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Pixel- and Object-based High-Resolution Image Processing
Pixel- and Object-based High-Resolution satellite Image classification in ENVI software (FAST TRACK)
This Course Includes
udemy
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2 total hours 
english
Online - Self Paced
course
Udemy
About Pixel- and Object-based High-Resolution Image Processing
High-resolution satellite imagery classification for land cover land use mapping is a critical aspect of Earth’s surface monitoring and mapping. In this course, land cover land use mapping using the well-known ENVI software is covered. You will learn how to use supervised algorithms, such as Artificial Neural Networks (ANN) and Maximum Likelihood classifier (MLC) to classify high-resolution satellite imagery. Pixel-based and object-based image classification is also discussed. Object-based feature extraction using high-resolution imagery is presented. You will learn how to use unsupervised algorithms, such as the k-means algorithm for satellite image clustering. The discussed methods can be utilized for different object/feature extraction and mapping (i.e., urban region extraction from high-resolution satellite imagery). Remote sensing is a powerful tool that can be used to identify and classify different land types, assess vegetation conditions, and estimate environmental changes. The validation of the models is also covered. In summary, remote sensing and GIS technologies are widely used for land cover mapping. They provide accurate and timely information that is critical for monitoring and managing natural resources.
Highlights:
Learn how to use unsupervised algorithms in ENVI software
Learn how to use supervised algorithms in ENVI software
Learn pixel-based high-resolution satellite image classification
Learn object-based high-resolution satellite image classification
Learn accuracy assessment in ENVI software
What You Will Learn?
- Unsupervised High-resolution satellite image classification.
- Supervised High-resolution satellite image classification.
- Pixel-based High-resolution satellite image classification.
- Object-based High-resolution satellite image classification.
- K-means and Isodata unsupervised algorithms.
- Maximum Likelihood, Minimum Distance, and Spectral Angle Mapper algorithms.
- Image classification using Artificial Neural Networks.
- Accuracy assessment in ENVI.
- Object-based feature extraction from high-resolution satellite imagery.
- Reference data generation in ENVI.