Matching Items (17)

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Supporting Global Environmental Change Research: A Review of Trends and Knowledge Gaps in Urban Remote Sensing

Description

This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and

This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and science communities’ increasing need for detailed and up-to-date information on the multiple dimensions of cities, including their social, biological, physical, and infrastructural characteristics. Because the interactions between urban and surrounding areas are complex, a synoptic and spatial view offered from remote sensing is integral to measuring, modeling, and understanding these relationships. Here we focus on three themes in urban remote sensing science: mapping, indices, and modeling. For mapping we describe the data sources, methods, and limitations of mapping urban boundaries, land use and land cover, population, temperature, and air quality. Second, we described how spectral information is manipulated to create comparative biophysical, social, and spatial indices of the urban environment. Finally, we focus how the mapped information and indices are used as inputs or parameters in models that measure changes in climate, hydrology, land use, and economics.

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Created

Date Created
  • 2014-04-30

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Rooftop Surface Temperature Analysis in an Urban Residential Environment

Description

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

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.

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Created

Date Created
  • 2015-09-18

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A MODIS/ASTER Airborne Simulator (MASTER) Imagery for Urban Heat Island Research

Description

Thermal imagery is widely used to quantify land surface temperatures to monitor the spatial extent and thermal intensity of the urban heat island (UHI) effect. Previous research has applied Landsat

Thermal imagery is widely used to quantify land surface temperatures to monitor the spatial extent and thermal intensity of the urban heat island (UHI) effect. Previous research has applied Landsat images, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, Moderate Resolution Imaging Spectroradiometer (MODIS) images, and other coarse- to medium-resolution remotely sensed imagery to estimate surface temperature. These data are frequently correlated with vegetation, impervious surfaces, and temperature to quantify the drivers of the UHI effect. Because of the coarse- to medium-resolution of the thermal imagery, researchers are unable to correlate these temperature data with the more generally available high-resolution land cover classification, which are derived from high-resolution multispectral imagery. The development of advanced thermal sensors with very high-resolution thermal imagery such as the MODIS/ASTER airborne simulator (MASTER) has investigators quantifying the relationship between detailed land cover and land surface temperature. While this is an obvious next step, the published literature, i.e., the MASTER data, are often used to discriminate burned areas, assess fire severity, and classify urban land cover. Considerably less attention is given to use MASTER data in the UHI research. We demonstrate here that MASTER data in combination with high-resolution multispectral data has made it possible to monitor and model the relationship between temperature and detailed land cover such as building rooftops, residential street pavements, and parcel-based landscaping. Here, we report on data sources to conduct this type of UHI research and endeavor to intrigue researchers and scientists such that high-resolution airborne thermal imagery is used to further explore the UHI effect.

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Created

Date Created
  • 2016-06-06

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Implementing rapid assessment of the trail environments of arid regions: indicator development and implementation scenarios

Description

As part of the effort to streamline management efforts in protected areas worldwide and assist accountability reporting, new techniques to help guide conservation goals and monitor progress are needed. Rapid

As part of the effort to streamline management efforts in protected areas worldwide and assist accountability reporting, new techniques to help guide conservation goals and monitor progress are needed. Rapid assessment is recognized as a field-level data collection technique, but each rapid assessment index is limited to only the ecoregion for which it is designed. This dissertation contributes to the existing bodies of conservation monitoring and tourism management literature in four ways: (i.) Indicators are developed for rapid assessment in arid and semi-arid regions, and the processes by which new indicators should be developed is explained; (ii.) Interpolation of surveyed data is explored as a step in the analysis process of a dataset collected through rapid assessment; (iii.) Viewshed is used to explore differences in impacts at two study sites and its underutilization in this context of conservation management is explored; and (iv.) A crowdsourcing tool to distribute the effort of monitoring trail areas is developed and deployed, and the results are used to explore this data collection's usefulness as a management tool.

