Third International Workshop on "Geographical Analysis, Urban Modeling, Spatial Statistics"

1. Detecting alluvial fans using quantitative roughness characterization and fuzzy logic analysis Andrea Taramelli [email_address] Third International Workshop on "Geographical Analysis,Urban Modeling, Spatial Statistics" GEOG-AN-MOD 08 The 2008 International Conference on Computational Science and its Applications (ICCSA 2008) June 30th to July 3rd, 2008 Laura Melelli Lamont-Doherty Earth Observatory – Columbia University, New York, USA ICRAM - Marine Sciences Research Institute , Rome Uniersità degli Studi di Perugia – Earth Science Department

3. The Study area 1 st case Perugia Gubbio basin Valle Umbra basin

4. Beijing The Study area 2 nd case The Alashan area

12. Landform Delineation Algorithm: Populating the Similarity Model P i is Maximum likelihood probability of attribution to the class. n Number of measurement variables. Ci Covariance matrix of the class considered. Mi Mean vector of the class considered. X Pixel vector. Pr i Prior probability of the class considered defined from the frequency histograms of the training sets. Fr is the pixel count of the class under examination. Frt Is the sum of counts of all the classes.

14. Cluster results 2.5 D and 2D for the Gubbio intermontane basin - an initial negative value of curvature (-6°) represents the upper fan-head trenching because of the linear channel erosion typical of the alluvial fans in our study area due to the recent regional tectonic uplift and the consequent readjustment of the drainage network; - a second positive value of curvature (8°) corresponds to upper and medium parts of the fan where the gravel deposits are present and show a convex longitudinal profile. - a last value (-0.5°) represents the area of the lower fan where lime and clay deposits lay adjacent to flat alluvial sediments.

15. Radar Backscatter (Feb. 2000) The retrieved roughness thresholds range from – 5 in the sandy deserts (Taklimakan, Badain Jaran, and Tengger Deserts) to up to 2 in the Gobi desert.

16. SRTM Analysis: Landform Delineation Algorithm The Alashan area