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Interesting Interval Discovery on Spatiotemporal Datasets

Study abrupt shifts in vegetation cover and climate patterns in Africa, focusing on spatiotemporal data analysis. Detect ecological transition zones vulnerable to climate change. Explore interesting interval patterns and high variation periods in datasets. Potential project ideas include implementing user-defined interest measures.

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Interesting Interval Discovery on Spatiotemporal Datasets

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  1. Interesting Interval Discovery on Spatiotemporal Datasets Csci 8715 Fall 2013

  2. Sub-path of Abrupt Change • Spatial sub-path of Abrupt Change[1] • Sharp change in vegetation cover • Transition between ecological zones (ecotones) • Vulnerable to climate change • Moves in response to climate change W1=[12N, 17N] The change is persistent and rapid A snapshot of vegetation cover in Africa [6]

  3. Sub-path of Abrupt Change • Temporal sub-path (interval) of Abrupt Change[1] • Abrupt shift in precipitation, temperature, etc. • Climate change detection. Raw Sahel precipitation anomaly (JJASO) Smoothed Sahel precipitation anomaly (JJASO)

  4. Case Study Output Data: NDVI by GIMMS, Africa, 1981 August. Resolution: 8km. Smoothed within 1x1 degree. Path: along each longitude (south  north) Interest measure: (Slope) Sameness degree ∆ : unit slope Thresholds:α= 20% percentile, SD ≥0.5 AVG{∆} AVG≥α{∆}

  5. Potential Project ideas • Explore other interest measures to find interesting interval patterns • High correlations time periods between two time series • High variation periods of time series • Implement an R software[2] package and enable user defined interest measure [1]. Xun Zhou, ShashiShekhar, Pradeep Mohan, Stefan Liess, and Peter K. Snyder. "Discovering interesting sub-paths in spatiotemporal datasets: A summary of results." In Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 44-53. ACM, 2011. [2]. The R project for statistical computing: http://www.r-project.org/

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