1. U C S B GEOGRAPHY 8/6/2001NCRST Building A Global Road Database? Possibilities and Techniques for Mapping Rural Roads Chris Funk

2. U C S B GEOGRAPHY 8/6/2001NCRST Rondonia – Matched Filter

3. U C S B GEOGRAPHY 8/6/2001NCRST Overview Motivation –Q: Why build a Global Database of Roads? –A: There is only one world ‘Nature’ <> ‘Society’ (ecologos) <> (economos) Developed <> undeveloped –Roads link societies to nature –communities to the global economy What defines utility –Consistent, Accurate, Available, Repeatable (CAAR) –Examples of Global Databases: DCW, ETOPO30 Global Road Database –sources of information –Algorithms Matched Filter Multi-spectral Analysis Texture Analysis

4. U C S B GEOGRAPHY 8/6/2001NCRST Human Impacts: Fire in Africa Roads increase probability of burns

5. U C S B GEOGRAPHY 8/6/2001NCRST Human Impacts: DMSP Fires in Indonesia Fires influenced by ENSO and Global Warming Climate influenced by CO2 emissions

6. U C S B GEOGRAPHY 8/6/2001NCRST Roads and Deforestation in the Amazon Rondonia 1975 Rondonia 1992 Source – USGS Earthshots

7. U C S B GEOGRAPHY 8/6/2001NCRST GRD Application – Disaster Mitigation Case Study: Flooding in Mozambique Context: in Winter of 2000 tropical cyclones brought massive flooding to Southern Africa Largest single threat was lack of access to good drinking water Improved knowledge of roads would have aided relief efforts Images www.disasterrelief.org Taken at Relief Station at Gode

8. U C S B GEOGRAPHY 8/6/2001NCRST Uncertain Human Futures Increasing populations strain food production Increasing temperature strain tropical climates

9. U C S B GEOGRAPHY 8/6/2001NCRST Solution? Improve current knowledge by harnessing the power of geographic science Improved knowledge increases the quality of response Data Knowledge Wisdom Action RS GIS.txt Policy

10. U C S B GEOGRAPHY 8/6/2001NCRST Utility Definition Consistency Accuracy Availability Repeatability

11. U C S B GEOGRAPHY 8/6/2001NCRST Geographic Science Provides Utility Spectral Libraries and Spectral Analysis methods are tied to invariant physical properties of stuff Remote Sensing techniques can be applied uniformly across space Remote Sensing techniques can be applied uniformly across time

12. U C S B GEOGRAPHY 8/6/2001NCRST Example of a High Utility ‘Physical’ Dataset USGS ETOPO30 –30 m Digital Elevations –Global Coverage –Universally Available –Many derived products Surface topology Stream networks

13. U C S B GEOGRAPHY 8/6/2001NCRST Example of a High Utility Dataset Digital Chart of the World 1:1,000,000 global data Created by ESRI Repeatable?

14. U C S B GEOGRAPHY 8/6/2001NCRST GRD Potential Data Sources Spectral Bands Spatial [m 2 ] 10 0 10 1 10 2 10 3 10 0 10 1 10 2 10 3 IKONOS TM AVHRR AVIRIS Inexpensive Widely Available

15. U C S B GEOGRAPHY 8/6/2001NCRST GRD – Potential Algorithms Matched Filtering –Sub-pixel detection strategy –Applicable where spectral signal is distinct, but weak Spectral Mixture Analysis –Breaks pixel into sub-components –Useful when road has strong soil component –Roads can also appear as high error pixels Texture Analysis –Use spatial information to isolate road pixels –Applicable in situations where no systematic difference in road material exists

16. U C S B GEOGRAPHY 8/6/2001NCRST Matched Filtering-I Rotate Data Cloud To Maximize Signal

17. U C S B GEOGRAPHY 8/6/2001NCRST Clustered Matched Filtering-II

18. U C S B GEOGRAPHY 8/6/2001NCRST MF example TM Rondonia 1998 – Bands 345

19. U C S B GEOGRAPHY 8/6/2001NCRST Rondonia Example – Bands 123

20. U C S B GEOGRAPHY 8/6/2001NCRST Rondonia – Matched Filter

21. U C S B GEOGRAPHY 8/6/2001NCRST Rondonia – Hi Pass – Band 1 8

22. U C S B GEOGRAPHY 8/6/2001NCRST Rondonia – 1998 – Local Range

23. U C S B GEOGRAPHY 8/6/2001NCRST Rondonia 1996 SMA Error

24. U C S B GEOGRAPHY 8/6/2001NCRST Summary Extraction of Rural Roads from TM imagery seems practical and plausible Library-based spectral techniques perform well We can and should build a global road database: –Based on TM imagery –100% coverage –‘easily’ updatable –freely available Future directions –Improved spectral libraries –Santa Barbara Testbed – algorithm evaluation –Application/testing of rural road extraction techniques in US and Brazil