Time-series Analysis Of Remote Sensing Data For M&e Training Course

Introduction

The Time-Series Analysis of Remote Sensing Data for M&E (Monitoring and Evaluation) Training Course is designed to provide professionals with advanced skills in analyzing remote sensing data to monitor and evaluate development projects and environmental changes over time. This course covers the techniques and tools for applying time-series analysis to remote sensing data, enabling participants to extract meaningful insights and track long-term changes in land use, vegetation, water bodies, and urban infrastructure. By mastering this skill set, professionals can make data-driven decisions, improving the accuracy and efficiency of their M&E processes.

As remote sensing technology continues to evolve, incorporating time-series analysis has become essential for monitoring dynamic environmental and societal changes. This course equips participants with the knowledge of key methodologies to utilize satellite imagery and geospatial data in analyzing temporal trends, facilitating informed decision-making for sustainable development and project evaluation.

Target Audience

This training course is ideal for:

• M&E professionals in government agencies, NGOs, and international organizations.
• Environmental scientists and researchers looking to incorporate time-series analysis in their work.
• Remote sensing specialists seeking to enhance their analytical capabilities for development projects.
• GIS analysts who want to gain expertise in the temporal analysis of geospatial data.
• Data scientists and spatial analysts working on remote sensing-based projects in environmental monitoring, disaster risk management, and urban development.
• Project managers and policy makers aiming to understand long-term trends and impacts in development initiatives.

Course Objectives

By the end of the Time-Series Analysis of Remote Sensing Data for M&E Training Course, participants will be able to:

• Understand Time-Series Analysis in Remote Sensing: Gain a comprehensive understanding of the principles and significance of time-series analysis for monitoring and evaluation (M&E) processes.
• Acquire Proficiency in Remote Sensing Data Interpretation: Learn how to interpret multi-temporal satellite imagery and geospatial data to track environmental and developmental changes over time.
• Apply Analytical Techniques for Change Detection: Master methods of detecting and analyzing changes in land use, vegetation, water bodies, and infrastructure using time-series data from remote sensing sources.
• Utilize Tools for Time-Series Data Processing: Gain hands-on experience with tools and software, such as Google Earth Engine, QGIS, and Python, to process and analyze time-series remote sensing data.
• Integrate Time-Series Data in M&E Frameworks: Learn to incorporate time-series analysis into M&E systems to assess the impact, effectiveness, and sustainability of development projects and programs.
• Develop Data-Driven Reports for Stakeholders: Understand how to present time-series analysis results through visually compelling reports, maps, and dashboards to support decision-making in development projects.
• Improve Project Monitoring and Impact Assessment: Leverage time-series remote sensing data to enhance monitoring strategies, improve project outcomes, and evaluate long-term environmental or developmental impacts.

This training course is structured to provide participants with both theoretical knowledge and practical tools, empowering them to effectively use time-series analysis of remote sensing data in M&E activities, driving sustainable and informed decision-making.

Duration

10 Days

Course content

Module 1: Introduction to Time-Series Analysis in Remote Sensing

• Overview of time-series analysis in remote sensing
• Importance of temporal analysis in monitoring and evaluation (M&E)
• Key concepts: Temporal resolution, change detection, and trend analysis

Module 2: Remote Sensing Data Sources for Time-Series Analysis

• Types of remote sensing data for M&E (satellite imagery, UAVs, aerial surveys)
• Understanding Landsat, Sentinel, and MODIS satellite data
• Temporal aspects of remote sensing data

Module 3: Geospatial Data Preprocessing for Time-Series Analysis

• Data cleaning and preprocessing techniques
• Georeferencing and image alignment
• Handling atmospheric effects and noise in remote sensing data

Module 4: Time-Series Analysis Techniques for Remote Sensing

• Introduction to time-series analysis methods
• Statistical techniques: Moving averages, smoothing, and trend analysis
• Time-series decomposition and anomaly detection

Module 5: Change Detection in Time-Series Remote Sensing Data

• Detecting land cover and land use changes over time
• Techniques for monitoring deforestation, urbanization, and agricultural expansion
• Time-series analysis for environmental monitoring

Module 6: Time-Series Classification for M&E

• Classification algorithms for temporal remote sensing data
• Supervised vs. unsupervised classification in time-series analysis
• Change detection using classification results

Module 7: Advanced Change Detection Methods

• Multi-temporal image differencing and vegetation index analysis
• Post-classification comparison and multi-date comparison
• Object-based change detection techniques

Module 8: Time-Series Analysis with Google Earth Engine

• Introduction to Google Earth Engine for time-series analysis
• Accessing and processing large remote sensing datasets
• Performing temporal analysis on satellite imagery using GEE

Module 9: Using Python for Time-Series Analysis in Remote Sensing

• Basics of Python for remote sensing data analysis
• Libraries for time-series analysis: Pandas, NumPy, and Matplotlib
• Analyzing time-series data with Python and Jupyter Notebooks

Module 10: Time-Series Data Visualization and Interpretation

• Visualizing time-series trends with graphs, charts, and maps
• Interpreting results of time-series analysis in M&E projects
• Best practices for presenting time-series analysis data to stakeholders

Module 11: Time-Series Modelling for Impact Assessment

• Modelling long-term trends and projecting future changes
• Evaluating impacts of land use, urbanization, and environmental policies
• Using time-series analysis for assessing the sustainability of projects

Module 12: Incorporating Time-Series Analysis into M&E Frameworks

• Integrating time-series analysis with M&E systems
• Using time-series data for tracking development goals and indicators
• Developing actionable insights for project improvement

Module 13: Case Studies: Time-Series Analysis in Environmental Monitoring

• Real-world examples of time-series analysis in environmental monitoring
• Using remote sensing data to assess deforestation, coastal erosion, and climate change
• Analyzing disaster-prone areas with temporal data

Module 14: Advanced Applications of Time-Series Analysis in M&E

• Time-series analysis for disaster risk management and resilience monitoring
• Monitoring water resources, agriculture, and biodiversity over time
• Applications in monitoring the effects of climate change and policy interventions

Module 15: Reporting and Communicating Time-Series Results

• Best practices for creating clear and concise reports
• Communicating complex time-series analysis results to non-technical stakeholders
• Using dashboards, maps, and visualizations to present findings

Course Outcome:
By the end of this training course, participants will be equipped with the skills to effectively analyze and interpret time-series remote sensing data, providing actionable insights for monitoring and evaluating projects and environmental conditions. This comprehensive course will enhance their ability to integrate time-series analysis into their M&E activities, making data-driven decisions for more sustainable development outcomes.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.