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.
