In this video you will see how to use contingency to quantifiy the quality of your training sets. in the end the first usage of the accuracy assessment tool is shown.
In this video you will see how to use contingency to quantify the quality of your training sets. in the end the first usage of the accuracy assessment tool is shown.
- Basics of Erdas Imagine: Import, Layer Info, Blend, Swipe, Layer Stack (Part 1)
- Basics of Erdas Imagine: Import, Layer Info, Blend, Swipe, Layer Stack (Part 2)
- Downloading Landsat Data and first steps (Layer Info, Layer Stack, Spectral Info) in Erdas Imagine
- Georeferencing using Erdas Imagine: image to image (part 1 of 2)
- Georeferencing using Erdas Imagine: image to image (part 2 of 2)
- Spectral characterization of objects (unsupervised classification part 1)
- k-means / ISODATA (unsupervised classification part 2)
- Unsupervised classification in Erdas Imagine (unsupervised classification part 3)
- Ways of evaluating an unsupervised classification (unsupervised classification part 4)
- Supervised classification using erdas imagine (part 1)
- Supervised classification using erdas imagine (part 2)
- Supervised classification using erdas imagine (part 3)
- Supervised classification using erdas imagine (part 4)
- Evaluating classification results (part 1)
- Evaluating classification results (part 2)
- Evaluating classification results (part 3)
- Analysis of digital elevation models and usage of conditional statements in Erdas Imagine
- DOS in Erdas Imagine
- Changedetection with Band Differencing and Band Rationing
- Calculating the NDVI with landsat data manually
Credit : Riccardo Klinger
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