Urban Imperviousness Research Articles

Designing a Multi-Objective, Multi-Support Accuracy Assessment of the 2001 National Land Cover Data (NLCD 2001) of the Conterminous United States

The database design and diverse application of NLCD 2001 pose significant challenges for accuracy assessment because numerous objectives are of interest, including accuracy of land-cover, percent urban imperviousness, percent tree canopy, land-cover composition, and net change. A multi-support approach is needed because these objectives require spatial units of different sizes for reference data collection and analysis. Determining a sampling design that meets the full suite of desirable objectives for the NLCD 2001 accuracy assessment requires reconciling potentially conflicting design features that arise from targeting the different objectives. Multi-stage cluster sampling provides the general structure to achieve a multi-support assessment, and the flexibility to target different objectives at different stages of the design. We describe the implementation of two-stage cluster sampling for the initial phase of the NLCD 2001 assessment, and identify gaps in existing knowledge where research is needed to allow full implementation of a multi-objective, multi-support assessment.

Estimation of Urban Imperviousness and its Impacts on Storm Water Systems

Imperviousness is an important indicator of the impact of urbanization on storm water systems. A hydrologic analysis was performed to evaluate long-term impacts from an apartment area in Miami. The result shows that the directly connected impervious area (DCIA), which covers 44% of the catchment, contributes 72% of the total runoff volume during 52 years. Few studies have actually measured the DCIA with a high level of accuracy for residential areas that constitute the largest proportion of urban land. A detailed analysis of urban imperviousness was performed using geographic information systems and field investigations on a 5.81 ha residential area in Boulder, Colo. For this study area, the total impervious area is 35.9% and the DCIA is 13.0%. Transportation-related imperviousness comprises 97.2% of the DCIA. Hydrologic modeling of this area shows about a 265% difference in estimates of peak discharge with imperviousness measured at five different levels of accuracy. These results suggest the need to focus on DCIA as the key indicator of urbanization’s effect on storm water quantity and quality.

Effectiveness of Subpixel Analysis in Detecting and Quantifying Urban Imperviousness from Landsat Thematic Mapper Imagery

The quantification of urban imperviousness using remotely sensed spectral data is next to impossible unless a spectral fraction of impervious components in an urban pixel can be detected. In this research, a multiple‐signature subpixel analysis technique coupled with a layered classification approach was developed to map urban imperviousness of each pixel of an urban scene into eight 10‐percent levels. The subpixel analysis was based on the idea of removing background spectra from the total radiance of a pixel and testing the residual spectrum against the signature spectrum. This study demonstrated that although the subpixel analysis was able to quantify urban imperviousness from most of the urban pixels, it experienced some difficulty in handling the spectral heterogeneity of diverse urban features. The layered classification approach was used to identify the extreme cases. An experiment of classifying Landsat TM data into eight levels of urban imperviousness revealed that 83.0% (kappa = 0.787) of the impervious pixels agreed with reference data. A Spearman rank‐order correlation analysis yielded rho = 0.964, giving a much improved assessment of the urban imperviousness map at subpixel level. Linear regression analysis is suggested, if interval data are retained from the subpixel process, as an alternative for map error modeling and model calibration with ground truth.