover and Land Use Mapping

• Remote Sensing for Biodiversity and Conservation

• Applications in AFOLU Sectors

Week 10: Integration with GIS and Data Fusion

• Combining Remote Sensing and GIS Data

• Data Fusion Techniques

• Case Studies and Applications

Week 11: Project Planning and Implementation

• Defining Project Objectives

• Data Collection and Analysis Workflow

• Visualization and Presentation Techniques

Week 12: Final Project Presentation and Assessment

• Project Report Submission

• Group Presentations

• Course Review and Feedback

 

Assessment and Evaluation

• Assignments: Weekly hands-on tasks (30%)

• Quizzes: Monthly online quizzes (20%)

• Final Project: Data analysis and presentation (50%)

 

Recommended Tools and Resources

• Software: ENVI, ERDAS Imagine, QGIS

• Data Sources: USGS Earth Explorer, Copernicus Open Access Hub, NASA Earthdata

• Reading Materials:

  • Remote Sensing of the Environment by John R. Jensen

  • Introductory Digital Image Processing by John R. Jensen

  • Online tutorials and documentation from NASA and ESA

 

Outcome

By the end of the program, participants will be able to:

• Understand fundamental concepts of remote sensing and sensor technologies

• Perform image preprocessing and classification techniques

• Analyze and interpret multispectral, hyperspectral, thermal, and radar data

• Apply remote sensing tools in environmental and AFOLU projects

 

This curriculum is designed to equip students with the practical skills and theoretical knowledge necessary to excel in the rapidly evolving GIS field.