Future Land Use with GIS - TerrSet - CA Markov - ArcGIS

CA Markov Model Machine Learning Approach. ArcGIS Erdas QGIS used for data Preparation and TerrSet for Prediction GIS

4.60 (218 reviews)
Udemy
platform
English
language
Other
category
809
students
4 hours
content
Feb 2023
last update
$69.99
regular price

What you will learn

You will be able to

Predict future expansion of urban area and generate future map.

Understand Advance concept of GIS and hands on

Advance concept In ArcGIS and Terrset Software

Understand Working with DEM

Running Advance Queries in GIS

Handling complex data of GIS

CA Markov Model

See Machine Learning in Action

Validation of Generated Results

Other Related task to GIS like UTM Zone, Mosaic of Digital Elevation Model

Description

In this course you will see Machine learning in Action using readymade land Change model Terrset (formerly IDRISI ) . This course used Terrset Software with CA Markov method to predict future landuse ArcGIS is used to prepare data. Erdas also used for some task. No coding is used .All software used in this course are NOT Open Source. You need to manage software. You must know to prepare landuse maps rest of things covered in this course from scratch. Future prediction of landuse depends on number of drivers/Parameters. Drives means forces which decide how the future urban area will look. It includes many drives like, old city boundary because new settlement will be constructed near to old city boundary. Roads and relief are also one of factors, because first roads near city covered by settlement. On another side how, much possibility at different location on agriculture site that can be convert to urban. Similarly, forest cover also. We also need to avoid some landuse classed like water, river, lake or reservoir never convert to urban. So, we need to setup our model in such a way so that it avoids water. After setting accuracy of learning and output accuracy also matters. We also need to modify it. In this course we have achieved learning accuracy of 42%, and 67% in two different runs. But 89% accuracy we have achieved in predicted landuse. Learning and prediction accuracy is different on computer to computer and data to data. While running you will receive more or less accuracy then this course. But focus on your output results. If Learning accuracy was 100% then it also wrong. So, see and understand each video carefully. Then run you model. You must see free preview video before enrolling this course. Because this is Expert level course.

Note: Who having IDRISI Taiga They can also follow same steps.

This course covers 90% Practical and 10% Theory.

Don’t hesitate to ask me Questions in QA Session.

Content

Introduction

What will be output after this course
Pre-course requirements
Introduction
Software Requirement

About Software and Methodology

TerrSet download
Methodology
Data UTM Intro
Understanding landuse value order
Landuse that we already Have – A look

Preparing Landuse related Drivers

Getting Ready Our Landuse for future Input
Urban Landuse Setting up for Model
Disturbances Urban

Roads Process

Downloading for Roads
Downloading QGIS
Street Map Conversion
Cut Vector layer to study area
Road Separation from other line features in Data using Query
Road distance

Downloading DEM and Prepare data of Landuse and Slope for Model input

Downloading Dem
Prepare Elevation Model for use with Prediction model
Process landuse with Erdas to be ready for model
Process Landuse in ArcGIS (Optional)
Slope Just A simple work

Data Management

Arrange Data for Batch Processing

Zero and one Road Layer generation (Optional)

Adding optional road layer to main data

Project Setup and Starting Land change Model in Terrset, Data conversion

Project setup in Terrset
Tiff File conversion for Model
Setting up Land Change Modeler and Image modification
Estimating Spatial Trend Change probabilities for Landuse

Transition sub model and parameter Power Test on landuse

Setting up and understand transition sub model for Land change
Testing power of Drivers and Sub Model setup

Machine Learning in Action – CA Markov Chain Model, Future Predictions

Running the Machine Learning and MLP Model
Generating future Image with Markov Chain Model

Validation of Results

Validation Method 1 Terrset
Validation Method 2 ArcGIS

After Validation Generate Future images and understand concept of Matrix

Future Landuse image Generation for year 2030,2050,2100
Modification of Future image with Matrix probability
Generation video of Urban Growth and Intermediate stage images till 2100 year
Understanding Model Settings what to change and run Model again, understanding
Resuming work after save

What if run with different landuse and different settings an Extra Run Results

Impact on Learning of land use class Full Model results. Extra with more classes

Additional GIS Task you may need it to prepare data

Convert whole Terrset Project files for ArcGIS
Method 1 for mosaic of DEM in ArcGIS
Method 2 mosaic of DEM in ArcGIS
Finding correct UTM inside ArcGIS and Reprojection to UTM
Last video

Download Data

Data Download

Screenshots

Future Land Use with GIS - TerrSet - CA Markov - ArcGIS - Screenshot_01Future Land Use with GIS - TerrSet - CA Markov - ArcGIS - Screenshot_02Future Land Use with GIS - TerrSet - CA Markov - ArcGIS - Screenshot_03Future Land Use with GIS - TerrSet - CA Markov - ArcGIS - Screenshot_04

Reviews

Franklin
April 6, 2023
Yes, it is perfect for my research. I wish it also covered mosaicing because my DEM is more than one tile.
Yew
August 5, 2022
Because you are doing what we need to do. You have to show the student to do. it .Only focus of TERRSET software that is what my university Murdoch is doing we have a work book but I am weak at follow all the command describe in the workbook
Daniela
January 22, 2021
Me ayudó mucho aplicar todo lo aprendido para la zona en donde yo vivo, y a complementar mejor mi proyecto de maestría, agradezco mucho al profesor por compartir sus conocimientos. Excelente curso, felicitaciones!!
Woheeul
October 22, 2020
nice experience. nice course. and it's really very helpful for me. very good explanation, and really thankful for the quick response of the questions.
Bibek
May 9, 2020
There are very very few resources to even learn terrset let alone use it for future land use prediction. It is a very good and relevant course to take your gis skill to the advanced level.
Luis
February 5, 2020
For me this course was extremely positive, as I could understand the process, and follow all the details without get lost. The instructor has great knowledge of the subject, and the lessons are easy to follow and well explained.
Vivek
July 20, 2019
One of the best courses i have seen.... Lakhwinder has an amazing grasp on his subject. Wonderful and superb..
Eduardo
July 11, 2019
the course is reasonable to learn a specific technique, the biggest problem is the pronunciation of English, I understand that sometimes it is difficult to demand that from this instructor because it's not his mother tongue, but ideally would be better to provide better subtitles in order to compensate for his lack of better pronunciation.
Pijush
April 9, 2019
The course was excellent training with a wonderful explanation. The course is very helpful. Thank You Very much, sir.
Ayad
February 18, 2019
Many thanks to Dr. Singh, and to Udemy as well. I appreciate their valuable efforts very much. On the other side, I hope that Dr. Singh could organize a new course entitled (Object-based classification and image segmentation using eCognition software). That course is very requested by many of our colleagues and students. So, please take this request in your priorities. Many thanks again. Ayad Fadhil
Nabeen
February 11, 2019
This video is perfect as my requirement and i hope it is equally helpful to others who wants to learn to predict future land use from past and present year data.
Karl
January 28, 2019
Excellent course!! I would like to know how to evaluate changes in agricultural areas for example and the drivers that we have to provide into the model. also, how to insert incentives and restrictions into the model. What is the difference between this method and the CA_MARCOV method?? Thanks so much!!
Mohd
October 11, 2018
Im really greatful for this tutorial because it describe each and everything for the person who want to work in the field of urban planning or as a civil engineer to simulate the urban sprawl of any region.
Peter
September 16, 2018
What a great course is this, thanks to the Instructor for making this course and also Udemy. It is very important course to all working with land-use issues. I recommend this course to all people working with GIS. also I liked the addition lecture it elaborate a some ideas that i always do wrong without knowing and it is not taught in class. Very important ideas are elaborated clearly. Thanks Again. keep it up. hope there will be more to come.
Manish
September 11, 2018
This course has extremely useful for prediction of future land use changes. each and every step needed to achieve the objective is explained in-depth and greater details. this course involves both very basic and advance things. The course gives you a flavor of Remote Sensing and GIS techniques. and exposure to a variety of software and websites. I appreciate great efforts of the tutor. He has really done a commendable job, taken his time to elaborate carefully on each step while predicting future land use. This course can be extremely useful and helpful for many of the research scholars who are looking for predicting future land use.

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1464748
udemy ID
12/10/2017
course created date
2/8/2020
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