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Purpose
The purpose of this project is to provide an account of the student experience at a higher education institution known for its holistic approach to sustainability education.


Design/methodology/approach
A qualitative study was conducted at Green Mountain College (GMC), an environmental liberal arts school in Poultney, VT; 55 students participated in focus group interviews.


Findings
Students articulate that the most valuable gains that manifest at GMA are a variety of new capacities for science literacy, anthropological appreciation, the triple bottom line, a sense of place, systems, empathic decision-making and reasoning, interdisciplinary collaboration, and practical techniques supporting self-sufficiency. Prompting these emergent outcomes was a philosophy of practice at Green Mountain College, which included place-based techniques, empowerment, personalization, community ecology and charting polarity. Many students described their seeming metamorphosis as uncomfortable, and some felt isolated from the outside paradigm.


Research limitations/implications
A key implication of the study's findings is that in a holistic setting, the line between the informal and formal curriculum are significantly blurred and what is implicitly communicated through university practices and values is what most transforms the students' explicit understanding of sustainability.


Practical implications
Sustainability education is far more than technique, far more than what a lone instructor can manifest in students. While the persistence of individual faculty members is important, this evidence suggests that the fertile conditions for transformation may be more fruitful when faculty members work together with a collective sense of responsibility and a well-articulated paradigm.


Originality/value
The advantage of the present study is that it examines the perceived impact of a focus on sustainability across curricula and school by considering the educational environment as a whole. The experiences of students from many different majors who are involved in a holistic, sustainability-infused curriculum at a university with a history of successful post-graduation job placements in the sustainability field are explored here.

Abstract. We present new radar-based techniques for efficient identification of surface changes generated by lava and pyroclastic flows, and apply these to the 1996 eruption of Manam Volcano, Papua New Guinea. Polarimetric L- and P-band airborne synthetic aperture radar (SAR) data, along with a C-band DEM, were acquired over the volcano on 17 November 1996 during a major eruption sequence. The L-band data are analyzed for dominant scattering mechanisms on a per pixel basis using radar target decomposition techniques. A classification method is presented, and when applied to the L-band polarimetry, it readily distinguishes bare surfaces from forest cover over Manam volcano. In particular, the classification scheme identifies a post-1992 lava flow in NE Valley of Manam Island as a mainly bare surface and the underlying 1992 flow units as mainly vegetated surfaces. The Smithsonian's Global Volcanism Network reports allow us to speculate whether the bare surface is a flow dating from October or November in the early part of the late-1996 eruption sequence. This work shows that fully polarimetric SAR is sensitive to scattering mechanism changes caused by volcanic resurfacing processes such as lava and pyroclastic flows. By extension, this technique should also prove useful in mapping debris flows, ash deposits and volcanic landslides associated with major eruptions.

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record. ; Skyline queries identify skyline points, the minimal set of data points that dominate all other data points in a large dataset. The main challenge with skyline queries is executing the skyline query in the shortest possible time. To address and solve skyline query performance issues, we propose a decision tree-based method known as the decision tree-based comparator (DC). This method minimizes unnecessary dominance tests (i.e., pairwise comparisons) by constructing a decision tree based on the dominance testing. DC uses dominance relations that can be obtained from the decision rules of the decision tree to determine incomparability between data points. DC can also be easily applied to improve the performance of various existing skyline query methods. After describing the theoretical background of DC and applying it to existing skyline queries, we present the results of various experiments showing that DC can improve skyline query performance by up to 23.15 times. ; Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) ; Industrial Strategic Technology Development Program funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea).