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Volunteer science programs are designed to increase public understanding and appreciation of science by creating opportunities for the public to engage in science. This research assesses the impact of Map of Life-Denali on its volunteers. This program calls on park visitors to record wildlife observations while they visit Denali National Park and Preserve, Alaska. This paper focuses specifically on place attachment and learning outcomes for the volunteers, who are mainly tourists. Results from volunteer surveys show positive volunteer outcomes of the program, with implications for the continuation of this program and the institution of others.

The implications of digital technologies for planning practice are receiving renewed interest in the wake of ever-improving capabilities in Big Data and artificial intelligence, as well as the rapid uptake of new technologies that allowed planners to work remotely during the COVID-19 pandemic. Despite this interest, there has been little cross-country comparative research regarding the adoption of technology within the planning profession and even less that addresses planners' expectations and desires for future digital tools. We undertook a multinational online survey of planners in the United States, Canada, the United Kingdom, Australia, and New Zealand to gain a comprehensive understanding of current and expected future use of data and software in planning practice. Although the current use of data-intensive digital tools was limited, we found widespread expectations of change across the planning profession. Remarkable similarities were observed across the countries surveyed. The biggest differences in tech use were among planners undertaking strategic, specialist, and regulatory roles. Planning organizations around the world should prepare for a new wave of digital change as many technical obstacles that previously hindered the rapid exchange and analysis of vast amounts of data have now been overcome. Continued development of digital skills among planners is important but should be paired with career pathways for digital specialists within the profession. Planners should not complacently assume that adopting digital technologies will automatically lead to more effective and equitable planning outcomes. They should use digital processes to actively address biases in the underlying planning system. [ABSTRACT FROM AUTHOR]

Community resilience refers to the ability for a geographic area to respond and adapt to acute shocks and long-term stresses. Geography research is well positioned to examine how communities can adapt to the compounding effects of climate change. Our work aims to analyze the factors that influence residential electricity in the context of increasing urban temperatures in Maricopa County, Arizona, coupled with the COVID-19 pandemic. Using census tracts as our basis for analysis, we quantified factors that influence electricity use related to neighborhood characteristics, home structures, social situations, pricing policies, and work-from-home estimates. Our findings suggest that the structure of the home (e.g., number of rooms and house size) influences the variation in residential electricity use, whereas trees and small-area temperatures were not factors. We then compared above-median-income census tracts to those that were below the median income. We found fewer factors influenced electricity use in the lower income census tracts and that they were also related mostly to the home structure. Our analysis did not reveal that working from home was significant, but we did find that the average household size was significant and that the amount of influence increased from 2019 to 2020, suggesting that the stay-at-home policies from the pandemic did affect electricity use. As we consider and implement work-from-home strategies, families need to recognize that the home structure plays a crucial role in determining electricity usage. [ABSTRACT FROM AUTHOR]

Two experiments investigating the benefit of computer-based applications in geography education are presented. The computer-based methods employ concepts of visualization, including animation and interactivity, to facilitate active learning. These computer-based methods are compared with physical (i.e. tangible) models, which themselves can be considered active learning tools. Thus, this report compares a pair of learning strategies using interactive external cognitive tools (one computer-based and one physical), rather than more typical studies which compare an approach using such interactive tools with an approach using more traditional lecture-based presentations. Results confirm existing findings that computer-based approaches are appealing to students but are not, by themselves, significantly beneficial in enabling understanding of complex concepts. Questions used in pre- and post-test for projection understanding are appended. (Contains 9 tables, 4 figures and 5 notes.)

In less‐developed countries, the lack of granular data limits the researcher's ability to study the spatial interaction of different factors on the COVID‐19 pandemic. This study designs a novel database to examine the spatial effects of demographic and population health factors on COVID‐19 prevalence across 640 districts in India. The goal is to provide a robust understanding of how spatial associations and the interconnections between places influence disease spread. In addition to the linear Ordinary Least Square regression model, three spatial regression models—Spatial Lag Model, Spatial Error Model, and Geographically Weighted Regression are employed to study and compare the variables explanatory power in shaping geographic variations in the COVID‐19 prevalence. We found that the local GWR model is more robust and effective at predicting spatial relationships. The findings indicate that among the demographic factors, a high share of the population living in slums is positively associated with a higher incidence of COVID‐19 across districts. The spatial variations in COVID‐19 deaths were explained by obesity and high blood sugar, indicating a strong association between pre‐existing health conditions and COVID‐19 fatalities. The study brings forth the critical factors that expose the poor and vulnerable populations to severe public health risks and highlight the application of geographical analysis vis‐a‐vis spatial regression models to help explain those associations. [ABSTRACT FROM AUTHOR]

