B61C - 0739: ASSESSMENT OF LANDSCAPE FRAGMENTATION ...
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Fragmentation Index 0 10 20 30 40 50 60 70 80 90 100 31. Melbourne 26-Feb-01 48. Sydney 26-Nov-01 1 2 3 4 5 6 7 Percent Fragmentation (Index Level) Fragmentation Index B61C - 0739: ASSESSMENT OF LANDSCAPE FRAGMENTATION ASSOCIATED WITH URBAN CENTERS USING ASTER DATA 1,2 William L. Stefanov 1 2 Department of Geological Sciences, Center for Environmental Studies Arizona State University, Tempe, AZ 85287-6305 USA; [email protected] ABSTRACT The role of humans as an integral part of the environment and ecosystem processes has only recently been accepted into mainstream ecological thought. The realization that virtually all ecosystems on Earth have experienced some degree of human alteration or impact has highlighted the need to incorporate humans (and their environmental effects) into ecosystem models. A logical starting point for investigation of human ecosystem dynamics is examination of the land cover characteristics of large urban centers. Land cover and land use changes associated with urbanization are important drivers of local geological, hydrological, ecological, and climatic change. Quantification and monitoring of urban land cover/land use change is part of the primary mission of the ASTER instrument on board the NASA Terra satellite, and comprises the fundamental research objective of the Urban Environmental Monitoring (UEM) Program at Arizona State University. The UEM program seeks to acquire day/night, visible through thermal infrared data twice per year for 100 global urban centers (with an emphasis on semi-arid cities) over the nominal six-year life of the Terra mission. Data have been acquired for the majority of the target urban centers and are used to compare landscape fragmentation patterns on the basis of land cover classifications. Land cover classifications of urban centers are obtained using visible through mid-infrared reflectance and emittance spectra together with calculated vegetation index and spatial variance texture information (all derived from raw ASTER data). This information is combined within a classification matrix, using an expert system framework, to obtain final pixel classifications. Landscape fragmentation is calculated using a pixel per unit area metric for comparison between 55 urban centers with varying geographic and climatic settings including North America, South America, Europe, central and eastern Asia, and Australia. Temporal variations in land cover and landscape fragmentation are assessed for 9 urban centers (Albuquerque, New Mexico, USA; Baghdad, Iraq; Las Vegas, Nevada, USA; Lisbon, Portugal; Madrid, Spain; Riyadh, Saudi Arabia; San Francisco, California, USA; Tokyo, Japan; and Vancouver, Canada). These data provide a useful baseline for comparison of human-dominated ecosystem land cover and associated regional landscape fragmentation. Continued collection of ASTER data throughout the duration of the Terra mission will enable further investigation of urban 80 60 40 20 0 -20 -40 -60 -80 -150 -100 -50 0 50 100 150 1. Albuquerque 17-June-00 21. Johannesburg 16-Oct-00 41. Rangoon 16-Apr-01 2. Algiers 27-July-00 22. Kabul 10-Sept-01 42. Riyadh 26-July-00 3. Amman 1-May-01 23. Karachi 28-Oct-01 43. San Diego 10-May-00 4. Baghdad 18-Oct-00 24. Kuwait City 3-July-01 44. San Francisco 14-June-00 5. Baltimore 28-Apr-01 25. Las Vegas 17-Oct-00 45. Santiago 29-Jan-01 6. Bamako 11-March-01 26. Lima 4-Apr-01 46. Seattle 7-Feb-01 7. Bangkok 29-July-00 27. Lisbon 24-Oct-01 47. Singapore 2-June-01 8. Barcelona 3-July-01 28. London 12-Oct-01 48. Sydney 26-Nov-01 9. Berlin 2-Apr-01 29. Los Angeles 23-July-01 49. Tashkent 26-Sept-01 10. Buenos Aires 18-Nov-00 30. Madrid 12-Apr-01 50. Tehran 26-June-01 11. Cairo 10-May-00 31. Melbourne 26-Feb-01 51. Tianjin 20-Aug-00 12. Calcutta 29-March-00 32. Mexico City 9-Apr-01 52. Tokyo 4-June-01 13. Caracas 3-Sept-00 33. Miami 11-May-00 53. Tucson 26-May-01 14. Casablanca 10-Apr-01 34. Monterrey 4-Sept-00 54. Vancouver 9-Aug-01 15. Chicago 3-May-00 35. Moscow 4-May-01 55. Washington D.C. 28-Apr-01 16. Chongqing 31-July-00 36. New York 8-June-01 17. Dallas 