Land use Land cover classification GIS, ERDAS, ArcGIS, ENVI
4.4 (168 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.
1,082 students enrolled

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

Land Use Scratch to Advance, All Softwares of Remote sensing and GIS. Most demanding task of GIS in Easy way learning.
4.4 (168 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.
1,082 students enrolled
Created by Lakhwinder Singh
Last updated 12/2018
English
English [Auto-generated]
Current price: $9.99 Original price: $104.99 Discount: 90% off
30-Day Money-Back Guarantee
This course includes
  • 5 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
  • 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
Requirements
  • You must have ArcGIS and ERDAS or ENVI
  • You must have basic knowledge of GIS
Description

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:

  1. Urban area and barren land has same signature

  2. Dry river reflect same signature as urban area and barren land

  3. if you try to correct urban and get error in barren

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

  5. Add new class after final work

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


Who this course is for:
  • 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
Course content
Expand all 37 lectures 05:14:06
+ Downloading and Data Processing
7 lectures 48:30

Link to Data download USGS Site https://earthexplorer.usgs.gov/

This video updated as USGS site update

Preview 11:49

Please consider ratings after watching full course. Not very early. It has still many things to understand. 

About Rating
00:17
Processing of Image in ArcGIS With Metafile
11:11
Image processing from Bands ArcGIS
04:56
Image Processing in Erdas
08:34
Removing black pixels
05:14
+ Understanding Satellite image and Google Earth Pro
5 lectures 23:12

Compare Suitability of Erdas 2014 to 2018 vs Google Earth. Updated

Why We Need Google Earth
00:53

Direct Download also available with this video

Downloading and Installing Google Earth Pro
03:51

Erdas 2018 has bug That need to be fixed. Updated Video.

Erdas 2018 - Bug fix for Google Earth Pro
02:32
More image improvement for better identification
05:41
Linking Satellite image with pro and Investigation - Don't Skip this Video
10:15
+ Which method to use and Why
1 lecture 05:08
Understanding Methods of Land Use and When to use which method.
05:08
+ Supervised Classification
5 lectures 01:03:58
Signature derivation - 1
19:47
Signature derivation -2
18:33
Signature save
01:42
Supervised classification and understand Errors
13:36
Class Value corrections
10:20
+ Unsupervised classification
1 lecture 10:52
Unsupervised classification
10:52
+ Combined classification
5 lectures 58:51
pixel Brakeout
08:32
Class Identification 1
29:33
Class Identification 2
01:26
Class information collection and arrange
10:49
Re-Code
08:31
+ Error pixel correction and New Class Generation
2 lectures 17:02
Pixel corrections of landuse class
08:53
New Class generation after landuse in same file
08:09
+ Results from Landuse
3 lectures 22:51
Calculate Area of Landuse classes
04:00
Performing Change Detection of time series land use
08:18
Making Change Detection Matrix in Excel from land use Data
10:33
+ Best Practical- Landuse Task in ArcGIS and ENVI
2 lectures 28:14
Landuse in ArcGIS
14:32
Live Landuse in ENVI
13:42
+ Miscellaneous
3 lectures 22:44
Accuracy assessment in Erdas
14:57
Thematic error Correction for Land Change Analysis
03:22
Statistical Filters to enhance final land use image
04:25