Elizabeth A. Wentz

The Spatial Structure of Land Use from 1970–2000 in the Phoenix, Arizona, Metropolitan Area

Abstract This article explores the dimensions of rapid urbanization in the Phoenix Standard Metropolitan Statistical Area (SMSA) over the past thirty years with respect to land use change. We devote primary attention to developing an understanding of what land transformations took place, the extent to which they occurred, and where they occurred. Our findings indicate that 32 percent of the Phoenix SMSA changed between 1970 and 2000. More than half of the overall change was from agriculture to some form of urban land use, and although a large percentage of the region remains open desert the parcels of desert are increasingly fragmented. This has significant implications for urban ecology and biodiversity. The growth indicates that rather than a pattern that reflects the agglomeration effects of a polycentric metropolis, the central business district of the City of Phoenix dominates the region. This has implications with respect to employment patterns, traffic congestion, and urban air quality and climate.

Spatial Patterns and Determinants of Winter Atmospheric Carbon Dioxide Concentrations in an Urban Environment

The purpose of this article is to describe determinants and spatial patterns of atmospheric carbon dioxide (CO2) in Phoenix, Arizona. Specifically, we use geographic information systems (GIS) and regression-based analyses to identify the human and biological factors that contribute to spatial and temporal variations in near-surface (2-meter height) atmospheric CO2 levels. We use these factors to create estimated surfaces of CO2 concentrations for the area. We evaluate the surfaces using records of CO2 from independent monitoring stations and transects. To investigate the temporal patterns and variations in CO2 concentrations, we estimate CO2 surfaces for the early mornings and the afternoons, on weekdays when traffic is heavy and spatially focused and on weekends when it is lighter and more spatially dispersed. Findings suggest there is a distinct relationship between the structure of Phoenix CO2 levels and spatial patterns of human activities and vegetation densities. Morning CO2 levels are higher than afternoon levels and correspond closely to the density of traffic, population, and employment. The spatial structure of human activity explains the pattern of CO2 better on weekdays than on weekends. CO2 surfaces reflect declining densities of human activity with distance from the city center, the pattern of irrigated agriculture in the Phoenix area, and riparian habitats on the urban fringe. Spatial and temporal patterns of CO2 concentrations are useful in understanding urban climate and ecosystem processes.

Land use and land cover mapping from diverse data sources for an arid urban environments

Accurate and up-to-date data describing land use and land cover change support studies of urban growth such as quantifying the amount of rural to urban change and identifying change trajectories. This paper compares three methods for identifying urban land use/land cover, based on aerial photography, satellite imagery, and ground observations. While it might be natural to assume that classification based on ground observations would be the most accurate, this may not always be the case. Here we aim to quantify to what degree these three different classification approaches agree or contradict each other and to understand why. Land use/land cover data derived from these three sources were compared for the Phoenix metropolitan area, an arid urban region undergoing rapid urbanization. Our results show that satellite data are well suited to classify land use/land cover where land use categories are associated with homogeneous land cover at the subpixel level, but that for land use categories with subpixel land cover complexity, aerial photographs or ground observations are needed to aid in the classification.

WaterSim: a simulation model for urban water planning in Phoenix, Arizona, USA

WaterSim, a simulation model, was built and implemented to investigate how alternative climate conditions, rates of population growth, and policy choices interact to affect future water supply and demand conditions in Phoenix, AZ. WaterSim is a hierarchical model that represents supply from surface and groundwater sources and demand from residential, commercial, and agricultural user sectors, incorporating the rules that govern reservoirs, aquifer use, and land-use change. In this paper we: (1) report on the imperative for exploratory modeling in water-resource management, given the deep uncertainties of climate change, (2) describe the geographic context for the Phoenix case study, (3) outline the objectives and structure of WaterSim, (4) report on testing the model with sensitivity analyses and history matching, (5) demonstrate the application of the model through a series of simulation experiments, and (6) discuss the models use for scenario planning and climate adaptation. Simulation results show there are significant challenges to Phoenixs water sustainability from climate change and rapid growth. Policies to address these challenges require difficult tradeoffs among lifestyles, groundwater sustainability, the pace of growth, and what is considered to be an appropriate level of risk of climate-induced shortage.

Expert system classification of urban land use/cover for Delhi, India

This study presents the results of classifying land use/land cover for Delhi, India using an expert system approach. For this study Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data of 22 September 2003 were used. The research goals of this project are two‐fold. In one respect, the research goal is to report on the extent covered by urbanization using the classified image. Thirteen different land‐cover categories were identified with an 85.55% overall classification accuracy based on 256 random points for validation and 50 on the ground observations. Secondly, we report on our efforts to duplicate an expert system model previously developed for Phoenix Arizona as a generalized approach for urban land use classification. Results suggest that while some of the methodology could be duplicated, there are local factors (e.g. data availability and specific land features) that required the approach to be modified.

