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Lesson Navigation IconOverview of sources and methods

Unit Navigation IconTypes of source materials

Unit Navigation IconQuality and Coverage of Data Sources

LO Navigation IconKey Issues Involving Data Sources

LO Navigation IconQuestions

LO Navigation IconSubmit your answer

Unit Navigation IconBibliography

Unit Navigation IconMetadata


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Key Issues Involving Data Sources

1. GIS Datasources

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2. Positional Accuracy

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The following animation calculates the acceptable error and allowable RMS based on scale. Klick on the picture to calculate

Click on the image to do the Calculation of Acceptable Error and Allowable RMSClick on the image to do the Calculation of Acceptable Error and Allowable RMS

3. Attribute Accuracy

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Interactively calculate the Kappa using the following animation.
The animation filled with random numbers for each pair of land use classes represented as (A, B, C, D, E) from reference data and map data. Then calculate the row and column total of the matrix. Then calculate the Kappa value. .

Attribute accuracy calculation can be used to test the accuracy of a classified map from remotely sensed data or to validate the attribute accuracy of an existing map with field data or data from a map of higher accuracy.

Click on the image to do the Kappa CalculationClick on the image to do the Kappa Calculation

3. Other Key Issues

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Practical Session

act

1. Fill the appropriate value on the empty raster grid based on the landuse value. Write down your rule on why you fill a particular value to a particular cell. Write down your suggestions to improve the quality in order to maintain the values of the original map as much as possible.

Animation for manual rasterization.

Click on the imageClick on the image

2. Calculate the Kappa Value based on the following table.

Landuse A B C D E F
A 8 0 1 0 2 0
B 0 10 0 2 0 1
C 3 0 21 0 4 0
D 0 0 0 9 0 3
E 4 0 5 0 23 0
F 0 2 0 3 0 14
  • A = Mixed forest
  • B = Paddy
  • C = Plantation
  • D = Corn
  • E = Pine
  • F = Sugarcane
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