Faculty and Staff

In 2014/2015, Arizona State University (ASU) Libraries, the Labriola National American Indian Data Center, and the ASU American Indian Studies Department completed an ASU Institute for Humanities Research (IHR) seed grant entitled “Carlos Montezuma’s Wassaja Newsletter: Digitization, Access and Context” to digitize all ASU held issues of the newsletter Wassaja Freedom’s Signal for the Indian, which Yavapai activist-intellectual Carlos Montezuma, MD (1866-1923) self-published during 1916-1922. The grant team additionally selected a portion of the ASU Libraries Carlos Montezuma archival collection for digitization to provide a more complete picture of Dr. Carlos Montezuma’s life and work.

The ASU grant team produced a searchable online collection on the ASU Digital Repository and created an online exhibition in conjunction with the IHR Nexus Lab’s Developing Wassaja Project. The Nexus Lab’s role at ASU is to grow the digital humanities through interdisciplinary collaborations bringing together humanities, science, and technology. The Nexus Lab partnered with the grant team to create the Developing Wassaja Project which provided an opportunity for faculty, staff, and students at ASU to engage in electronic publication through web application development.

The resulting web platform, Wassaja: A Carlos Montezuma Project, provides context for this digitized collection and facilitates community interaction, including a partnership with Dr. Montezuma’s home community the Fort McDowell Yavapai Nation. In this webcast, Digital Projects Librarian Matthew Harp, Developing Wassaja Project team member Joe Buenker (subject librarian), and grant team member Joyce Martin (librarian and curator of the Labriola National American Indian Data Center) will discuss and demonstrate the resources created and the resulting partnership with the Fort McDowell Yavapai Nation. The webcast will focus on identifying collaborators and needed skills to engage in Digital Humanities research and on identifying the stages of a collaborative project.

Participants will gain insight on working directly with diverse communities; overcoming technical limitations of traditional institutional repositories; collaborative strategies with faculty, research centers, and cultural heritage societies; solutions for moving hidden collections into an engaging digital exhibition; integrating digital humanities research and instruction with library curation; and preparing for long term costs and management issues.

Anthropology librarian Juliann Couture and Joyce Martin, curator of the Labriola National American Indian Data Center, looking at the Center's display of unique Hopi Kachina dolls. Four of the kachinas (Navan Kachina; Talavi Kachina; Flute Kachina; and Ahöla Kachina) were created by artist, carver, and former ASU employee Tony Dukepoo as a gift to the libraries in 1979. The kachina dolls are on display in the Labriola Center located on the 2nd floor of the Hayden Library on ASU's Tempe campus.

The Simon Ortiz and Labriola Center Lecture on Indigenous Land, Culture, and Community addresses topics and issues across disciplines in the arts, humanities, sciences, and politics. Underscoring Indigenous American experiences and perspectives, this Series seeks to create and celebrate knowledge that evolves from an Indigenous worldview that is inclusive and that is applicable to all walks of life.” Professor Simon Ortiz discussed the overall nature of the Series, especially emphasizing the global nature of Indigenous concerns. Joyce Martin and Matthew Harp elaborated on the contributions of the Labriola National American Indian Data Center and ASU Libraries to the Series.

The Labriola Center hosts an informal event in Hayden Library which facilitates close interaction between the featured speaker and audience members. The ASU Libraries records the evening lectures which take place at the Heard Museum and presents both an audio podcast and streaming video of each lecture on the ASU Library Channel webpage. This lecture series provides not only a chance for community discussion at the events themselves, but through the innovative use of technology the ASU Libraries enables additional forums for discussion in blogs and web pages which choose to link to the streaming videos.

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.

This study examines the spatial and temporal patterns of the surface urban heat island (SUHI) intensity in the Phoenix metropolitan area and the relationship with land use land cover (LULC) change between 2000 and 2014. The objective is to identify specific regions in Phoenix that have been increasingly heated and cooled to further understand how LULC change influences the SUHI intensity. The data employed include MODerate-resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) 8-day composite June imagery, and classified LULC maps generated using 2000 and 2014 Landsat imagery. Results show that the regions that experienced the most significant LST changes during the study period are primarily on the outskirts of the Phoenix metropolitan area for both daytime and nighttime. The conversion to urban, residential, and impervious surfaces from all other LULC types has been identified as the primary cause of the UHI effect in Phoenix. Vegetation cover has been shown to significantly lower LST for both daytime and nighttime due to its strong cooling effect by producing more latent heat flux and less sensible heat flux. We suggest that urban planners, decision-makers, and city managers formulate new policies and regulations that encourage residential, commercial, and industrial developers to include more vegetation when planning new construction.

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.

Deforestation in Myanmar has recently attracted much attention worldwide. This study examined spatio-temporal patterns of deforestation and forest carbon flux in Myanmar from 2001 to 2010 and environmental impacts at the regional scale using land products of the Moderate Resolution Imaging Spectroradiometer (MODIS). The results suggest that the total deforestation area in Myanmar was 21,178.8 km², with an annual deforestation rate of 0.81%, and that the total forest carbon release was 20.06 million tons, with an annual rate of 0.37%. Mangrove forests had the highest deforestation and carbon release rates, and deciduous forests had both the largest deforestation area and largest amount of carbon release. During the study period, the south and southwestern regions of Myanmar, especially Ayeyarwady and Rakhine, were deforestation hotspots (i.e., the highest deforestation and carbon release rates occurred in these regions). Deforestation caused significant carbon release, reduced evapotranspiration (ET), and increased land surface temperatures (LSTs) in deforested areas in Myanmar during the study period. Constructive policy recommendations are put forward based on these research results.

Land-use mapping is critical for global change research. In Central Arizona, U.S.A., the spatial distribution of land use is important for sustainable land management decisions. The objective of this study was to create a land-use map that serves as a model for the city of Maricopa, an expanding urban region in the Sun Corridor of Arizona. We use object-based image analysis to map six land-use types from ASTER imagery, and then compare this with two per-pixel classifications. Our results show that a single segmentation, combined with intermediary classifications and merging, morphing, and growing image-objects, can lead to an accurate land-use map that is capable of utilizing both spatial and spectral information. We also employ a moving-window diversity assessment to help with analysis and improve post-classification modifications.