RESILIENCE ACADEMY STUDENT INTERNSHIP MODEL AS AN INNOVATIVE WAY TO ENHANCE GEOSPATIALLY LITERATE FUTURE WORK FORCE IN AFRICA

This paper is based on the experiences from Resilience Academy project in Dar es Salaam, Tanzania, where students’ are engaged to a mass-internships for a period of 8-12 weeks. Student internship model of the Resilience Academy is designed to work with the local organisations to conduct geospatial data collection campaigns based on the use of various open-source data and tools combined with community mapping and digital online working. Simultaneously, students’ exposure to practical training during the internship provides them with relevant applied geospatial skills, which increase their future employment opportunities and participation in informed decision-making.

Toward Crowd-sourced Soundscape Monitoring in Protected Areas: Integrating Sound Dominance and Triggers to Facilitate Proactive Management

This research expanded on prior use of visitor perception data to inform potential social indicators of soundscape quality, by integrating existing urban-context soundscapes work, and the emerging use of triggers to help managers identify concerns before they reach the threshold level. Along with existing measures of sound appeal and acceptability, sound dominance helped provide a sense of how the extent of particular sounds influenced visitor experiences and a desire to visit more. Geospatial data collection for 899 visitors and eight sites within the Coyhaique National Reserve (CNR) in southern Chile during the summer high visitation season of 2019, allowed researchers to examine perceptual similarities and differences, facilitating an evaluation of new perceptual variables for soundscape monitoring. Correlation analyses identified informative relationships between the dominance (sound duration and foreground/background placement) of natural and anthropogenic sounds, and overall soundscape ratings. The duration of natural sounds was positively correlated with soundscape-level ratings, while the duration of anthropogenic sounds was negatively correlated with these ratings. Unique trends and relationships were identified across specific sites, demonstrating the value of adding measures of perceived sound dominance to soundscape monitoring processes. Observed Protected Area (PA) visitor enthusiasm for sounds and soundscapes suggests potential for crowd-sourced citizen science-based methods that could be done voluntarily and regularly using simple and accessible applications and technologies.

Consortial Geospatial Data Collection: Toward Standards and Processes for Shared GeoBlacklight Metadata

Consortial geospatial data communities, such as the OpenGeoPortal federation and the GeoBlacklight initiative, facilitate contextualized discovery and promote metadata sharing to disperse hosting and preservation responsibilities across institutions. However, the challenges of communal metadata are manifold; they include proliferating standards, varying levels of completeness, mutable technology infrastructures, and uneven availability of human labor. Drawing from literature on metadata quality control, we outline a procedure for “scoring” GeoBlacklight records to establish a Domain Specific Language for metadata best practices. We propose strategies for authorship and management conducive to functionally interoperable geospatial metadata, that is versioned and enhanceable by the collective.

Geospatial Data Analysis: A Review of Theory and Methods

A vast amount of data is generated and collected every moment and often, data has a spatial and/or temporal aspect. This increasing data generation and collection is resulting in increasing volume and varying formats of data being collected and the geospatial data collection is no exception. This posses challenges in storing, processing, analyzing and visualizing the geospatial data. This paper discusses the big data paradigm of the geospatial data and presents a taxonomy for analysis of the geospatial data. The existing literature is studied and discussed based on the proposed taxonomy for analysis of geospatial data.