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Created

Date Created
  • 2013

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An exploratory toolkit for examining residential movement patterns at a micro scale

Description

Change of residence is a commonly occurring event in urban areas. It reflects how people interact with the social or physical environment. Thus, by exploring the movement patterns of residential

Change of residence is a commonly occurring event in urban areas. It reflects how people interact with the social or physical environment. Thus, by exploring the movement patterns of residential changes, geographers and other scholars hope to learn more about the reasons and impacts associated with residential mobility, and to better understand how humans and the environment mutually interact. This is especially meaningful if exploration is based on micro scale movements, since residential changes within a city or a county reflect how the urban structure and community composition interact. Local differentiation, as an inevitable feature among movements at different places, can best be examined based on data at the micro scale. Such work is meaningful, but there have not been appropriate approaches for assessment and evaluation. The majority of traditional methods concentrate more on aggregate movement data at a national scale. So, in order to facilitate research examining movement patterns from a mass of individual residential changes at a micro scale, a toolkit, implemented by computational programming, is introduced in this dissertation to integrate both exploratory as well as confirmatory methods. This toolkit also employs a creative method to explore the spatial autocorrelation of residential movements, reflecting the local effects involved in this social event. The effectiveness and efficiency of this toolkit is examined through a concrete application involving 2,363 residential movements in Franklin County, Ohio.

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Created

Date Created
  • 2012

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Implicit visualization as usable science visualizing uncertainty as decision outcomes

Description

Decision makers contend with uncertainty when working through complex decision problems. Yet uncertainty visualization, and tools for working with uncertainty in GIS, are not widely used or requested in decision

Decision makers contend with uncertainty when working through complex decision problems. Yet uncertainty visualization, and tools for working with uncertainty in GIS, are not widely used or requested in decision support. This dissertation suggests a disjoint exists between practice and research that stems from differences in how visualization researchers conceptualize uncertainty and how decision makers frame uncertainty. To bridge this gap between practice and research, this dissertation explores uncertainty visualization as a means for reframing uncertainty in geographic information systems for use in policy decision support through three connected topics. Initially, this research explores visualizing the relationship between uncertainty and policy outcomes as a means for incorporating policymakers' decision frames when visualizing uncertainty. Outcome spaces are presented as a method to represent the effect of uncertainty on policy outcomes. This method of uncertainty visualization acts as an uncertainty map, representing all possible outcomes for specific policy decisions. This conceptual model incorporates two variables, but implicit uncertainty can be extended to multivariate representations. Subsequently, this work presented a new conceptualization of uncertainty, termed explicit and implicit, that integrates decision makers' framing of uncertainty into uncertainty visualization. Explicit uncertainty is seen as being separate from the policy outcomes, being described or displayed separately from the underlying data. In contrast, implicit uncertainty links uncertainty to decision outcomes, and while understood, it is not displayed separately from the data. The distinction between explicit and implicit is illustrated through several examples of uncertainty visualization founded in decision science theory. Lastly, the final topic assesses outcome spaces for communicating uncertainty though a human subject study. This study evaluates the effectiveness of the implicit uncertainty visualization method for communicating uncertainty for policy decision support. The results suggest that implicit uncertainty visualization successfully communicates uncertainty in results, even though uncertainty is not explicitly shown. Participants also found the implicit visualization effective for evaluating policy outcomes. Interestingly, participants also found the explicit uncertainty visualization to be effective for evaluating the policy outcomes, results that conflict with prior research.

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Created

Date Created
  • 2013

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Measuring the success of a transportation project: Loop 202 (Red Mountain Freeway) case study

Description

Measuring the success of a transportation project as it is envisioned in the Regional Transportation Plan (RTP) and is detailed in an Environmental Impact Statement (EIS) is not part of

Measuring the success of a transportation project as it is envisioned in the Regional Transportation Plan (RTP) and is detailed in an Environmental Impact Statement (EIS) is not part of any current planning process, for a post construction analysis may have political consequences for the project participants, would incur additional costs, and may be difficult to define in terms of scope. With local, state and federal budgets shrinking, funding sources are demanding that the performance of a project be evaluated and project stakeholders be held accountable. The Transportation Research Board (TRB) developed a framework that allows transportation agencies to customize their reporting so that a project's performance can be measured. In the case of the Red Mountain Freeway, the selected performance measure allows for comparing the population forecasts, the traffic volumes, and the project costs defined in the final EIS to actual population growth, actual average annual daily traffic (ADT), and actual project costs obtained from census data, the City of Mesa, and contractor bids, respectively. The results show that population projections for both Maricopa County and the City of Mesa are within less than half a percent of the actual annual population growth. The traffic analysis proved more difficult due to inconsistencies within the EIS documents, variations in the local arterials used to produce traffic volume, and in the projection time-spans. The comparison for the total increase in traffic volume generated a difference of 11.34 percent and 89.30 percent. An adjusted traffic volume equal to all local arterials and US 60 resulted in a difference of 40 percent between the projected and actual ADT values. As for the project cost comparison, not only were the costs within the individual documents inconsistent, but they were underestimated by as much as 75 percent. Evaluating the goals as described in an EIS document using the performance measure guidelines provided by the TRB may provide the tool that can help promote conflict resolution for political issues that arise, streamline the planning process, and measure the performance of the transportation system, so that lessons learned can be applied to future projects.

