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

  • Začetnik teme dlreleases
  • Datum pokretanja
D

dlreleases

UPLOADER
Učlanjen(a)
01.05.2019
Poruka
50.566

h264, yuv420p, 1280x720 |ENGLISH, 44100 Hz, 2channels | 6h 23mn | 3.15 GB

Land Use Scratch to Advance, All Softwares of Remote sensing and GIS.​

Machine Learning, GIS Tasks in Easy way learning.
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

ing 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 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 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 bning, 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 Eeers

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



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http://nitroflare.com/view/51661AAB2BB0F6D/q3NxSAAr__Land_use_L.part1.rar
http://nitroflare.com/view/EE31755B395429E/q3NxSAAr__Land_use_L.part2.rar
http://nitroflare.com/view/9EA3AAD5D8FE2D1/q3NxSAAr__Land_use_L.part3.rar
http://nitroflare.com/view/2E0082E9E41A3A4/q3NxSAAr__Land_use_L.part4.rar
 
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