Multitemporal analysis of urban reflectance Christopher Small* Lamont Doherty Earth Observatory, Columbia University, Palisades, NY 10964, USA Received 12 June 2001; received in revised form 4 February 2002; accepted 4 February 2002 Abstract Spatial and temporal changes in urban reflectance have a strong influence on energy flux through the urban environment. Optical sensors on operational satellites provide self-consistent time series of urban reflectance variations, but quantitative analyses are complicated by spectral heterogeneity at sensor instantaneous field of view (IFOV) scales and by temporal changes in illumination and atmospheric conditions. These complications can be minimized by combining a multitemporal radiometric rectification with a physically based reflectance analysis. Spectral Mixture Analysis (SMA) provides a physically based approach to quantifying spatial and temporal changes in spectrally heterogeneous urban reflectance. Multitemporal analysis of Landsat Thematic Mapper (TM) imagery of the New York metropolitan area suggests that urban reflectance can be described with a three-component linear mixture model spanned by high albedo, low albedo, and vegetation endmembers. The topology of the spectral mixing space indicates that mixing fractions are well constrained for the vegetation endmember and that nonlinear mixing occurs primarily between the high and low albedo endmembers. Selection of pseudoinvariant (PIV) image endmembers allows radiometric rectification of multitemporal imagery to a common set of endmembers, thereby minimizing variations in radiance that are unrelated to changes in surface reflectance. Inversion of the three- component linear mixture model for the New York metro area produces robust, consistent fraction estimates for different combinations of rectifications and inversion constraints. Temporal variation of the presumed invariant endmember sites provides a measure of uncertainty for the endmember fraction estimates. The resulting vegetation fraction estimates agree with high-resolution reference measurements to within 10% for a 1996 midsummer validation and PIV endmember fraction estimates vary by less than 7% over the course of the 1996 growing season. In contrast, intraurban spatial variations in vegetation fraction span several tens of percent, suggesting that the measured changes significantly exceed the uncertainty of the estimates. These results suggest that Landsat TM imagery may be used to monitor seasonal to interannual variations in urban reflectance and vegetation abundance. D 2002 Published by Elsevier Science Inc. 1. Introduction Global urbanization is one of the primary forms of environmental change directly impacting the human popu- lation. Although cities occupy a small percentage of the Earth’s land area, the physical conditions of the urban environment exert a direct influence on almost half of the world’s population (United Nations, 1999). In order to understand the physical dynamics of the urban environment, it will be necessary to quantify changes in certain key environmental parameters. Many of the important envir- onmental parameters in urban areas are best measured in situ, but some parameters are more amenable to measure- ment by remote sensing. Optical remote sensing measures upwelling radiance, a parameter directly related to the albedo and surface reflectance of the urban mosaic. Albedo is a critical environmental parameter because it modulates energy fluxes and can be influenced by choices of building materials and landcovers. Temporal variations in the albedo of the urban mosaic exert a strong influence on the energy flux through urban environments. A procedure to estimate shortwave urban albedo from Landsat MSS imagery was devised by Brest and Goward (1987) and used by Brest (1987) to quantify seasonal variability in urban albedo for input to climate models. One of the primary determinants of the albedo and surface temperatures in urban and suburban environments is the spatial and temporal distribution of vegetation (Goward, Cruickshanks, & Hope, 1985). Fig. 1 shows an example of the seasonal variation in Near Infrared (NIR) reflectance resulting from vegetation phenology in the New York metro area. By modulating reflection and 0034-4257/02/$ – see front matter D 2002 Published by Elsevier Science Inc. PII:S0034-4257(02)00019-6 * Tel.: +1-845-365-8354; fax: +1-845-365-8179. E-mail address: small@ldeo.columbia.edu (C. Small). www.elsevier.com/locate/rse Remote Sensing of Environment 81 (2002) 427 – 442