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A Case Study for Durban, South Africa (1985-2009)

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A Case Study for Durban, South Africa (1985-2009) Subpixel Land Cover Change from Landsat: A Case Study for Durban, South Africa (1985-2009) Christopher Small, Lamont-Doherty Earth Observatory, Columbia University Cristina Milesi, California State University Monterey Bay / NASA Ames Research Center Introduction Results Satellite-based land cover change characterization of urban areas and their surrounding regions offers a valuable tool for investigating the effects of RGB composites of Substrate, Vegetation & Dark fractions derived from Spectral Mixture Analysis for 3/23/1985, 3/25/2000, and 3/24/2009 King Shaka Airport Hazelmere Dam socio-economic changes on the physical environment, and thus understand King Shaka Airport King Shaka Airport the challenges for sustainable development. Verulam Verulam However, land cover change characterization over urbanized areas is Verulam Inanda Dam Inanda Dam complicated by the presence of spectrally heterogeneous land cover types Inanda Dam within the field of view of satellite sensors with spatial resolution greater Early construction Inanda Phoenix Inanda Inanda Phoenix than a few meters. Multitemporal spectral mixture analysis (MSMA) derives Phoenix Hillcrest physical representations of the temporal changes within spectrally mixed Hillcrest KwaMashu KwaMashu pixels as areal fractions of spectral endmembers. KwaMashu Pinetown Here we show an example of land cover change prepared in occasion of the Pinetown Pinetown 2011 COP 17 meeting in Durban, South Africa. Durban is an example of an African city where changes in climate have the potential to pose significant Durban Durban challenges on the local population that is already vulnerable in terms of Durban poverty, health, and secure access to food and water. Characterization and maping of changes in vegetation, shadow and impervious fractions from the Chatsworth Chatsworth Chatsworth Landsat archive offers an opportunity to examine the effects of significant socio-economic changes during the pre- and post Apartheid period (before Umlazi Umlazi Umlazi Durban Mpandwini Durban Durban International and after 1994) on the urbanization of South Africa from 1985 to 2009. International Intenational Airport Airport Airport Nungwane 1985 Nungwane Nungwane Illovo 2000 Illovo 2009 Dam Dam Illovo Dam Methods RGB composites of change in fractions derived from Spectral Mixture Analysis for 2000-1985, 2009-2000, and 2009-1985. Color indicates increase in substrate, increase in vegetation, and increase in dark fraction (water or shadow). Prominent changes include Increase in impervious+shadow, impounded water and Increase in fallow croplands. Abandoned Completion of King Shaka Airport took place between 2000 and We use the linear spectral mixture model (Adams et al. (1986, 1993) to construction at King 2010), and now replaces Durban Inanda Dam, Water supply Int. Airport. represent land cover as fractions of Substrate, Vegetation and Dark Sugar cane Shaka W to Durban, Completed in 1998, cultivation Airport. surfaces. The Substrate endmember represents SWIR-bright rock, soil Construction began Sugar cane Sugar cane in 1973. The project cultivation cultivation and impervious surfaces. The Vegetation endmember represents was halted in 1982 due to an economic illuminated foliage. The Dark endmember represents water, shadow and slowdown. absorptive materials. We use a unity-constrained inversion of the 6x3 Uhmalanga Gateway, largest shopping mall on the African Hillcrest Hillcrest linear mixture model based on the Singular Value Decomposition given continent. Built on a dump Construction boom in Densification of Construction boom in that closed in the mid-1990. 1990’s and 2000’s KwaMashu 1990’s and 2000’s by Boardman (1989, 1990). Calibration to exoatmospheric reflectance, The sixth largest electricity radiometric rectification, and use of generic global endmembers (Small, consumer in the Durban Mpumalanga metro area. Mpumalanga Cropland and forestry 2004) reduce, but do not completely eliminate spurious change., Modal Mpumalanga changes Cropland and forestry Densification of Cropland and forestry difference fractions of Substrate and Vegetation are 0.01 and 0.005 Densification of changes Inland Durban changes respectively, indicating that the calibration and rectification are Inland Durban effective. The modal difference fraction for the Dark endmember is - Densification 0.35; a result of actual changes in both atmospheric opacity and of Umlazi turbidity in the coastal ocean. township Durban International Sugar plantations Airport losing traffic in Sugar plantations Sugar plantations Expansion of by Mpandwini favor of Tambo by Mpandwini by Mpandwini Umlazi RGB composites of the SVD fractions show the dominant endmember International Airport in Johannesburg township combinations as additive colors. RGB composites of the fraction differences show relative increases in SVD fractions. Relative 2000-1985 2009-2000 2009-1985 increases in one or two fractions may result from decreases in the Sugar plantations Sugar plantations complementary fraction(s). by Illovo by Illovo References Acknowledgment Adams, J. B., M. O. Smith, et al. (1993). Imaging Spectroscopy: Interpretation based on spectral mixture analysis. Remote Geochemical Analysis: Elemental and Mineralogical Composition. C. M. Pieters and P. Englert. New York, Cambridge University Press: 145-166. Adams, J. B., M. O. Smith, et al. (1986). "Spectral mixture modeling; A new analysis of rock and soil types at the Viking Lander 1 site." Journal of Geophysical Research 91: 8098- 8122. This work is supported by a grant from the NASA Land Boardman, J. (1990). "Inversion of high spectral resolution data." SPIE - Imaging Spectroscopy of the Terrestrial Environment 1298: 222-233. Boardman, J. W. (1989). Inversion of imaging spectrometry data using singular value decomposition. IGARSS'89 12th Canadian Symposium on Remote Sensing, Vancouver, B.C. Cover and Land Use Change Program. Small, C. (2004). The Landsat ETM+ spectral mixing space. Remote Sensing of Environment, 93, 1-17. .
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