Compares student reactions to traditional teaching methods and an approach where computer-based tools (GEODe CD-ROM and GIS-based exercises) were either integrated with or replaced the traditional methods. Reveals that the students found both of these tools valuable forms of instruction when used in combination with the traditional methods. (CMK)

In this commentary we reflect on the potential and power of geographical analysis, as a set of methods, theoretical approaches, and perspectives, to increase our understanding of how space and place matter for all. We emphasize key aspects of the field, including accessibility, urban change, and spatial interaction and behavior, providing a high‐level research agenda that indicates a variety of gaps and routes for future research that will not only lead to more equitable and aware solutions to local and global challenges, but also innovative and novel research methods, concepts, and data. We close with a set of representation and inclusion challenges to our discipline, researchers, and publication outlets. [ABSTRACT FROM AUTHOR]

In citizen science programs, the concept of "participant" is often used as a catch-all without considering how different participants (e.g., young, old, wealthy, poor, differentlyabled, local inhabitants, and visitors) affect scientific outcomes of citizen science programs (e.g., the data collection, data analysis, publications, etc.). This research advances the understanding of tourist participants' ability to produce data comparable to participants who live near the study area. To examine data collected by tourist participants, we performed a case study on wildlife observation data collected through the Map of Life-Denali program in Denali National Park and Preserve in Alaska, USA. The species observation data collected by tourists and Alaska Residents were compared visually using heatmaps and statistically with the Ripley's K function variation, the L function. Results from the analysis show that the tourist and resident data have similar point patterns for the three species we compared, Ursus arctos (Grizzly Bear), Rangifer tarandus (Caribou), and Alces alces (Moose). Our results indicate that tourists can be effective citizen science participants. And show the potential for leveraging this large pool of untapped participants in popular tourist destinations such as U.S. National Parks. [ABSTRACT FROM AUTHOR]

The fusion of optical imagery with radar data can provide more accurate land cover change analysis of deforestation and tree-based agriculture. Radar data is limited temporally with most geographic areas not covered prior to 2007. This paper presents a new methodology to classify land cover change related to oil palm expansion that takes historic data limitations into account. Our approach utilizes Hansen's Global Forest Cover data, optical imagery, and texture information, to extract land cover information in Sumatra and Western Malaysia, where historical data is absent. Our method demonstrates how to accurately classify oil palm without radar data with overall accuracies for optical only experiments within 4.4% of optical plus radar classifications. Our results show agricultural land use was the primary driver of land cover change with the largest increase due to oil palm expansion (6.1%). Better estimations of oil palm expansion could be used in sustainable land management policies. [ABSTRACT FROM AUTHOR]

Geodesign is a technology-supported planning approach that combines community collaboration and engagement with geospatial analysis to make land use decisions quickly. In this study we tested the role of Geodesign in improving the quality of local plans through community participation and collaborative decision making supported by geospatial analysis. Our research evaluates Geodesign as a tool and process in establishing community engagement in planning decisions by applying and analyzing Geodesign in two Navajo Nation communities in Arizona to use scientific and community knowledge to make consensus-based decisions for land use planning. There are three critical components to this analysis. First, we evaluate the use of Geodesign as a plan-making tool. Second, we examine how Geodesign can be inclusionary for planning using Arnstein's ladder of citizen participation with marginalized American Indian communities. Finally, we look at the planner's role and required planning expertise in developing successful Geodesign plans. We conclude that Geodesign can empower historically marginalized Indigenous communities to make community-based land use plans that leverage local knowledge/values and geospatial analysis. Planners can use Geodesign approaches to collaborate and guide marginalized communities to engage in the planning process and incorporate diverse perspectives and cultural values in decision making. A planner should judiciously apply their expertise in their role as a planning facilitator, trainer, and knowledge resource. Using geospatial data and community engagement, Geodesign produces community-based land use plans. [ABSTRACT FROM AUTHOR]