19-Aug-00 37. Paris 23-May-01 18. Delhi 17-March-01 38. Phoenix 19-Sept-00 19. Houston 27-Oct-01 39. Puebla 4-July-00 20. Istanbul 16-June-00 40. Quito 2-Oct-01 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 METHODOLOGY INTRODUCTION AND OBJECTIVES The role of humans as integral components of ecosystems, both driving biogeophysical change and effected by these same changes, has only recently been accepted into mainstream ecological thought. The logical starting point to gain understanding of ecosystem processes in human-dominated systems is investigation of urban centers and their dynamics (Grimm et al. 2000). The Urban Environmental Monitoring (UEM; elwood.la.asu.edu/grsl/UEM/) project at Arizona State University seeks to investigate urban ecosystem processes by acquiring biseasonal, day/night data collected by NASA EOS sensors (primarily the Advanced Spaceborne Thermal Emission and Reflection Radiometer, or ASTER) for 100 urban centers during the projected six-year mission of the Terra satellite (Stefanov et al. 2001a). The current research assesses the degree of landscape fragmentation associated with 55 urban centers using land cover classifications as input to calculate Pixel Per Unit Area (PPU) index values. These index values are recast into percent area (for each ASTER scene) to allow comparison between urban centers located on all of the major continents. Figure 1. ASTER visible-near infrared (321 RGB) scene of the San Francisco metropolitan area acquired 14-June-00.Vegetation is red, urban areas are blue-green, and water is blue-black. Figure 2. NDVI (Normalized Difference Vegetation Index) data derived from the visible-near infrared ASTER data in Fig. 1. Brightness corresponds to vegetation abundance (bright = high, dark = low). Figure 3. Variance texture image for ASTER bands 321 (as RGB) calculated from Fig. 1. Pixel brightness corresponds to edge density (bright = high, dark = low). Urban areas appear bright due to high edge density resulting from buildings, streets, etc. Figure 4. Matrix used with classified NDVI, texture, and spectral information (for water) to produce land cover classifications for urban centers using a modification of the expert classification system of Stefanov et al. (2001b). Table 1. ASTER Specifications (Abrams, 2000) Wavelength region Band Bandwidth ( mm) Resolution (m/pixel) Visible to 1 0.52 – 0.60 15 near infrared 2 0.63 – 0.69 15 3 0.76 – 0.86 15 Shortwave 4 1.60 – 1.70 30 infrared 5 2.145 – 2.185 30 6 2.185 – 2.225 30 7 2.235 – 2.285 30 8 2.295 – 2.365 30 9 2.360 – 2.430 30 Mid- (thermal) 10 8.125 – 8.475 90 infrared 11 8.475 – 8.825 90 12 8.925 – 9.275 90 13 10.25 – 10.95 90 14 10.95 – 11.65 90 Unsupervised classification of NDVI and texture data into low, moderate, and high classes Figure 5. Land cover classification of the metropolitan San Francisco region. Figure 6. Landscape fragmentation is calculated using the Pixel Per Unit area (PPU) index of Frohn (1998). The index is (number of pixel classes per unit area)/1089, which corresponds to a unit area of 250 m x 250 m (equal to 1089 ASTER pixels). This unit area was selected as it is intermediate between the 2 typical scale of landscape modeling (1 km ) and the full resolution of ASTER visible to near infrared data (15 m/pixel). Full resolution data was not used in order to more clearly distinguish fragmentation associated with urban centers from small-scale surficial variations in undisturbed landscapes. Figure 7. Urban centers were selected for analysis based on their geographic location and availability of high-quality ASTER data (low cloud cover and the majority of the urban center captured). Numbers correspond to individual cities on the map (scene acquisition dates are also given). Red squares without an associated number are other city targets of the UEM project not included in the current work. CITY SITE LOCATIONS A B C D E F G Figure 8. Percent landscape fragmentation level by ASTER scene for urban centers. Fragmentation index values correspond to calculated values presented in Fig. 6; higher index values represent higher levels of landscape fragmentation per unit area. Urban centers are grouped according to location: A - North America; B - Middle East; C - South America; D - Europe; E - Asia/India; F - Africa; G - Australia. RESULTS AND DISCUSSION Percent Area Urban Centers Figure 9. Comparison of fragmentation levels for urban centers over approximately one year. In general, fragmentation levels are comparable for each individual city. Major differences in fragmentation levels are due to variation in ASTER scene coverage over the urban center (i.e. Vancouver). Table 2. Urban Centers with over 50% Area Fragmentation Indices 5 and Higher Region total n # of Cities % All Regions 55 37 67 North America 19 13 68 South American 5 3 60 Africa 5 4 80 Asia/India 8 6 75 Europe 8 7 87.5 Australia 2 1 50 Middle East 8 3 37.5 Results of the fragmentation analyses of 55 urban centers suggest that relatively intense landscape fragmentation (defined as fragmentation indices of 5 or higher per unit area) of the urban/exurban region is present in over half of the metropolitan areas examined (Fig. 8 and Table 2). European, African, and Asian/Indian urban centers exhibit the highest degrees of landscape fragmentation relative to other continental areas. This result reflects the high population densities in the selected cities, as the majority of cities in this grouping are “megacities”. The impact of large human populations, and associated landscape alteration, on ecosystem connectiveness is well illustrated and quantified by the current work. The results presented here are based solely on ASTER data. The high spectral and spatial resolution allows for increased classification accuracy (estimated at 75-80% overall) of both built and natural materials, however spatial and temporal coverage of the data is not uniform. This difficulty is illustrated for several cities in Fig. 9. Future work will involve the incorporation of other datasets (such as Landsat Thematic Mapper, Enhanced Thematic Mapper Plus, and Advanced Land Imager data, and astronaut photography) to create a more uniform temporal and spatial dataset for each city. Incorporation of additional ancillary geospatial data (i.e. land use, geologic, and vegetation maps; agricultural or water use data; and zoning information) for each city could be used to further refine the classification algorithm. REFERENCES Abrams, M., 2000. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data products for the high spatial resolution imager on NASA’s Terra Platform. International Journal of Remote Sensing 21: 847-859. Frohn, R.C., 1998. Remote Sensing for Landscape Ecology. Lewis Publishers, Boca Raton, FL, 99 p. Grimm, N.B., J.M. Grove, S.T.A. Pickett, and C.L. Redman, 2000. Integrated approaches to long-term studies of urban ecological systems. Bioscience 50: 571-584. Stefanov, W.L., P.R. Christensen, and M.S. Ramsey, 2001a. Remote sensing of urban ecology at regional and global scales: Results from the Central Arizona-Phoenix LTER site and ASTER Urban Environmental Monitoring program. In Remote Sensing of Urban Areas, ed. C. Jurgens. Regensburger Geographische Schriften 35: 313-321 (on supplemental CD ROM). Stefanov, W.L., M.S. Ramsey, and P.R. Christensen, 2001b. Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to arid urban centers. Remote Sensing of Environment 77: 173-185. ACKNOWLEDGEMENTS The author thanks Jayme Harris (ASU Department of Geological Sciences) for download and archiving of ASTER data, and Maik Netzband (ASU Center for Environmental Studies) for being an intellectual sounding board for the current work. This research was funded by NASA EOS-ASTER Team Member Investigation Grant NAS 5-31371 to P.R. Christensen (ASU Department of Geological Sciences). 