Is All Open Space Created Equal? A Hedonic Application within a Data-Rich GIS Environment

Economic evidence reveals that preserved open space fosters services that are valued by members of society. However, when making the municipal decision to preserve land, communities must decide what type of open space to preserve, and must also deal with entities purchasing land and affecting tax revenues. The United States Fish and Wildlife Service (USFWS) has made efforts in recent years to expand the National Wildlife Refuge (NWR) system. This research seeks to determine if residential property owners value NWRs, and if they value NWRs differently than other types of open space, including conservation land, agricultural land, sports parks, golf courses, and cemeteries. The hedonic method is used to estimate the benefits of each open space type that accrue to surrounding residential property owners. The hedonic models used here explain the sale price of a residential property as a function of numerous land, structure, and neighborhood characteristics, in addition to open space characteristics. The open space characteristics included in this research include measures of continuous distance from each property to the nearest open space of each type, discrete measures of distance to the closest open space of each type, continuous measures of distance to the closest public and private open space, and an index describing the diversity of open space types evaluated at 100 and 1,000 meters around a home. As such, the hedonic method is utilized to estimate implicit prices associated with each of these open space characteristics. The study area for this research is centered on a National Wildlife Refuge in central Middlesex County, Massachusetts called Great Meadows. The area is located approximately 20 miles northwest of Boston and is convenient for investigating the price effects of NWRs because of the abundance of residential properties adjacent to the refuge. The property sales data used in this study consists of residential transactions occurring between January, 1993 and December, 1998. Open space GIs data was obtained from the Massachusetts Office of Geographic and Environmental Information. Results suggest that National Wildlife Refuges are valued by residential property owners. Specifically, a property located 100 meters closer to the Great Meadows NWR than a neighboring property has a price premium of $791. Further, Great Meadows is valued more highly than agricultural land, cemeteries, and conservation land but not valued significantly different than sports fields and golf courses

Toward a user-oriented analytical approach to learning design

The London Pedagogy Planner (LPP) is a prototype for a collaborative online planning and design tool that supports lecturers in developing, analysing and sharing learning designs. The tool is based on a developing model of the components involved in learning design, and the critical relationships between them. As a decision tool, it makes the pedagogical design explicit as an output from the process, capturing it for testing, redesign, reuse and adaptation by the originator, or by others. The aim is to test the extent to which we can engage lecturers in reflecting on learning design, and make them part of the educational community that discovers how best to use Technology Enhanced Learning (TEL). This paper describes the development of LPP, presents pedagogical benefits of visual representations of learning designs, and proposes an analytical approach to learning design based on these visual representations. The analytical approach is illustrated based on an initial evaluation with the lecturers

Towards a user oriented analytical approach to learning design

The London Pedagogy Planner (LPP) is a prototype for a collaborative online planning and design tool that supports lecturers in developing, analysing and sharing learning designs. The tool is based on a developing model of the components involved in learning design and the critical relationships between them. As a decision tool it makes the pedagogical design explicit as an output from the process, capturing it for testing, redesign, reuse and adaptation by the originator, or by others. The aim is to test the extent to which we can engage lecturers in reflecting on learning design, and make them part of the educational community that discovers how best to use technology‐enhanced learning. This paper describes the development of LPP, presents pedagogical benefits of visual representations of learning designs and proposes an analytical approach to learning design based on these visual representations. The analytical approach is illustrated based on an initial evaluation with a small group of lecturers from two partner institutions

Pursuing Antiracist Public Policy Education: An Example Connecting the Racist History of Housing Policy to Contemporary Inequity

We review the antiracism concept and contextualize it in Extension public policy education and the Extension system itself. Despite public policy education having a long history in Extension on a wide variety of issues, missing from this programming is the pursuit of antiracism. As a programmatic example, we review some historical causes of present-day housing inequities and an associated example approach for pursuing antiracism in housing policy education. Finally, we conclude by noting additional opportunities to pursue antiracism in Extension public policy education. In doing so, we emphasize that public policy education cannot be “nonracist” if it is not antiracist

Tuning the emission properties of a fluorescent polymer using a polymer microarray approach - identification of an optothermo responsive polymer

Fluorescent polymer microarrays were prepared using inkjet printing and screened. The fluorescence intensity was found to be tunable by temperature change when the dye was immobilized in identified thermo-responsive polymer beads.</p

Soccer Team Vectors

In this work we present STEVE - Soccer TEam VEctors, a principled approach for learning real valued vectors for soccer teams where similar teams are close to each other in the resulting vector space. STEVE only relies on freely available information about the matches teams played in the past. These vectors can serve as input to various machine learning tasks. Evaluating on the task of team market value estimation, STEVE outperforms all its competitors. Moreover, we use STEVE for similarity search and to rank soccer teams.Comment: 11 pages, 1 figure; This paper was presented at the 6th Workshop on Machine Learning and Data Mining for Sports Analytics at ECML/PKDD 2019, W\"urzburg, Germany, 201