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Articles

Phenology-based temporal mixture analysis for estimating large-scale impervious surface distributions

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Pages 779-795 | Received 10 May 2013, Accepted 14 Nov 2013, Published online: 20 Jan 2014

References

  • Arnold, C. L., and C. J. Gibbons. 1996. “Impervious Surface Coverage – The Emergence of a Key Environmental Indicator.” Journal of the American Planning Association 62 (2): 243–258. doi:10.1080/01944369608975688.
  • Bauer, M. E., J. J. Heinert, J. K. Doyle, and F. Yuan. 2004. “Impervious Surface Mapping and Change Monitoring Using Landsat Remote Sensing.” Paper presented at the ASPRS Annual Conference Proceedings, Denver, CO, May 23–28.
  • Demarchi, L., F. Canters, J. C. Chan, and T. Van de Voorde. 2012. “Multiple Endmember Unmixing of CHRIS/Proba Imagery for Mapping Impervious Surfaces in Urban and Suburban Environments.” IEEE Transactions on Geoscience and Remote Sensing 50 (9): 3409–3424. doi:10.1109/tgrs.2011.2181853.
  • Elvidge, C. D., B. T. Tuttle, P. S. Sutton, K. E. Baugh, A. T. Howard, C. Milesi, B. L. Bhaduri, and R. Nemani. 2007. “Global Distribution and Density of Constructed Impervious Surfaces.” Sensors 7 (9): 1962–1979. doi:10.3390/s7091962.
  • Foody, G. M., and D. P. Cox. 1994. “Sub-Pixel Land-Cover Composition Estimation Using a Linear Mixture Model and Fuzzy Membership Functions.” International Journal of Remote Sensing 15 (3): 619–631.
  • Franke, J., D. A. Roberts, K. Halligan, and G. Menz. 2009. “Hierarchical Multiple Endmember Spectral Mixture Analysis (MESMA) of Hyperspectral Imagery for Urban Environments.” Remote Sensing of Environment 113 (8): 1712–1723. doi:10.1016/j.rse.2009.03.018.
  • Fry, J. A., G. Xian, S. Jin, J. A. Dewitz, C. G. Homer, L. Yang, C. A. Barnes, N. D. Herold, and J. D. Wickham. 2012. “Completion of the 2006 National Land Cover Database Update for the Conterminous United States.” Photogrammetric Engineering and Remote Sensing 77: 858–864.
  • Goodwin, N., N. C. Coops, and C. Stone. 2005. “Assessing Plantation Canopy Condition from Airborne Imagery Using Spectral Mixture Analysis and Fractional Abundances.” International Journal of Applied Earth Observation and Geoinformation 7 (1): 11–28. doi:http://dx.doi.org/10.1016/j.jag.2004.10.003
  • Green, A. A., M. Berman, P. Switzer, and M. D. Craig. 1988. “A Transformation for Ordering Multispectral Data in Terms of Image Quality with Implications for Noise Removal.” IEEE Transactions on Geoscience and Remote Sensing 26 (1): 65–74. doi:10.1109/36.3001.
  • Grubler, A. 1994. “Technology and Global Change: Land-Use, Past and Present” In Changes in Land Use and Land Cover: A Global Perspective, edited by W. B. Merye, and B. L. Turner London: Cambridge University Press.
  • Guttikunda, S. K., G. R. Carmichael, G. Calori, C. Eck, and J. H. Woo. 2003. “The Contribution of Megacities to Regional Sulfur Pollution in Asia.” Atmospheric Environment 37 (1): 11–22. doi:10.1016/s1352-2310(02)00821-x.
  • Huang, C., and J. R. G. Townshend. 2003. “A Stepwise Regression Tree for Nonlinear Approximation: Applications to Estimating Subpixel Land Cover.” International Journal of Remote Sensing 24 (1): 75–90. doi:10.1080/01431160110115032.