0 10 20 30 40 50 60 70 80 90 100 3. Amman 1-May-01 4. Baghdad 18-Oct-00 22. Kabul 10-Sept-01 23. Karachi 28-Oct-01 24. Kuwait City 3-July-01 42. Riyadh 26-July-00 49. Tashkent 26-Sept-01 50. Tehran 26-June-01 0 10 20 30 40 50 60 70 80 90 100 10. Buenos Aires 18-Nov-00 13. Caracas 3-Sept-00 26. Lima 4-Apr-01 40. Quito 2-Oct-01 45. Santiago 29-Jan-01 0 10 20 30 40 50 60 70 80 90 100 8. Barcelona 3-July-01 9. Berlin 2-Apr-01 20. Istanbul 16-June-00 27. Lisbon 24-Oct-01 28. London 12-Oct-01 30. Madrid 12-Apr-01 35. Moscow 4-May-01 37. Paris 23-May-01 0 10 20 30 40 50 60 70 80 90 100 7. Bangkok 29-July-00 12. Calcutta 29-March-00 16. Chongqing 31-July-00 18. Delhi 17-March-01 41. Rangoon 16-Apr-01 47. Singapore 2-June-01 51. Tianjin 20-Aug-00 52. Tokyo 4-June-01 0 10 20 30 40 50 60 70 80 90 100 2. Algiers 27-July-00 6. Bamako 11-March-01 11. Cairo 10-May-00 14. Casablanca 10-Apr-01 21. Johannesburg 16-Oct-00 Low Texture Moderate Texture High Texture Low Vegetation Moderate Vegetation High Vegetation Bare Soil/Low Vegetation, Roadways Low Density Urban, Roadways, and Dry Washes High Density Urban Moderate Vegetation Moderate Density Urban Moderate Density Urban Moderate Density Urban High Vegetation High Vegetation 1 2 3 4 5 6 7 Albuquerque 17- June-00 Albuquerque 26- Apr-01 Baghdad 18-Oct- 00 Baghdad 15- June-01 Las Vegas 17- Oct-00 Las Vegas 23- June-01 Lisbon 2-Aug-00 Lisbon 24-Nov- 01 Madrid 6-Aug-00 Madrid 12-Apr-01 Riyadh 26-Aug- 00 Riyadh 3-July-01 San Francisco 14-June-00 San Francisco 23-Oct-01 Tokyo 26-Dec-00 Tokyo 4-June-01 Vancouver 22- Aug-00 Vancouver 9- Aug-01 0 20 40 60 80 100 0 10 20 30 40 50 60 70 80 90 100 1. Albuquerque 17-June-00 5. Baltimore 28-Apr-01 15. Chicago 3-May-00 17. Dallas 19-Aug-00 19. Houston 27-Oct-01 25. Las Vegas 17-Oct-00 29. Los Angeles 23-July-01 32. Mexico City 9-Apr-01 33. Miami 11-May-00 34. Monterrey 4-Sept-00 36. New York 8-June-01 38. Phoenix 19-Sept-00 39. Puebla 4-July-00 43. San Diego 10-May-00 44. San Francisco 14-June-00 46. Seattle 7-Feb-01 53. Tucson 26-May-01 54. Vancouver 9-Aug-01 55. Washington D.C. 28-Apr-01
Transcript of B61C - 0739: ASSESSMENT OF LANDSCAPE FRAGMENTATION ...
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B61C - 0739: ASSESSMENT OF LANDSCAPE FRAGMENTATION ASSOCIATED WITH URBAN CENTERS USING ASTER DATA 1,2 William L. Stefanov
1 2Department of Geological Sciences, Center for Environmental StudiesArizona State University, Tempe, AZ 85287-6305 USA; [email protected]
ABSTRACT
The role of humans as an integral part of the environment and ecosystem processes has only recently been accepted into mainstream ecological thought. The realization that virtually all ecosystems on Earth have experienced some degree of human alteration or impact has highlighted the need to incorporate humans (and their environmental effects) into ecosystem models. A logical starting point for investigation of human ecosystem dynamics is examination of the land cover characteristics of large urban centers. Land cover and land use changes associated with urbanization are important drivers of local geological, hydrological, ecological, and climatic change. Quantification and monitoring of urban land cover/land use change is part of the primary mission of the ASTER instrument on board the NASA Terra satellite, and comprises the fundamental research objective of the Urban Environmental Monitoring (UEM) Program at Arizona State University. The UEM program seeks to acquire day/night, visible through thermal infrared data twice per year for 100 global urban centers (with an emphasis on semi-arid cities) over the nominal six-year life of the Terra mission. Data have been acquired for the majority of the target urban centers and are used to compare landscape fragmentation patterns on the basis of land cover classifications. Land cover classifications of urban centers are obtained using visible through mid-infrared reflectance and emittance spectra together with calculated vegetation index and spatial variance texture information (all derived from raw ASTER data). This information is combined within a classification matrix, using an expert system framework, to obtain final pixel classifications. Landscape fragmentation is calculated using a pixel per unit area metric for comparison between 55 urban centers with varying geographic and climatic settings including North America, South America, Europe, central and eastern Asia, and Australia. Temporal variations in land cover and landscape fragmentation are assessed for 9 urban centers (Albuquerque, New Mexico, USA; Baghdad, Iraq; Las Vegas, Nevada, USA; Lisbon, Portugal; Madrid, Spain; Riyadh, Saudi Arabia; San Francisco, California, USA; Tokyo, Japan; and Vancouver, Canada). These data provide a useful baseline for comparison of human-dominated ecosystem land cover and associated regional landscape fragmentation. Continued collection of ASTER data throughout the duration of the Terra mission will enable further investigation of urban
