Land use Land cover classification GIS, ERDAS, ArcGIS, ML
Machine Learning, Land Use Scratch to Advance, All Softwares of Remote Sensing and GIS, GIS Tasks in Easy way learning.
4.45 (593 reviews)
3 338
students
6.5 hours
content
Apr 2024
last update
$13.99
regular price
What you will 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
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Our Verdict
This course is a must-enroll for those looking to expand their knowledge in remote sensing, image processing, and land use classification. The instructor's expertise shines through the content with easy-to-follow examples, even though some learners might need additional guidance on specific software. However, the majority of those who complete the course appreciate the practical applications covered and leave equipped to implement their newfound skills in real-life projects.
What We Liked
- Comprehensive coverage of land use classification using various software including ERDAS, ArcGIS, and ML
- In-depth explanation of image processing and analysis techniques, accuracy assessment report generation, and pixel level corrections
- Real-life scenarios and practical examples make the learning experience engaging and effective
- High-quality video content and step-by-step guidance for all levels of learners
Potential Drawbacks
- Lack of focus on specific software (ArcGIS) requested by some learners, which may limit its applicability in certain use cases
- A few learners reported issues in following the instructions due to variations in software interfaces across versions
- While most learners appreciated the theoretical knowledge provided, a handful of users expressed a desire for more hands-on assignments
- Limited scope for pre-processing tasks like atmospheric corrections and radiometric correction
Related Topics
1482476
udemy ID
26/12/2017
course created date
08/02/2020
course indexed date
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