Future Land Use with GIS - TerrSet - CA Markov - ArcGIS
4.1 (89 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
342 students enrolled

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
4.1 (89 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
342 students enrolled
Created by Lakhwinder Singh
Last updated 8/2019
English [Auto]
Current price: $30.99 Original price: $44.99 Discount: 31% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 4 hours on-demand video
  • 1 article
  • 1 downloadable resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll 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
  • You Must know Basic of GIS
  • Familiar with ArcGIS, ERDAS Just basics
  • You Must have software Terrset and ArcGIS both are NOT Open Source. You need to manage.
  • Must know how to prepare land use. This is advanced course. Otherwise first learn Landuse mapping using other course.
  • You must have two landuse with Good Accuracy

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.

Who this course is for:
  • Water Resource Engineers
  • Urban Planner
  • Land Mangement teams
  • Student of GIS Masters and Phd Level
  • Student of Remote Sensing
  • Civil Enginners
  • Remote Sensing and GIS Project Scientist
Course content
Expand all 47 lectures 04:03:34
+ Preparing Landuse related Drivers
3 lectures 24:27
Getting Ready Our Landuse for future Input
Urban Landuse Setting up for Model
Disturbances Urban
+ Roads Process
6 lectures 27:52
Downloading for Roads
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
5 lectures 34:04
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
1 lecture 04:37
Arrange Data for Batch Processing
+ Zero and one Road Layer generation (Optional)
1 lecture 11:00
Adding optional road layer to main data
+ Project Setup and Starting Land change Model in Terrset, Data conversion
4 lectures 16:41
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
2 lectures 09:26
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
2 lectures 14:45
Running the Machine Learning and MLP Model
Generating future Image with Markov Chain Model