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Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time. [ABSTRACT FROM AUTHOR]

The structure of urban environments is known to alter local climate, in part due to changes in land cover. A growing subset of research focuses specifically on the UHI in terms of land surface temperature by using data from remote sensing platforms. Past research has established a clear relationship between land surface temperature and the proportional area of land covers, but less research has specifically examined the effects of the spatial patterns of these covers. This research considers the rapidly growing City of Phoenix, Arizona in the United States. To better understand how landscape structure affects local climate, we explored the relationship between land surface temperature and spatial pattern for three different land uses: mesic residential, xeric residential, and industrial/commercial. We used high-resolution (2.4 m) land cover data and an ASTER temperature product to examine 90 randomly selected sample sites of 240 square-meters. We (1) quantify several landscape-level and class-level landscape metrics for the sample sites, (2) measure the Pearson correlation coefficients between land surface temperature and each landscape metric, (3) conduct an analysis of variance among the three land uses, and (4) model the determinants of land surface temperature using ordinary least squares linear regression. The Pearson's correlation coefficients reveal significant relationships between several measures of spatial configuration and LST, but these relationships differ among the land uses. The ANOVA confirmed that mean land surface temperature and spatial patterns differed among the three land uses. Although a relationship was apparent between surface temperatures and spatial pattern, the results of the linear regression indicate that proportional land cover of grass and impervious surfaces alone best explains temperature in mesic residential areas. In contrast, temperatures in industrial/commercial areas are explained by changes in the configuration of grass and impervious surfaces. [ABSTRACT FROM AUTHOR]

The article presents a study which investigates the dynamics of phosphorus in an urban ecosystem. The study made use of a three-pronged approach to understand the P cycling in the greater Phoenix, Arizona metropolitan area such as the mass balance approach and land cover and land-use data. The result of the study suggests that the cross-boundary fluxes of P to the city should be minimized by more efficient recycling of waste.

A common critique of urban sprawl is that it leads to increased land fragmentation, which has negative social and ecological implications. Consistent with theory, empirical research generally finds increased levels of fragmentation near the urban fringe. We apply landscape metrics to 1-m resolution remotely sensed imagery of the City of Phoenix, Arizona from 2010 in order to analyze urban sprawl based on the area, fragmentation, shape complexity, and diversity of land covers at a resolution finer than that of an individual land parcel. While previous work typically defines areas by how far they are from the central city, we identify census block groups in Phoenix based on the decade during which they became developed in order to observe landscape variation based on the age of a neighborhood area. Results confirm substantial variation in present-day land cover patterns based on the timing of development: landscape structure in Phoenix is heavily path-dependent. While land covers in newer-developing regions generally appear more fragmented, more homogeneous, and less diverse, the complexity of shapes and incidence of desert landscaping appear to be higher as well. Areas that developed principally during the 1990s and 2000s appear noticeably different than their older counterparts across many measures used. We speculate that institutional changes and evolving preferences for various development types explain much of this present-day variation. [ABSTRACT FROM AUTHOR]