An Autocorrelation Analysis Approach to Detecting Land Cover Change using Hyper-Temporal Time-Series Data.pdf

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  • 1. An Autocorrelation Analysis Approach to Detecting Land Cover Change using Hyper-Temporal Time-Series DataW. Kleynhans 1,2 B.P. Salmon 1,2 J.C. Olivier 1 K.J. Wessels 2 F. van den Bergh 2 1 Electrical and Electronic Engineering, University of Pretoria, South Africa2 Remote Sensing Research Unit, Meraka Institute, CSIR, Pretoria, South Africa July 25, 2011
  • 2. Outline Introduction Study Area Methodology Results Conclusion Exampleswww.csir.co.za
  • 3. Introduction Remote sensing satellite data - effective way to monitor and evaluate land cover changes Bi-temporal change detection approach is not always appropriate. The temporal frequency should be high enough to distinguish change events from natural phenological cycles. Having a series of equally sampled acquisitions opens the door for the utilization basic signal processing methods. Temporal autocorrelation was effectively used as an input feature for a change detection alarm.www.csir.co.za
  • 4. Problem statement Settlement expansion is the most pervasive form of land cover change in South Africa. Objective is to develop a change alarm that is able to detect the formation of new settlement developments. These changes typically occur in areas that are naturally vegetated. Change events should be distinguished from natural phenological cycles.www.csir.co.za
  • 5. Outline Introduction Study Area Methodology Results Conclusion Exampleswww.csir.co.za
  • 6. Study Area The Gauteng province is located in northern South Africa and covers a total area of approximately 17000 km2 592 natural vegetation and 372 settlement no-change MODIS pixels were identified. 181 change MODIS pixels were identified. Each pixel has a 7 year time-series (8 day composited: 2001-2007).www.csir.co.za
  • 7. Change example: Quickbird image in 2002www.csir.co.za
  • 8. Change example: Quickbird image in 2007www.csir.co.za
  • 9. Hyper temporal MODIS band 4 Time Series : No changewww.csir.co.za
  • 10. Hyper temporal MODIS band 4 Time Series : Changewww.csir.co.za
  • 11. Outline Introduction Study Area Methodology Results Conclusion Exampleswww.csir.co.za
  • 12. Temporal ACF method Assume time series in vector form: X = Xn , n ∈ {1, 2, ..., N} (1) The normalized ACF for time-series X: E [(Xn − mean(X))(Xn+τ − mean(X))] RXX (τ ) = (2) var(X) Stationarity assumption: mean(X) and var(X) should be constant! Reflection time-series from nature very rarely adhere to this assumption but some do more than others...www.csir.co.za
  • 13. Temporal ACF methodwww.csir.co.za
  • 14. Change metric formulationwww.csir.co.za
  • 15. Use of simulated change to determine detection parameters Time-series of no change areas are relatively easy to obtain but examples of real change is much more difficult. Solution: Obtain only examples of no-change time-series and simulate the change time-series using time-series blending. Using simulated change the start and rate of change can be controlled. Start of change date was random using a uniform distribution Duration of change was varied between 6 and 24 months. Using a no-change and simulated change dataset, the optimal band lag and threshold is determined (“off-line” optimization phase)www.csir.co.za
  • 16. Use of simulated change to determine detection parameters 0.9 Band 1 0.85 Band 2 Band 3 0.8 Band 4 Band 5 0.75 Band 6 Band 7 NDVI A 0.7 O 0.65 0.6 0.55 0.5 40 80 120 160 200 240 280 320 360 Time Lag (Days)www.csir.co.za
  • 17. Opperational phase A pixel is labeled as having changed by evaluating the following, true if R b (τ ) ≥ δτ b∗ Change = false if R b (τ ) < δτ , b∗www.csir.co.za
  • 18. Outline Introduction Study Area Methodology Results Conclusion Exampleswww.csir.co.za
  • 19. Results using simulated change Confusion Matrix, overall accuracy (OA ) and optimal threshold (δ ∗ ) showing the best land cover change detection performance during the off-line optimization phase using MODIS band 4 550 nm with a lag of 96 days Simulated No Change δ∗ OA change (n=482) (n=592) Change Detected 75.17% 14.73% 0.16 80.22% No Change Detected 24.83% 85.27%www.csir.co.za
  • 20. Results using real change Confusion Matrix, overall accuracy (OA ) and threshold (δ) for the case of real change detection using the MODIS band 4 (550 nm) with a lag of 96 days as determined during the off-line optimization phase Real change No Change δ OA (n=181) (n=482) Change Detected 92.27% 15.35% 0.16 88.46% No Change Detected 7.73% 84.65%www.csir.co.za
  • 21. Results : Timing of the change Mean start of change OA 2001/06 70.67% 2002/06 83.57% 2003/06 85.33% 2004/06 85.43% 2005/06 84.92% 2006/06 81.74% 2007/06 76.66%www.csir.co.za
  • 22. Outline Introduction Study Area Methodology Results Conclusion Exampleswww.csir.co.za
  • 23. Concluding remarks A change metric can be formulated by selecting the lag that shows the highest separability between the ACF of no-change and simulated change time-series examples. The optimal band lag and threshold selection is determined in an “off-line” optimization phase. After the detection parameters are determined, the method was run blindly over the study area. The method shows a slight decrease in performance if the start of change is in the first or last year.www.csir.co.za
  • 24. Outline Introduction Study Area Methodology Results Conclusion Exampleswww.csir.co.za
  • 25. Example 1 - Beforewww.csir.co.za
  • 26. Example 1 - Afterwww.csir.co.za
  • 27. Example 2 - Beforewww.csir.co.za
  • 28. Example 2 - Afterwww.csir.co.za
  • 29. Example 3 - Beforewww.csir.co.za
  • 30. Example 3 - Afterwww.csir.co.za
  • 31. Example 4 - Beforewww.csir.co.za
  • 32. Example 4 - Afterwww.csir.co.za
  • 33. Example 5 - Beforewww.csir.co.za
  • 34. Example 5 - Afterwww.csir.co.za
  • 35. Example 6 - Feb 2005www.csir.co.za
  • 36. Example 6 - May 2006www.csir.co.za
  • 37. Example 6 - Sep 2006www.csir.co.za
  • 38. Example 6 - May 2007www.csir.co.za
  • 39. Example 7 - Apr 2002www.csir.co.za
  • 40. Example 7 - Mar 2004www.csir.co.za
  • 41. Example 7 - Apr 2005www.csir.co.za
  • 42. Example 7 - May 2005www.csir.co.za