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1. Albuquerque 17-June-00 21. Johannesburg 16-Oct-00 41. Rangoon 16-Apr-012. Algiers 27-July-00 22. Kabul 10-Sept-01 42. Riyadh 26-July-003. Amman 1-May-01 23. Karachi 28-Oct-01 43. San Diego 10-May-004. Baghdad 18-Oct-00 24. Kuwait City 3-July-01 44. San Francisco 14-June-005. Baltimore 28-Apr-01 25. Las Vegas 17-Oct-00 45. Santiago 29-Jan-016. Bamako 11-March-01 26. Lima 4-Apr-01 46. Seattle 7-Feb-017. Bangkok 29-July-00 27. Lisbon 24-Oct-01 47. Singapore 2-June-018. Barcelona 3-July-01 28. London 12-Oct-01 48. Sydney 26-Nov-019. Berlin 2-Apr-01 29. Los Angeles 23-July-01 49. Tashkent 26-Sept-0110. Buenos Aires 18-Nov-00 30. Madrid 12-Apr-01 50. Tehran 26-June-0111. Cairo 10-May-00 31. Melbourne 26-Feb-01 51. Tianjin 20-Aug-0012. Calcutta 29-March-00 32. Mexico City 9-Apr-01 52. Tokyo 4-June-0113. Caracas 3-Sept-00 33. Miami 11-May-00 53. Tucson 26-May-0114. Casablanca 10-Apr-01 34. Monterrey 4-Sept-00 54. Vancouver 9-Aug-0115. Chicago 3-May-00 35. Moscow 4-May-01 55. Washington D.C. 28-Apr-0116. Chongqing 31-July-00 36. New York 8-June-0117. Dallas 19-Aug-00 37. Paris 23-May-0118. Delhi 17-March-01 38. Phoenix 19-Sept-0019. Houston 27-Oct-01 39. Puebla 4-July-0020. Istanbul 16-June-00 40. Quito 2-Oct-01
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METHODOLOGY
INTRODUCTION AND OBJECTIVESThe role of humans as integral components of ecosystems, both driving biogeophysical change and effected by thesesame changes, has only recently been accepted into mainstream ecological thought. The logical starting point to gainunderstanding of ecosystem processes in human-dominated systems is investigation of urban centers and theirdynamics (Grimm et al. 2000).
The Urban Environmental Monitoring (UEM; elwood.la.asu.edu/grsl/UEM/) project at Arizona State University seeksto investigate urban ecosystem processes by acquiring biseasonal, day/night data collected by NASA EOS sensors(primarily the Advanced Spaceborne Thermal Emission and Reflection Radiometer, or ASTER) for 100 urban centersduring the projected six-year mission of the Terra satellite (Stefanov et al. 2001a).
The current research assesses the degree of landscape fragmentation associated with 55 urban centers using land coverclassifications as input to calculate Pixel Per Unit Area (PPU) index values. These index values are recast into percentarea (for each ASTER scene) to allow comparison between urban centers located on all of the major continents.
Figure 1. ASTER visible-near infrared (321 RGB) scene of the San Franciscometropolitan area acquired 14-June-00.Vegetation is red, urban areas areblue-green, and water is blue-black.
Figure 2. NDVI (Normalized Difference Vegetation Index) data derivedfrom the visible-near infrared ASTER data in Fig. 1. Brightness correspondsto vegetation abundance (bright = high, dark = low).
Figure 3. Variance texture image for ASTER bands 321 (as RGB) calculatedfrom Fig. 1. Pixel brightness corresponds to edge density (bright = high, dark = low).Urban areas appear bright due to high edge density resulting from buildings, streets, etc.
Figure 4. Matrix used with classified NDVI, texture, and spectralinformation (for water) to produce land cover classifications for urban centers using a modification of the expert classification system of Stefanov et al. (2001b).
Table 1. ASTER Specifications (Abrams, 2000) Wavelength region Band Bandwidth (mm) Resolution (m/pixel)
Visible to 1 0.52 – 0.60 15
near infrared 2 0.63 – 0.69 15 3 0.76 – 0.86 15
Shortwave 4 1.60 – 1.70 30 infrared 5 2.145 – 2.185 30
6 2.185 – 2.225 30 7 2.235 – 2.285 30 8 2.295 – 2.365 30 9 2.360 – 2.430 30
Mid- (thermal) 10 8.125 – 8.475 90 infrared 11 8.475 – 8.825 90
12 8.925 – 9.275 90 13 10.25 – 10.95 90 14 10.95 – 11.65 90
Unsupervised classificationof NDVI and texture data intolow, moderate, and high classes
Figure 5. Land cover classification of the metropolitan San Francisco region.
