Udemy

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English

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Object-based Image Analysis & Classification in QGIS ArcGIS

Learn image segmentation and object-based image analysis OBIA & object-based image classification in QGIS & ArcGIS , GIS

4.54 (22 reviews)

620

Students

3 hours

Content

Nov 2020

Last Update
$84.99
Regular Price

What you will learn

Learn image segmentation, object-based image analysis (OBIA) & object-based image classification in QGIS & ArcGIS

Advance your skills in QGIS and ArcGIS

Understand the concept of segmentation and object-based image analysis

Learn theory and practise behind land use & land cover mapping

Learn how to work with the variety of remote sensing data streams (UAV data. satellite images)

Apply segmentation and object-based image classification in QGIS (OTB) and ArcGIS

You'll have a copy of the labs, step-by-step manuals and scripts used in the course for QGIS and ArcGIS & more

Conduct your independent OBIA projects in QGIS & ArcGIS




Description

Object-based Land Use / Land Cover mapping with Machine Learning and Remote Sensing Data in QGIS ArcGIS

This course is designed to take users who use QGIS & ArcGIS for basic geospatial data/GIS/Remote Sensing analysis to perform more advanced geospatial analysis tasks including segmentation, object-based image analysis (OBIA) for land use, and land cover (LULC) tasks using a variety of different data, and applying Machine Learning state of the art algorithms. In addition to level up your skills in QGIS, ArcGIS for spatial data analysis, you will be introduced to a powerful opportunity to learn how to use ArcGIS also for advanced satellite-based image analysis for the most demanded task in Remote Sensing, that is land use and land cover mapping.

I'm very excited that you found my intermediate to advance object-based image analysis for the LULC mapping course. This course is designed to equip you with the practical knowledge of advanced Land Use and Land Cover (LULC) mapping, which is one of the core skills for any Geographic Information Systems (GIS) and Remote Sensing analyst. By the end of the course, you will feel confident and completely understand and apply advanced Geospatial analysis including performing Machine Learning algorithms for land use and land cover mapping and learning object-based image analysis and basics of segmentation. All this you will be able to carry out on the real data in one of the most popular GIS software which is ArcGIS and QGIS.

Please, note: this course is best suited for the users with the basic knowledge of Remote Sensing image analysis.

This course is different from other training resources. Each lecture seeks to enhance your GIS and Remote Sensing skills in a demonstrable and easy-to-follow manner and provide you with practically implementable solutions. You’ll be able to start analyzing spatial data for your own projects, and gain appreciation from your future employers with your advances GIS skills and knowledge of the cutting edge LULC techniques.

In the course, you will be able to learn the theory behind OBIA and LULC mapping, as well as basics information on how to work with the satellite images. I will show you how to perform image segmentation in QGIS/ ArcGIS and how to carry out all stages of object-based LULC mapping. I also will show you how to apply OBIA for a real-life example of an object-based crop classification task with the real project-data. All image classification routines we will implement using state-of-the-art Machine Learning algorithms such as Random Forest and Support Vector Machines.

The course is ideal for professionals such as geographers, programmers, social scientists, geologists, GIS, and Remote Sensing experts and all other experts who need to use LULC maps in their field and would like to learn the fundamentals of LULC and change detection in GIS. If you're planning to undertake a task that requires to use a state of the art classification algorithms for creating, for instance, land cover and land use maps, this course will give you the confidence you need to understand and solve such geospatial problem.

One important part of the course is the practical exercises. You will be given some precise instructions, codes, and datasets to create LULC maps and change maps using the ArcGIS & QGIS software

INCLUDED IN THE COURSE: You will have access to the data used in the course, along with the Java code files. You will also have access to future resources. Enroll in the course today & take advantage of these special materials!


Screenshots

Object-based Image Analysis & Classification in QGIS ArcGIS
Object-based Image Analysis & Classification in QGIS ArcGIS
Object-based Image Analysis & Classification in QGIS ArcGIS
Object-based Image Analysis & Classification in QGIS ArcGIS

Content

Introduction & Software used for the course

Introduction

Installation of the software needed for the course

Install QGIS on your PC

OTB installation

ArcGIS Software

Introduction to object-based image analysis in GIS & Remote Sensing

Section Overview

Theory: How to work with the Remote Sensing imagery

Segmentation and object-based image analysis (OBIA)

Object-based image classification (OBIA) VS pixel-based image classification

Section Overview

Image Segmentation in GIS & Remote Sensing

Principles of image segmentation for GIS and Remote Sensing analysis

Lab: Segmentation of high-resolution satellite image in QGIS

Lab: image segmentation fin ArcGIS

Theory: What is image classification of Remote Senisng images?

Section 5: Overview

Introduction to supervised and unsupervised image classification

Main steps of land use/ land cover (LULC) mapping with Remote Sensing images

Accuracy Assessment of LULC maps

Object-based Image classification with Machine Learning algorithms in ArcGIS

Object-based image classification in ArcGIS part 1: training data

Object-based image classification (OBIA) using airborne data in ArcGIS

Object-based crop classification with Machine Learning algorithms in QGIS

Segmentation of high-resolution satellite image in QGIS

Creating training data from satellite image based on the segmented layer

Object-based image classification with the Machine Learning algorithms

Object-based crop fields classification in QGIS

Object-based image classification in QGIS with OTB for crop analysis

Feature Extraction for object-based crop classification

Training of Machine learning Classifiers for object-based crop classification

Object-based crop classification with Machine Learning algorithms in QGIS

Final Project Description

Your OBIA Project in ArcGIS

Your OBIA Project in QGIS

BONUS



Reviews

N
Natalia11 January 2021

This was all new to me. I had some prior knowledge from non-related courses on GIS, but most of this was pretty new and nifty to me. The course seemed is very engaging and the instructor is great.

F
Fabian30 December 2020

Ik heb er veel van opgestoken. De secties zijn kort en overzichtelijk. De verdeling tussen theorie en praktijk is goed. De theorie over object-based image classification wordt toegepast in QGIS en in ArcGIS.

А
Анастасия20 December 2020

Object-based image analysis with QGIS is very useful and methods of its application have been brilliantly explained by the instructor through the lectures in the course.

Н
Наталья17 December 2020

This course was recommended to me by a friend. Using QGIS makes for OBIA analysis makes GIS Spatial Data Analysis easier! The instructor made that informative sections much easier to understand. Thank you!

А
Айнур17 December 2020

I enjoy the lectures. The instructor has a good teaching style which keeps me interested. Lots of concrete examples make it easier to understand. Great learning experience.

J
Jessie16 October 2020

I was looking long-time for a course on object-based image analysis and finally, Kate made it. I am very satisfied with the content. Great to work on OBIA in QGIS and ArcGIS.


Coupons

StatusDateDiscount
Expired10/15/2020100% OFF


3550448

Udemy ID

10/6/2020

Course created date

10/15/2020

Course Indexed date
Angelcrc Seven
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