Spatial Heterogeneity of Denitrification in Semi-Arid Floodplains

Riparian ecosystems are recognized as sinks for inorganic nitrogen (N). Denitrification, a heterotrophic microbial process, often accounts for a significant fraction of the N removed. Characteristics of both riparian soils and hydrologic vectors may constrain the locations where denitrification can occur within riparian ecosystems by influencing the distribution of substrates, water, and suitable redox conditions. We employed spatially explicit methods to quantify heterogeneity of soil characteristics and potential rate of denitrification in semi-arid riparian ecosystems. These results allow us to evaluate the relative contributions of hydrologic vectors (water courses that convey materials) and soil resources (materials required by biota) to spatial heterogeneity of denitrification. During dry and monsoon seasons we contrasted a mesic site, characterized by shallow groundwater and annual inundation by floods, with a xeric site that is inundated less often and has a deeper water table. Potential denitrification was detected throughout the mesic floodplain and the average rate of denitrification was greater at the mesic site than at the xeric site, indicating the influence of water availability on denitrification. At the xeric reach, sharp declines in pools of soil resources and rate of denitrification occurred away from the stream, demonstrating the importance of the stream in determining spatial patterns. Using geographically weighted regression analysis, we determined that soil organic matter and soil nitrate were significant predictors of denitrification at the xeric site, but that factors influencing denitrification varied spatially. Spatial heterogeneity of carbon (C) and N substrates in soils likely influenced spatial patterns of denitrification, but distribution of C and N substrates was ultimately organized by hydrologic vectors. Droughts will increase the abundance of reaches with hydrogeomorphic templates similar to the xeric reach studied here. Consequences of such a transition may include a reduced rate of denitrification and patchy distribution of denitrification in floodplain soils, which will decrease the contribution of riparian ecosystems to N removal.

Factors Influencing Water Consumption in Multifamily Housing in Tempe, Arizona

Central to the Smart Growth movement is that compact development reduces vehicle miles traveled, carbon emissions, and water use. Empirical efforts to evaluate compact development have examined residential densities but have not distinguished decreasing lot sizes from multifamily apartments as mechanisms for compact development. Efforts to link design features to water use have emphasized single-family at the expense of multifamily housing. This study isolates the determinants of water use in large (more than fifty units) apartment complexes in the city of Tempe, Arizona. In July 2007, per bedroom water use increased with pool area, dishwashers, and in-unit laundry facilities. We are able to explain nearly 50 percent of the variation in water demand with these variables. These results inform public policy for reducing water use in multifamily housing structures, suggesting strategies to construct and market “green” apartment units.

A comparison of two methods to create tracks of moving objects: linear weighted distance and constrained random walk

As an object moves through space, it creates a track (or path) representing the objects past and present position and associated attributes. If data capture fails, then positions along the tracks are unknown. The particular problem we address in this paper is to create tracks of moving objects with missing data. We implement and test two techniques that create continuous tracks of two primate species (Ateles geoffroyi, the red spider monkey, and Cebus capucinus, the white-faced capuchin). Continuous tracks were needed to calculate home range and to analyze daily ranging patterns for each species. Establishing continuous tracks of primates through field data alone, however, was impossible due to challenging field conditions. The results of the analysis using tracks with interpolated positions helped establish that Ateles tend to move directly to their destination while Cebus tended to follow a more wandering track.

An Evaluation of Teaching Introductory Geomorphology using Computer-based Tools

This paper compares student reactions to traditional teaching approaches with those that also include computer-based components. The traditional teaching approach involved lectures, assigned readings from a textbook and a variety of hands-on exercises. As a supplement to the traditional approach, students also utilised computerbased tools. One of the computer-based tools was a prepackaged CD-ROM to complement the textbook readings. The second computer tool, used in the laboratory component of the course, was a simplified geographical information system (GIS) interface to create digital descriptions of landforms. The results show that students found both the CD-ROM- and the GIS-based exercises valuable forms of instruction when used in combination with the traditional methods.

Rooftop Surface Temperature Analysis in an Urban Residential Environment

The urban heat island (UHI) phenomenon is a significant worldwide problem caused by rapid population growth and associated urbanization. The UHI effect exacerbates heat waves during the summer, increases energy and water consumption, and causes the high risk of heat-related morbidity and mortality. UHI mitigation efforts have increasingly relied on wisely designing the urban residential environment such as using high albedo rooftops, green rooftops, and planting trees and shrubs to provide canopy coverage and shading. Thus, strategically designed residential rooftops and their surrounding landscaping have the potential to translate into significant energy, long-term cost savings, and health benefits. Rooftop albedo, material, color, area, slope, height, aspect and nearby landscaping are factors that potentially contribute. To extract, derive, and analyze these rooftop parameters and outdoor landscaping information, high resolution optical satellite imagery, LIDAR (light detection and ranging) point clouds and thermal imagery are necessary. Using data from the City of Tempe AZ (a 2010 population of 160,000 people), we extracted residential rooftop footprints and rooftop configuration parameters from airborne LIDAR point clouds and QuickBird satellite imagery (2.4 m spatial resolution imagery). Those parameters were analyzed against surface temperature data from the MODIS/ASTER airborne simulator (MASTER). MASTER images provided fine resolution (7 m) surface temperature data for residential areas during daytime and night time. Utilizing these data, ordinary least squares (OLS) regression was used to evaluate the relationships between residential building rooftops and their surface temperature in urban environment. The results showed that daytime rooftop temperature was closely related to rooftop spectral attributes, aspect, slope, and surrounding trees. Night time temperature was only influenced by rooftop spectral attributes and slope.