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Course Highlights:

Discover the Power of Object-Based Land Use and Land Cover Mapping with Machine Learning and Remote Sensing Data in QGIS and ArcGIS

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Course Highlights:

Discover the Power of Object-Based Land Use and Land Cover Mapping with Machine Learning and Remote Sensing Data in QGIS and ArcGIS

This comprehensive course is tailored for individuals familiar with QGIS and ArcGIS basics, seeking to advance their geospatial analysis skills. Dive into sophisticated geospatial analysis techniques, including segmentation and object-based image analysis (OBIA) for land use and land cover (LULC) mapping, all while applying cutting-edge Machine Learning algorithms. Elevate your expertise in QGIS, ArcGIS, and satellite-based image analysis to master one of the most sought-after tasks in Remote Sensing: land use and land cover mapping.

Course Introduction:

Welcome to this intermediate to advanced course on object-based image analysis for land use and land cover (LULC) mapping. Designed to equip you with practical knowledge in advanced LULC mapping, a crucial skill for Geographic Information Systems (GIS) and Remote Sensing analysts, this course empowers you to confidently perform Machine Learning algorithms for LULC mapping, grasp object-based image analysis, and understand the basics of segmentation. All of this will be executed on real data within two of the most popular GIS software platforms: ArcGIS and QGIS.

Prerequisite Knowledge:

Please note that this course is best suited for individuals with basic knowledge of Remote Sensing image analysis.

Unique Approach:

This course distinguishes itself from other training resources through its hands-on, easy-to-follow approach. Each lecture aims to enhance your GIS and Remote Sensing skills, providing practical solutions. You'll gain the capability to analyze spatial data for your own projects, earning recognition from future employers for your advanced GIS skills and mastery of cutting-edge LULC techniques.

Course Content:

Throughout the course, you'll explore the theory behind OBIA and LULC mapping and gain fundamental insights into working with satellite images. You'll discover how to perform image segmentation in QGIS and ArcGIS, mastering all stages of object-based LULC mapping. Additionally, you'll apply OBIA to a real-life object-based crop classification task using actual project data. All image classification processes will leverage state-of-the-art Machine Learning algorithms, including Random Forest and Support Vector Machines.

Target Audience:

This course caters to professionals in various fields, including geographers, programmers, social scientists, geologists, GIS and Remote Sensing experts, and others who require LULC maps and aim to grasp the fundamentals of LULC and change detection in GIS. If you're planning to undertake tasks that demand the use of cutting-edge classification algorithms to create land cover and land use maps, this course will equip you with the confidence and skills to tackle such geospatial challenges.

Practical Exercises:

Engage in practical exercises featuring precise instructions, code snippets, and datasets to create LULC maps and change maps using ArcGIS and QGIS.

Course Inclusions:

Enroll in this course today to gain access to course data, Java code files, and future resources, ensuring a comprehensive learning experience. Don't miss out on this opportunity to expand your geospatial analysis skills.

Enroll now

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches learners to perform Machine Learning algorithms for LULC mapping, a core skill in RS and GIS
Develops expertise in Remote Sensing image analysis, QGIS, and ArcGIS for LULC mapping
Builds a strong foundation for beginners seeking to advance their geospatial analysis skills
Provides in-depth knowledge of OBIA and LULC mapping for professionals
Offers hands-on labs and interactive materials to enhance learners' experiences
Adheres to best practices and conforms to industry standards in LULC mapping

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Object-based Image Analysis & Classification in QGIS ArcGIS with these activities:
Read: 'Remote Sensing and Image Interpretation' by Thomas M. Lillesand and Ralph W. Kiefer
Gain a deeper theoretical understanding of remote sensing and image interpretation concepts, which will enhance your application of OBIA and LULC mapping techniques.
Show steps
  • Read Chapter 10: 'Image Processing and Analysis'
  • Read Chapter 11: 'Digital Image Classification'
  • Read Chapter 12: 'Accuracy Assessment and Error Analysis'
Compile a Collection of LULC Mapping Resources
Enhance your learning by gathering and organizing a collection of useful resources related to LULC mapping, including articles, tutorials, datasets, and tools.
Browse courses on Resources
Show steps
  • Conduct online searches for LULC mapping resources.
  • Identify and bookmark articles, tutorials, and datasets relevant to the course.
  • Create a folder or document to store and organize the resources.
Image Segmentation Practice Exercises
Improve your image segmentation skills by completing a series of guided exercises in QGIS or ArcGIS, focusing on selecting appropriate segmentation parameters.
Browse courses on Image Segmentation
Show steps
  • Load a satellite image into QGIS or ArcGIS.
  • Experiment with different segmentation algorithms and parameters.
  • Evaluate the results of your segmentation and adjust parameters as needed.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Introductory Project: Object-Based LULC Mapping
Build a solid foundation by applying core concepts of object-based image analysis (OBIA) to a real-world LULC mapping project using QGIS or ArcGIS.
Show steps
  • Create a new project and import satellite imagery.
  • Perform image segmentation to divide the image into meaningful objects.
  • Extract features from the segmented objects.
  • Train and apply a machine learning classifier to classify the objects into LULC categories.
  • Evaluate the accuracy of your classification and make adjustments as needed.
Follow a Tutorial on Machine Learning for LULC Mapping
Enhance your understanding of machine learning algorithms for LULC mapping by following a guided tutorial using QGIS or ArcGIS.
Browse courses on Machine Learning
Show steps
  • Find a tutorial on machine learning for LULC mapping.
  • Follow the steps in the tutorial to train and apply a machine learning classifier.
  • Interpret the results of your classification.
Attend a GIS or Remote Sensing Conference or Webinar
Expand your knowledge and connect with professionals in the field by attending a GIS or remote sensing conference or webinar, focusing on LULC mapping.
Browse courses on Networking
Show steps
  • Research upcoming GIS or remote sensing conferences or webinars.
  • Identify sessions or presentations related to LULC mapping.
  • Attend the sessions and take notes.
  • Connect with speakers and other attendees.
Volunteer with a Local GIS or Conservation Organization
Gain practical experience and apply your LULC mapping skills by volunteering with a local organization working on conservation or land management projects.
Browse courses on Volunteering
Show steps
  • Research local GIS or conservation organizations.
  • Identify opportunities to contribute your skills in LULC mapping.
  • Contact the organization and offer your services.
  • Participate in projects and contribute to the organization's goals.

