Land use Land cover classification GIS, ERDAS, ArcGIS, ENVI




  • Tipología


  • Metodología


  • Horas lectivas


  • Inicio

    Fechas disponibles

"This is first landuse landcover course on udemy the most demanding topic in GIS, In this course I covered from data download to final results. I used ERDAS, ArcGIS and ENVI. I explained all possible methods of land use classification. More then landuse, Pre-Procession of images are covered after download and after classification, how to correct error pixels are also covered, So after learning here you no need to ask anyone about lanudse classification. I explained theoretical concept also during processing of data. I have covered supervised, unsupevised, combined method, pixel correction methods etc. I have also shown to correct area specific pixels to achieve maximum accuracy. Most of this course is focused on Erdas and ArcGIS for image classification and calculations.For in depth of all methods enroll in this course. 

This course also include accuracy assessment report generation in erdas. 

Note: Each Land Use method  Section covers different Method from beginning, So before starting landuse watch entire course. Then start land use with method that  you think easy for you and best fit for your study area., then you will be able to it best. Different method are applicable for different type of study area. This course is applicable to Erdas Version 2014, 2015, 2016 and 2018.

90% practical 10% theory

Problem faced During classification:

Some of us faced problem during classification as:

Urban area and barren land has same signature

-Dry river reflect same signature as urban area and barren land

-if you try to correct urban and get error in barren

-In Hilly area you cannot classify forest which is in the hill shade area. 

-Add new class after final work

How to get rid of this all problems Join this course.


Información importante

¿Qué objetivos tiene esta formación?: "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"

¿Esta formación es para mi?: "Civil Engineers
Water Resource Experts
Master Student of GIS
PhD Students of Satellite Data Analysis
Research Scholars
GIS Analyst
Environment and Earth Science Persons
Urban and city Planner"

Requisitos: "You must have ArcGIS and ERDAS or ENVIYou must have basic knowledge of GIS"

Sedes y fechas disponibles





Fechas disponibles Inscripciones abiertas



  • Satellite
  • spatial
  • ArcGIS
  • Land Use
  • Image
  • Global
  • GIS
  • Earth
  • Geospatial Data
  • Geospatial concepts
  • Geographical data
  • Geomatics
  • Geographic Information Systems
  • Geoscience
  • Remote Sensing
  • Remote sense technology
  • Spatial analysis
  • Spatial Analyst
  • Spatial Data
  • Mapping Tool


"Downloading and Data Processing
Downloading of Latest Satellite Images
About Rating
Processing of Image in ArcGIS With Metafile
Image processing from Bands ArcGIS
Image Processing in Erdas
Image Enhancement
Removing black pixels
Understanding Satellite image and Google Earth Pro
Why We Need Google Earth
Downloading and Installing Google Earth Pro
Erdas 2018 - Bug fix for Google Earth Pro
More image improvement for better identification
Linking Satellite image with pro and Investigation - Don't Skip this Video
Which method to use and Why
Understanding Methods of Land Use and When to use which method.
Supervised Classification
Signature derivation - 1
Signature derivation -2
Signature save
Supervised classification and understand Errors
Class Value corrections
Unsupervised classification
Unsupervised classification
Combined classification
pixel Brakeout
Class Identification 1
Class Identification 2
Class information collection and arrange
Error pixel correction and New Class Generation
Pixel corrections of landuse class
New Class generation after landuse in same file
Results from Landuse
Calculate Area of Landuse classes
Performing Change Detection of time series land use
Making Change Detection Matrix in Excel from land use Data
Best Practical- Landuse Task in ArcGIS and ENVI
Landuse in ArcGIS
Live Landuse in ENVI
Accuracy assessment in Erdas
Thematic error Correction for Land Change Analysis
Statistical Filters to enhance final land use image
Miscellaneous Task - Cut Your Study Area
Cut Study Area in Erdas
Cut Study Area in ArcGIS
Download Data used in Course
Download Files of Course
Bonus Lecture"

Land use Land cover classification GIS, ERDAS, ArcGIS, ENVI