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Created

Date Created
  • 2012

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Evaluation of Geodesign as a Planning Framework for American Indian Communities in the Southwest United States

Description

The overarching aim of this dissertation is to evaluate Geodesign as a planning approach for American Indian communities in the American Southwest. There has been a call amongst indigenous planners

The overarching aim of this dissertation is to evaluate Geodesign as a planning approach for American Indian communities in the American Southwest. There has been a call amongst indigenous planners for a planning approach that prioritizes indigenous and community values and traditions while incorporating Western planning techniques. Case studies from communities in the Navajo Nation and the Tohono O’odham Nation are used to evaluate Geodesign because they possess sovereign powers of self-government within their reservation boundaries and have historical and technical barriers that have limited land use planning efforts. This research aimed to increase the knowledge base of indigenous planning, participatory Geographic information systems (GIS), resiliency, and Geodesign in three ways. First, the research examines how Geodesign can incorporate indigenous values within a community-based land use plan. Results showed overwhelmingly that indigenous participants felt that the resulting plan reflected their traditions and values, that the community voice was heard, and that Geodesign would be a recommended planning approach for other indigenous communities. Second, the research examined the degree in which Geodesign could incorporate local knowledge in planning and build resiliency against natural hazards such as flooding. Participants identified local hazards, actively engaged in developing strategies to mitigate flood risk, and utilized spatial assessments to plan for a more flood resilient region. Finally, the research examined the role of the planner in conducting Geodesign planning efforts and how Geodesign can empower marginalized communities to engage in the planning process using Arnstein’s ladder as an evaluation tool. Results demonstrated that outside professional planners, scientists, and geospatial analysts needed to assume the role of a facilitator, decision making resource, and a capacity builder over traditional roles of being the plan maker. This research also showed that Geodesign came much closer to meeting American Indian community expectations for public participation in decision making than previous planning efforts. This research demonstrated that Geodesign planning approaches could be utilized by American Indian communities to assume control of the planning process according to local values, traditions, and culture while meeting rigorous Western planning standards.

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Created

Date Created
  • 2020

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Modeling suitable habitat under climate change for chaparral shrub communities in the Santa Monica Mountains National Recreation Area, California

Description

Species distribution modeling is used to study changes in biodiversity and species range shifts, two currently well-known manifestations of climate change. The focus of this study is to explore how

Species distribution modeling is used to study changes in biodiversity and species range shifts, two currently well-known manifestations of climate change. The focus of this study is to explore how distributions of suitable habitat might shift under climate change for shrub communities within the Santa Monica Mountains National Recreation Area (SMMNRA), through a comparison of community level to individual species level distribution modeling. Species level modeling is more commonly utilized, in part because community level modeling requires detailed community composition data that are not always available. However, community level modeling may better detect patterns in biodiversity. To examine the projected impact on suitable habitat in the study area, I used the MaxEnt modeling algorithm to create and evaluate species distribution models with presence only data for two future climate models at community and individual species levels. I contrasted the outcomes as a method to describe uncertainty in projected models. To derive a range of sensitivity outcomes I extracted probability frequency distributions for suitable habitat from raster grids for communities modeled directly as species groups and contrasted those with communities assembled from intersected individual species models. The intersected species models were more sensitive to climate change relative to the grouped community models. Suitable habitat in SMMNRA's bounds was projected to decline from about 30-90% for the intersected models and about 20-80% for the grouped models from its current state. Models generally captured floristic distinction between community types as drought tolerance. Overall the impact on drought tolerant communities, growing in hotter, drier habitat such as Coastal Sage Scrub, was predicted to be less than on communities growing in cooler, moister more interior habitat, such as some chaparral types. Of the two future climate change models, the wetter model projected less impact for most communities. These results help define risk exposure for communities and species in this conservation area and could be used by managers to focus vegetation monitoring tasks to detect early response to climate change. Increasingly hot and dry conditions could motivate opportunistic restoration projects for Coastal Sage Scrub, a threatened vegetation type in Southern California.

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Created

Date Created
  • 2014