Land use Land cover classification GIS, ERDAS, ArcGIS, ENVI
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
Classify with Machine Learning
Support Vector Machine
Random Forest
Requirements
You must have ArcGIS and ERDAS or ENVI
You must have basic knowledge of GIS
Description
This is the 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, ENVI and MACHINE LEARNING. I explained all the 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 the theoretical concept also during the processing of data.
I have covered supervised, unsupervised, 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 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 method Section 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 10.8
90% practical 10% theory
Problem faced During classification:
Some of us faced problem during classification as:
Urban area and barren land has the same signature
Dry river reflect the same signature as an urban area and barren land
if you try to correct urban and get an 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.
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
h264, yuv420p, 1280x720 |ENGLISH, 44100 Hz, 2channels | 6h 23mn | 3.15 GB
3.03GB
Download
*
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
Classify with Machine Learning
Support Vector Machine
Random Forest
Requirements
You must have ArcGIS and ERDAS or ENVI
You must have basic knowledge of GIS
Description
This is the 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, ENVI and MACHINE LEARNING. I explained all the 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 the theoretical concept also during the processing of data.
I have covered supervised, unsupervised, 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 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 method Section 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 10.8
90% practical 10% theory
Problem faced During classification:
Some of us faced problem during classification as:
Urban area and barren land has the same signature
Dry river reflect the same signature as an urban area and barren land
if you try to correct urban and get an 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.
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
h264, yuv420p, 1280x720 |ENGLISH, 44100 Hz, 2channels | 6h 23mn | 3.15 GB
3.03GB
Download
*
