Land use Land cover classification ArcGIS ERDAS ENVI and ML (Udemy.com)
Machine Learning, Land Use Scratch to Advance, All Softwares of Remote Sensing and GIS, GIS Tasks in Easy way learning.
Created by: Lakhwinder Singh
Last updated August 2026
What you will learn
- Able to do a Prefect Land use classification of Earth using satellite image
- Also learn image Processing and analysis in depth
- Landuse change Detection
- Understand Features identification on Earth using Landsat Image
- Post Landuse Pixel level corrections
- Accuracy Assessment Report
- Downloading of best satellite image and process
- Understanding FCC satellite image and bands
- Pixel level correction in land use at specific area and statistical filters
- Calculate area from Pixels
- Generate new class after final landuse
- Learn all best method of classification.
- How to achieve maximum accuracy of classification
- Cut Study Area
- Classify with Machine Learning
- Support Vector Machine
- Random Forest
How it compares
Against the other 335 rated Udemy courses in Engineering on CourseDuck:
- Rating4.3 out of 5higher than 28% of them
- Reviews623#129 of 336 by number of reviews
- Length6.7 hourslonger than 61% of them
- Last updatedAugust 2026more recently than 93% of them
Course Description
Most of this course is focused on Erdas and ArcGIS for image classification and calculations. For in-depth of all methods enrol in this course. Image classification with Machine learning also covered in this course. This course also includes an accuracy assessment report generation in erdas.
Note: Each Land Use methodSection covers different Method from the beginning, So before starting landuse watch the entire course. Then start land use with a method that you think easy for you and best fit for your study area., then you will be able to it best. Different method is applicable to a different type of study area. This course is applicable to Erdas Version 2014, 2015, 2016 and 2018. and ArcGIS Version 10.
1 and above, i.
e 10.
4, 10.
7 or 10.
890% practical 10% theoryProblem faced During classification:
Some of us faced problem during classification as:
Urban area and barren land has the same signatureDry river reflectthe same signature as an urban area and barren landif you try to correct urban and get an error in barrenIn Hilly area you cannot classify forest which is in the hill shade area.
Add new class after final workHow to get rid of this all problems Join this course.
Who this course is for:
Civil EngineersWater Resource ExpertsMaster Student of GISPhD Students of Satellite Data AnalysisResearch ScholarsGIS AnalystEnvironment and Earth Science PersonsUrban and city Planner
Instructor Details
- 4.3 Rating
623 Reviews
Lakhwinder Singh
I doing PhD at IIT Roorkee. I have wide Experience of GIS more than 12 years. I have developed my Own Models, Online Apps. Performed Automated task in GIS for faster Project management. I did many real projects for Govt. Like planing of the lake. Discharge Simulation, Soil Erosion, Sediment model development and analysis. Research is published in International Journals. You can find me on Research-gate also. I answer GIS Queries around the world with my GIS Facebook page followed by 25k and Youtube followed by 48k. and running worldwide GIS discussion group with 50k Expert of GIS around the world. Even I have a free Basic tutorial website. I alsotaughtGIS course for Govt Engineers sponsored by Govt with real-life problems and discussion. So I have wide Experience of the teaching of GIS. I know how to teach difficult task in an Easy way. I am providing a course at my own place to student around the world. Including Nepal, India, Ghana, Ethiopia, Zambia, South Africa, etc At my own place I teaching full GIS course from Basic to Advanced covering 124 topics. My student required just basic knowledge of computer and they will become GIS Expert at End of Course.
Received International Award for Best SWAT Support, from Texas A&M University, USA and USDA at Brussels, Belgium
All course 90% practical 10% theory
My training Method of Different than All others. More user friendly from practical Examples. I know how our brain learns scientifically.
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Reviews
By Kssenthillkumar on 11/15/2020
excellant and outstanding thanks sir
By Elnur Safarov on 11/8/2020
Excellent Course reccomend
By Ruchi Vasudeva on 11/8/2020
Really Good and informative. Explanation and detailing of every component is clear and precise.
By Ivan Taslim on 10/21/2020
Great course for beginner
By Ana Crdenas on 10/16/2020
Se me complic el idioma, y no explic con claridad los ejercicios
By M Leela Priyanka on 8/26/2020
very easy to understand
By Sujathaa on 8/18/2020
This course is very useful for all GIS learners ,easy to understand for all beginners. i learnt lot from this course.
By Parimita Saikia on 8/17/2020
Great beginner course with a little GIS background to learn application of Machine learning in the field of GIS
By Burt Samuelson on 8/14/2020
It oriented me to the field of remote sensing. It gave me the knowledge of where and how to download satellite and aerial images. The course exposed me to some of the particulars of the software packages. For example, I know to download image files in a particular order, which is really important in ArcGIS and I think one other software package. I know how to put images in a certain order to get a natural color or infrared image, as an example. And, of course, I learned about classifying land uses using major remote sensing software packages. I understand how spatial analysis is done using satellite and aerial images. Now, it's something that's becoming familiar, which means I'm in a good position to learn more about this field.
By Bhaskar K on 7/27/2020
detailed explanation
By Yong Jie Wong on 7/9/2020
One of the best course I have ever taken and learned in Udemy. I would like to encourage anyone who is planning to work on Remote Sensing to take this course. The instructor is the best lecturer that I have ever had, even in real life.
By Satya Raj on 7/3/2020
The teacher is explaining every details and going quite consistently..
Quality Score
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Overall Score : 86 / 100