  • Jantz, C. A., S. J. Goetz, and M. K. Shelley. 2004. “Using the SLEUTH Urban Growth Model to Simulate the Impacts of Future Policy Scenarios on Urban Land Use in the Baltimore – Washington Metropolitan Area.” Environment and Planning B: Planning and Design 31 (2): 251–271.
  • Knight, J., and M. Voth. 2011. “Mapping Impervious Cover Using Multi-Temporal MODIS NDVI Data.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 4 (2): 303–309. doi:10.1109/jstars.2010.2051535.
  • Lee, S., and R. G. Lathrop. 2006. “Subpixel Analysis of Landsat ETM+ Using Self-Organizing Map (SOM) Neural Networks for Urban Land Cover Characterization.” IEEE Transactions on Geoscience and Remote Sensing 44 (6): 1642–1654. doi:10.1109/tgrs.2006.869984.
  • Lin, G. C. S., and S. P. S. Ho. 2003. “China’s Land Resources and Land-Use Change: Insights from the 1996 Land Survey.” Land Use Policy 20 (2): 87–107. doi:10.1016/s0264-8377(03)00007-3.
  • Lu, D., and Q. Weng. 2004. “Spectral Mixture Analysis of the Urban Landscape in Indianapolis with Landsat ETM Plus Imagery.” Photogrammetric Engineering and Remote Sensing 70 (9): 1053–1062.
  • Lu, D., and Q. Weng. 2006. “Use of Impervious Surface in Urban Land-Use Classification.” Remote Sensing of Environment 102 (1–2): 146–160. doi:10.1016/j.rse.2006.02.010.
  • Madhavan, B. B., S. Kubo, N. Kurisaki, and T. Sivakumar. 2001. “Appraising the Anatomy and Spatial Growth of the Bangkok Metropolitan Area Using a Vegetation-Impervious-Soil Model Through Remote Sensing.” International Journal of Remote Sensing 22 (5): 789–806. doi:10.1080/01431160051060200.
  • Newman, P., and J. R. Kenworthy. 1999. Sustainability and Cities: Overcoming Automobile Dependence. Washington, DC: Island Press.
  • Pauleit, S., and F. Duhme. 2000. “Assessing the Environmental Performance of Land Cover Types for Urban Planning.” Landscape and Urban Planning 52 (1): 1–20. doi:10.1016/s0169-2046(00)00109-2.
  • Phinn, S., M. Stanford, P. Scarth, A. T. Murray, and P. T. Shyy. 2002. “Monitoring the Composition of Urban Environments Based on the Vegetation-Impervious Surface-Soil (VIS) Model by Subpixel Analysis Techniques.” International Journal of Remote Sensing 23 (20): 4131–4153. doi:10.1080/01431160110114998.
  • Pielke, R. A. 2005. “Land Use and Climate Change.” Science 310 (5754): 1625–1626. doi:10.1126/science.1120529.
  • Powell, R. L., D. A. Roberts, P. E. Dennison, and L. L. Hess. 2007. “Sub-Pixel Mapping of Urban Land Cover Using Multiple Endmember Spectral Mixture Analysis: Manaus, Brazil.” Remote Sensing of Environment 106 (2): 253–267. doi:10.1016/j.rse.2006.09.005.
  • Pu, R., P. Gong, R. Michishita, and T. Sasagawa. 2008. “Spectral Mixture Analysis for Mapping Abundance of Urban Surface Components from the Terra/ASTER Data.” Remote Sensing of Environment 112 (3): 939–954. doi:10.1016/j.rse.2007.07.005.
  • Roberts, D. A., M. Gardner, R. Church, S. Ustin, G. Scheer, and R. O. Green. 1998. “Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models.” Remote Sensing of Environment 65 (3): 267–279. doi:10.1016/s0034-4257(98)00037-6.