Career center

Learners who complete Object-based Image Analysis & Classification in QGIS ArcGIS will develop knowledge and skills that may be useful to these careers:
Remote Sensing Analyst
Remote Sensing Analysts use satellite imagery and other data to study the Earth's surface. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to analyze remote sensing data, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful Remote Sensing Analyst.
Environmental Scientist
Environmental Scientists study the environment and develop solutions to environmental problems. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to analyze environmental data, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful Environmental Scientist.
Transportation Planner
Transportation Planners develop plans for the development of transportation systems. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to analyze transportation planning data, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful Transportation Planner.
Water Resources Engineer
Water Resources Engineers design and manage water resources systems. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to analyze water resources data, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful Water Resources Engineer.
Land Use Planner
Land Use Planners develop plans for the use of land. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to analyze land use data, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful Land Use Planner.
Natural Resource Manager
Natural Resource Managers manage natural resources, such as forests, water, and soil. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to analyze natural resource data, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful Natural Resource Manager.
GIS Specialist
GIS Specialists use GIS software to create and analyze maps. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to create maps, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful GIS Specialist.
Geospatial Analyst
Geospatial Analysts are responsible for collecting, analyzing, and interpreting geographic data. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to analyze spatial data, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful Geospatial Analyst.
Urban Planner
Urban Planners develop plans for the development of cities and towns. This course will help you develop the skills needed to perform these tasks. You will learn how to use QGIS and ArcGIS to analyze urban planning data, and you will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills are essential for a successful Urban Planner.
Project Manager
Project Managers plan and execute projects. This course may be useful for aspiring Project Managers who want to learn how to use QGIS and ArcGIS to manage spatial data projects. You will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills can be helpful for Project Managers who work on projects related to environmental science, urban planning, or transportation planning.
Data Scientist
Data Scientists use data to solve problems. This course may be useful for aspiring Data Scientists who want to learn how to use QGIS and ArcGIS to analyze spatial data. You will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills can be helpful for Data Scientists who work on projects related to environmental science, urban planning, or transportation planning.
Software Engineer
Software Engineers develop software applications. This course may be useful for aspiring Software Engineers who want to learn how to use QGIS and ArcGIS to develop spatial data applications. You will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills can be helpful for Software Engineers who work on projects related to environmental science, urban planning, or transportation planning.
Business Analyst
Business Analysts use data to make business decisions. This course may be useful for aspiring Business Analysts who want to learn how to use QGIS and ArcGIS to analyze spatial data. You will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills can be helpful for Business Analysts who work on projects related to environmental science, urban planning, or transportation planning.
Financial Analyst
Financial Analysts use data to make investment decisions. This course may be useful for aspiring Financial Analysts who want to learn how to use QGIS and ArcGIS to analyze spatial data. You will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills can be helpful for Financial Analysts who work on projects related to environmental science, urban planning, or transportation planning.
Marketing Manager
Marketing Managers develop and execute marketing campaigns. This course may be useful for aspiring Marketing Managers who want to learn how to use QGIS and ArcGIS to analyze spatial data. You will also learn how to apply Machine Learning algorithms to land use and land cover mapping. These skills can be helpful for Marketing Managers who work on projects related to environmental science, urban planning, or transportation planning.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Object-based Image Analysis & Classification in QGIS ArcGIS.
Provides a comprehensive overview of image processing and computer vision, and introduces the mathematical and computational techniques used in these fields.
Offers a comprehensive overview of GIS, covering the principles, concepts, applications, and management of GIS, providing a solid foundation for understanding the field and its real-world applications.
Provides a comprehensive overview of computer vision, and introduces the algorithms and techniques used in the field, offering a solid foundation for understanding the theoretical and practical aspects of computer vision.
Offers a comprehensive introduction to pattern recognition and machine learning, covering the principles and algorithms used in these fields, providing a solid foundation for understanding the theoretical and practical aspects of pattern recognition and machine learning.
Provides a comprehensive overview of machine learning from a probabilistic perspective, covering the principles and algorithms used in the field, offering a solid foundation for understanding the theoretical and practical aspects of machine learning from a probabilistic perspective.
Offers a comprehensive overview of deep learning, covering the principles and algorithms used in the field, providing a solid foundation for understanding the theoretical and practical aspects of deep learning.

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