Map algebras are used for the manipulation of spatial data and form the basis for many types of spatial analyses and modeling efforts. The most basic form of a map algebra applies the same function (e.g., addition, subtraction) across the study area. To account for local variation of modeling parameters, we present a spatially dynamic map algebra to demonstrate the need for and utility of algebraic functions where the function is determined based on a specific and relative location. The need for such an algebra comes from the growth of complex models where the values of variables or parameters are not fixed across space. Locally derived parameters are not new, as shown by geographically weighted regression. This type of algebra is needed in cases of complex models, such as those found in flow networks, where network dynamics vary across space. This includes hydrologic processes, movement of people and goods, and the transmission of ideas. We test the approach on a case study of nitrogen flow in the Niantic River watershed, Connecticut. Findings show that the results from a spatially dynamic map algebra can differ from a fixed function. Fixed functions can result in model outputs that under‐ or overestimate by up to 50%. [ABSTRACT FROM AUTHOR]

Problem, research strategy, and findings: Cities across the United States must have reliable and consistent water supplies to support public health, promote economic growth, and protect the environment. The way we build and design cities influences water consumption patterns; however, the most significant factors of the built environment and their associations with water use are not well explored. In this study we seek to reveal the ways in which characteristics of the built environment influence urban water use. We analyze spatially detailed data sets of water use and the built environment in four different cities in the western United States. Our findings indicate the built environment in these cities has a substantial influence on single-family residential water use. Specifically, we find that vegetated land cover, housing density, and lot size are influential determinants of water use. However, we did find variation in the strength and significance of these variables between the cities, and there remains a need for city-specific analyses. Takeaway for practice: The results indicate even small changes to design and permitting for single-family residential properties can produce substantial cumulative water savings for cities. Based on our findings, we propose planning and design strategies such as form-based codes, zoning, and municipal ordinances to help growing cities reduce their water use. We present estimates of the water conservation impacts these strategies might achieve and provide specific examples of planning documents, municipal ordinances, and land use plans some cities are already using to reduce their water use. Overall, our study provides empirical evidence to further support integrating land use planning and water management. [ABSTRACT FROM AUTHOR]

This article presents a new methodology for data fitness-for-use assessment. Most current measures of data quality rely on metadata and other data producer-derived information. This creates a void of options for a user-driven assessment of data quality when metadata are sparse or unavailable, as is often the case with citizen science and volunteered geographic information. This article puts forward data fitness-for-use (DaFFU), a method that can be adapted for a wide range of data uses. Using the mathematical framework of multiple criteria decision making (MCDM), we create a method to select the best data set from multiple options using a select set of user criteria. The DaFFU methodology is demonstrated with both a simple exemplar and a detailed case study for watershed management. The simple exemplar illustrates how varying parameters and weights influence the outcome. The case study on watershed management considers four possible data sets and six data quality criteria for wetland delineation and an application toward watershed nitrogen retention, each of which has a claim on being of the “best” quality, depending on which data quality aspect the user evaluates. The DaFFU methodology allows the user to consider these data in terms of how they will be used and to use selected data quality measures. Case study results show this methodology is a robust and flexible approach to quantitatively assessing multiple data sets in terms of their intended use. [ABSTRACT FROM AUTHOR]

Shade provided by trees, shrubs and other vegetation serves as a natural umbrella to mitigate insolation absorbed by features of the urban environment, especially building structures. For a desert community, tree shade is a valuable asset, contributing to energy conservation efforts, improving home values, enabling cost savings, and promoting enhanced health and well-being. Therefore, maximizing tree shade coverage is an important component in creating an eco-friendly and sustainable urban environment. Strategic placement of trees enhances tree shade coverage of buildings. This paper details an optimization method to simultaneously maximize tree shade coverage on building facades and open structures and to minimize shade coverage on building rooftops in a 3-dimensional environment. This method integrates geographic information systems and spatial optimization approaches for placing trees that provide the greatest potential benefit to a building. A residential area in Tempe, Arizona is utilized to demonstrate the capabilities of the method. The optimization results show that two trees can provide up to 22.20 m 2 shade coverage at 12:00 across a 54 m 2 south-facing facade. This research offers a method to help homeowners, urban planners, and policy makers to quantitatively evaluate shade coverage from trees for building structures in a residential environment. [ABSTRACT FROM AUTHOR]