  • Rosso, P. H., S. L. Ustin, and A. Hastings. 2005. “Mapping Marshland Vegetation of San Francisco Bay, California, Using Hyperspectral Data.” International Journal of Remote Sensing 26 (23): 5169–5191.
  • Samanta, A., S. Ganguly, E. Vermote, R. R. Nemani, and R. B. Myneni. 2012. “Interpretation of Variations in MODIS-Measured Greenness Levels of Amazon Forests During 2000 to 2009.” Environmental Research Letters 7 (2): 024018.
  • Sexton, J. O., X. Song, C. Huang, S. Channan, M. E. Baker, and J. R. Townshend. 2013. “Urban Growth of the Washington, D.C.–Baltimore, MD Metropolitan Region from 1984 to 2010 by Annual, Landsat-Based Estimates of Impervious Cover.” Remote Sensing of Environment 129: 42–53. doi:http://dx.doi.org/10.1016/j.rse.2012.10.025.
  • Stevens, D., S. Dragicevic, and K. Rothley. 2007. “ICity: A GIS-CA Modelling Tool for Urban Planning and Decision Making.” Environmental Modelling & Software 22 (6): 761–773. doi:10.1016/j.envsoft.2006.02.004.
  • Sung, C., and M. Li. 2012. “Considering Plant Phenology for Improving the Accuracy of Urban Impervious Surface Mapping in a Subtropical Climate Regions.” International Journal of Remote Sensing 33 (1): 261–275. doi:10.1080/01431161.2011.591445.
  • Van Metre, P. C., and B. J. Mahler. 2005. “Trends in Hydrophobic Organic Contaminants in Urban and Reference Lake Sediments Across the United States, 1970–2001.” Environmental Science & Technology 39 (15): 5567–5574. doi:10.1021/es0503175.
  • Ward, D., S. R. Phinn, and A. T. Murray. 2000. “Monitoring Growth in Rapidly Urbanizing Areas Using Remotely Sensed Data.” Professional Geographer 52 (3): 371–386. doi:10.1111/0033-0124.00232.
  • Weng, Q. 2012. “Remote Sensing of Impervious Surfaces in the Urban Areas: Requirements, Methods, and Trends.” Remote Sensing of Environment 117: 34–49. doi:10.1016/j.rse.2011.02.030.
  • Weng, Q., and X. Hu. 2008. “Medium Spatial Resolution Satellite Imagery for Estimating and Mapping Urban Impervious Surfaces Using LSMA and ANN.” IEEE Transactions on Geoscience and Remote Sensing 46 (8): 2397–2406. doi:10.1109/tgrs.2008.917601.
  • Weng, Q., X. Hu, and H. Liu. 2009. “Estimating Impervious Surfaces Using Linear Spectral Mixture Analysis with Multitemporal ASTER Images.” International Journal of Remote Sensing 30 (18): 4807–4830. doi:10.1080/01431160802665926.
  • Wu, C. 2004. “Normalized Spectral Mixture Analysis for Monitoring Urban Composition Using ETM Plus Imagery.” Remote Sensing of Environment 93 (4): 480–492. doi:10.1016/j.rse.2004.08.003.
  • Wu, C. 2009. “Quantifying High-Resolution Impervious Surfaces Using Spectral Mixture Analysis.” International Journal of Remote Sensing 30 (11): 2915–2932. doi:10.1080/01431160802558634.
  • Wu, C., and A. T. Murray. 2003. “Estimating Impervious Surface Distribution by Spectral Mixture Analysis.” Remote Sensing of Environment 84 (4): 493–505. doi:10.1016/s0034-4257(02)00136-0.
  • Wu, C., and F. Yuan. 2007. “Seasonal Sensitivity Analysis of Impervious Surface Estimation with Satellite Imagery.” Photogrammetric Engineering and Remote Sensing 73 (12): 1393–1401.
  • Wu, J. 2010. “Urban Sustainability: An Inevitable Goal of Landscape Research.” Landscape Ecology 25 (1): 1–4. doi:10.1007/s10980-009-9444-7.
