Comparing directional maps


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Presented in AAG 2008. Boston

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  • Lea 92 used aspect associated with each pixel to determine the flow direction. “An aspect driven kinematic routing algorithm’”.
  • Previous studies have recoded aspect into 8/16 different directions so an error of +- 44, 22 degrees is acceptable. (Coops 2000) Visual interpretation of histograms was used to find the difference: X axis we have angles (difference) and on Y axis no of pixels having that difference. Skidmore ‘89 Spearman’s rank correlation coefficient is used to find the correlation between the two aspect maps. Skidmore ’89 Wind direction modeling, habitat suitability, site selection, hydrologic modeling Coarsening the resolution of the elevation grid results is more errors from the truth values of slope and aspect. (Chang – Tsai 1991) The resolution of the data is dependent upon purpose of the analysis
  • Queens case: The central pixel gets the direction of the steepest slope of eight neighboring pixels, Tarbonton 97 Rooks case: The central pixel gets the direction of the steepest slope of four neighboring pixels
  • The big slump in the aspect values between 30 to 60 m res is due to the fact that the values are off by just the neighboring pixels. When the pixel is coarsened the aspect value are more conformal.
  • Comparing directional maps

    1. 1. Rahul Rakshit PhD Candidate Clark University [email_address]
    2. 2. Major Points
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    6. 6. Location: Plum Island Ecosystems Long Term Ecological Research (LTER) site
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    8. 8. Queen’s Case Rooks' Case
    9. 9. ArcGIS Aspect Values (Degrees) Idrisi Aspect Values (Degrees) Scatterplot: Resolution 30 m
    10. 10. Issue in comparing directions Aspect is a circular variable All the Units are in Degrees 360 90 180 270 5 355 10 350
    11. 11. Fine Resolution Coarse Resolution Vector Addition: To coarsen the resolution Direction 0 270 90 225 Direction 37 Magnitude 5 Magnitude 6 2 7 2√2 2 North 6 2√2 5 resultant 37˚ 7
    12. 12. :90 00 :90 00
    13. 13. Coarse Resolution Aspect Maps After Vector Addition
    14. 14. Scatter Plots: X Axis ArcGIS – Y Axis Idrisi
    15. 15. Resolution (m) MAE (Degrees) Mean Absolute Error (MAE) Shows the average difference in direction Coarse Fine MAE is the weighted average of absolute errors
    16. 16. Major Points
    17. 17. <ul><li>For more information, please contact at : [email_address] </li></ul><ul><li>To tackle other types of variables, read the following from </li></ul><ul><ul><li>Pontius, Thontteh and Chen. 2006. Components of information for multiple resolution comparison between maps that share a real variable. Environmental and Ecological Statistics. </li></ul></ul><ul><ul><li>Pontius and Cheuk. 2006. A generalized cross-tabulation matrix to compare soft-classified maps at multiple resolutions. International Journal of Geographical Information Science. </li></ul></ul><ul><li>Rahul extends special thanks to: </li></ul><ul><li>Prof. Robert Gilmore Pontius Jr. for the concept and advice in every step of </li></ul><ul><li>this research. </li></ul>Acknowledgements and Plugs
    18. 18. Aspect ArcGIS (Radians) Aspect Idrisi (Radians) Cos (Aspect) Sin (Aspect) Cos (aspect) Sin (Aspect) Slope (ArcGIS) Slope * Sin Slope * Cos Aggregate to coarser resolution Vector Addition (ArcGIS) Slope (Idrisi) Slope * Sin Slope * Cos Aggregate to coarser resolution Vector Addition (Idrisi) Scatter Plots at Coarser Resolutions Study Area Mask Mean Absolute Error (MAE) Elevation Coarse Angle(ArcGIS) Coarse Angle(Idrisi) Coarse Angle Difference
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