Figure 6. Landscape fragmentation is calculated using thePixel Per Unit area (PPU) index of Frohn (1998). The index is(number of pixel classes per unit area)/1089, which correspondsto a unit area of 250 m x 250 m (equal to 1089 ASTER pixels).This unit area was selected as it is intermediate between the
2typical scale of landscape modeling (1 km ) and the fullresolution of ASTER visible to near infrared data (15 m/pixel).Full resolution data was not used in order to more clearly distinguish fragmentation associated with urban centers fromsmall-scale surficial variations in undisturbed landscapes.
Figure 7. Urban centers were selected for analysis based on their geographiclocation and availability of high-quality ASTER data (low cloud cover andthe majority of the urban center captured). Numbers correspond to individualcities on the map (scene acquisition dates are also given). Red squareswithout an associated number are other city targets of the UEM project notincluded in the current work.
CITY SITE LOCATIONS
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Figure 8. Percent landscape fragmentation level by ASTER scene for urban centers.Fragmentation index values correspond to calculated values presented in Fig. 6;higher index values represent higher levels of landscape fragmentation per unitarea. Urban centers are grouped according to location: A - North America; B - MiddleEast; C - South America; D - Europe; E - Asia/India; F - Africa; G - Australia.
RESULTS AND DISCUSSION
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Figure 9. Comparison of fragmentation levels for urban centers over approximately oneyear. In general, fragmentation levels are comparable for each individual city. Major differencesin fragmentation levels are due to variation in ASTER scene coverage over the urban center (i.e.Vancouver).
Table 2. Urban Centers with over 50% Area Fragmentation Indices 5 and Higher
Region total n # of Cities %
All Regions 55 37 67 North America 19 13 68
South American 5 3 60 Africa 5 4 80
Asia/India 8 6 75 Europe 8 7 87.5
Australia 2 1 50 Middle East 8 3 37.5
Results of the fragmentation analyses of 55 urban centers suggest thatrelatively intense landscape fragmentation (defined as fragmentationindices of 5 or higher per unit area) of the urban/exurban region is present in over half of the metropolitan areas examined (Fig. 8 and Table 2).
European, African, and Asian/Indian urban centers exhibit the highestdegrees of landscape fragmentation relative to other continental areas.This result reflects the high population densities in the selected cities, asthe majority of cities in this grouping are “megacities”. The impact of largehuman populations, and associated landscape alteration, on ecosystemconnectiveness is well illustrated and quantified by the current work.
The results presented here are based solely on ASTER data. The highspectral and spatial resolution allows for increased classification accuracy(estimated at 75-80% overall) of both built and natural materials, howeverspatial and temporal coverage of the data is not uniform. This difficulty isillustrated for several cities in Fig. 9. Future work will involve theincorporation of other datasets (such as Landsat Thematic Mapper,Enhanced Thematic Mapper Plus, and Advanced Land Imager data, andastronaut photography) to create a more uniform temporal and spatialdataset for each city.
Incorporation of additional ancillary geospatial data (i.e. land use,geologic, and vegetation maps; agricultural or water use data; and zoninginformation) for each city could be used to further refine the classificationalgorithm.
REFERENCES
Abrams, M., 2000. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER):Data products for the high spatial resolution imager on NASA’s Terra Platform. International Journal ofRemote Sensing 21: 847-859.
Frohn, R.C., 1998. Remote Sensing for Landscape Ecology. Lewis Publishers, Boca Raton, FL, 99 p.
Grimm, N.B., J.M. Grove, S.T.A. Pickett, and C.L. Redman, 2000. Integrated approaches to long-termstudies of urban ecological systems. Bioscience 50: 571-584.
Stefanov, W.L., P.R. Christensen, and M.S. Ramsey, 2001a. Remote sensing of urban ecology atregional and global scales: Results from the Central Arizona-Phoenix LTER site and ASTERUrban Environmental Monitoring program. In Remote Sensing of Urban Areas, ed. C. Jurgens.Regensburger Geographische Schriften 35: 313-321 (on supplemental CD ROM).
Stefanov, W.L., M.S. Ramsey, and P.R. Christensen, 2001b. Monitoring urban land cover change:An expert system approach to land cover classification of semiarid to arid urban centers.Remote Sensing of Environment 77: 173-185.
ACKNOWLEDGEMENTS
The author thanks Jayme Harris (ASU Department of Geological Sciences) for download and archiving of ASTER data, and Maik Netzband (ASUCenter for Environmental Studies) for being an intellectual sounding board for the current work. This research was funded by NASA EOS-ASTERTeam Member Investigation Grant NAS 5-31371 to P.R. Christensen (ASU Department of Geological Sciences).
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