  • Wu, J., G. D. Jenerette, A. Buyantuyev, and C. L. Redman. 2011. “Quantifying Spatiotemporal Patterns of Urbanization: The Case of the Two Fastest Growing Metropolitan Regions in the United States.” Ecological Complexity 8 (1): 1–8. doi:10.1016/j.ecocom.2010.03.002.
  • Xian, G., and M. Crane. 2005. “Assessments of Urban Growth in the Tampa Bay Watershed Using Remote Sensing Data.” Remote Sensing of Environment 97 (2): 203–215. doi:10.1016/j.rse.2005.04.017.
  • Xian, G., and C. Homer. 2010. “Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 Using Landsat Imagery Change Detection Methods.” Remote Sensing of Environment 114 (8): 1676–1686. doi:10.1016/j.rse.2010.02.018.
  • Yang, F., B. Matsushita, and T. Fukushima. 2010. “A Pre-Screened and Normalized Multiple Endmember Spectral Mixture Analysis for Mapping Impervious Surface Area in Lake Kasumigaura Basin, Japan.” ISPRS Journal of Photogrammetry and Remote Sensing 65 (5): 479–490. doi:10.1016/j.isprsjprs.2010.06.004.
  • Yang, F., B. Matsushita, T. Fukushima, and W. Yang. 2012. “Temporal Mixture Analysis for Estimating Impervious Surface Area from Multi-Temporal MODIS NDVI Data in Japan.” ISPRS Journal of Photogrammetry and Remote Sensing 72: 90–98. doi:10.1016/j.isprsjprs.2012.05.016.
  • Yang, L., L. Jiang, H. Lin, and M. Liao. 2009. “Quantifying Sub-Pixel Urban Impervious Surface Through Fusion of Optical and InSAR Imagery.” Giscience & Remote Sensing 46 (2): 161–171. doi:10.2747/1548-1603.46.2.161.
  • Yang, L. M., C. Q. Huang, C. G. Homer, B. K. Wylie, and M. J. Coan. 2003. “An Approach for Mapping Large-Area Impervious Surfaces: Synergistic Use of Landsat-7 ETM+ and High Spatial Resolution Imagery.” Canadian Journal of Remote Sensing 29 (2): 230–240.
  • Yang, L. M., G. Xian, J. M. Klaver, and B. Deal. 2003. “Urban Land-Cover Change Detection Through Sub-Pixel Imperviousness Mapping Using Remotely Sensed Data.” Photogrammetric Engineering and Remote Sensing 69 (9): 1003–1010.
  • Yuan, F., M. E. Bauer, N. J. Heinert, and G. R. Holden. 2005. “Multi‐Level Land Cover Mapping of the Twin Cities (Minnesota) Metropolitan Area with Multi‐Seasonal Landsat TM/ETM+ Data.” Geocarto International 20 (2): 5–13. doi:10.1080/10106040508542340.
  • Yuan, F., C. Wu, and M. E. Bauer. 2008. “Comparison of Spectral Analysis Techniques for Impervious Surface Estimation Using Landsat Imagery.” Photogrammetric Engineering and Remote Sensing 74 (8): 1045–1055.
  • Zang, S., C. Wu, H. Liu, and X. Na. 2011. “Impact of Urbanization on Natural Ecosystem Service Values: A Comparative Study.” Environmental Monitoring and Assessment 179 (1–4): 575–588. doi:10.1007/s10661-010-1764-1.
  • Zhou, L. M., R. E. Dickinson, Y. H. Tian, J. Y. Fang, Q. X. Li, R. K. Kaufmann, C. J. Tucker, and R. B. Myneni. 2004. “Evidence for a Significant Urbanization Effect on Climate in China.” Proceedings of the National Academy of Sciences of the United States of America 101 (26): 9540–9544. doi:10.1073/pnas.0400357101.

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