1. Discussion: Urban terrain segmentation for the Marmara Region Speaker: Akarun Discussant: Lerner-Lam

2. Classic Geophysical Inverse Problem Forward Problem: Image = F { Classifications [segments] } Segments = geographic basis functions, change with time. Useful for hypothesis testing and examining prior assumptions about geographic variation.

3. Inverse Problem l Classifications [segments] = F -1 {Image} l F -1 = F † l Inverse = generalized inverse (approximate) l Treated by Stochastic Techniques and l Genetic or Evolutionary Algorithms, AI (training), matched filtering, wavelets, empirical orthogonal eigenfunctions analysis, etc.

4. Basic Issues l Uniqueness of derived classifications. Do different combinations of classifications fit the data equally well? l Error model, including covariance. Uncertainties as input to further calculations. l Resolving power of data. –Geographical resolution (function of instrument) –Ability to distinguish between classifications l Optimizing a penalty function, including prior knowledge

5. Other issues l Proxy set –What needs to be quantified? l Relate to multidisciplinary needs –What is measurable/detectable? l Collateral data sets l Groundtruth: minimum (necessary and sufficient) tests l Baselining: time dimension l Background and causal changes –Global experience database –EOF ( t): time variation of geographic basis functions