WorldMap – a geospatial framework for collaborative research

Guan, Weihe Wendy; Bol, Peter K.; Lewis, Benjamin; Bertrand, Matthew; Berman, Merrick Lex; Blossom, Jeffrey

doi:10.1080/19475683.2012.668559

Cited by 23 publications

(12 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In Malé, unlike St. Kitts, environmental impacts remain one of the three main driving forces behind migration patterns, especially in respondents with higher levels of education, namely with college diplomas or university degrees [85]. Similar to other literature, our results from Malé show that migration of island populations persists as a main characteristic of island life [50,86,87]. The normality of migration might indicate why Maldivians do not appear to be overly concerned about the potential migration consequences of climate change.…”

Section: Discussionsupporting

confidence: 84%

Local Perceptions of Climate Change Impacts in St. Kitts (Caribbean Sea) and Malé, Maldives (Indian Ocean)

et al. 2018

View full text Add to dashboard Cite

Small Island Developing States (SIDS) are now experiencing the local consequences of a changing climate, environment, and society. Nonetheless, climate change research frequently remains at regional or national levels. Without locally grounded data, islanders’ perceived impacts of the changes might not be considered, thereby causing difficulties when policy and practice responses are implemented without accounting for local understandings. To contribute to addressing this gap, this study examines perceptions of climate change and associated environmental and social changes in two SIDS case studies: St. Kitts in the Caribbean Sea and Malé Atoll, Maldives in the Indian Ocean. Through these two case studies, we assess perceptions of changing social and natural environments through a closed-question, face-to-face survey. Our results suggest that in both island case studies, communities perceive environmental changes to be happening that demand negotiation with the social changes of daily life. Results also suggest that perceived climate change impacts are only part of the equation, as social and economic impacts reveal two case studies of changing island societies. While the geographic context in each case study differs, this study reveals the perceived impacts of climate change and social changes at a local level, providing valuable insights and angles for formulating policies and actions to deal with the myriad of social and environmental changes affecting SIDS.

show abstract

Section: Discussionsupporting

confidence: 84%

Local Perceptions of Climate Change Impacts in St. Kitts (Caribbean Sea) and Malé, Maldives (Indian Ocean)

et al. 2018

View full text Add to dashboard Cite

show abstract

“…With the popularization of the Internet, personal computers, and spatially enabled portable devices such as global positioning system (GPS)-equipped smartphones and personal digital assistants, citizens can now easily share georeferenced observations of the world (e.g., wildlife sightings) via interactive geovisualization interfaces (e.g., Google Maps, Google Earth, and Microsoft Virtual Earth), via social media (e.g., Twitter, Flickr, Instagram), or via citizen science projects (e.g., eBird) (Silvertown 2009, Sullivan et al 2009, Dickinson et al 2012, Guan et al 2012. These technologies have created unprecedented opportunities for citizens to report their observations of the world.…”

Section: Introductionmentioning

confidence: 99%

A citizen data-based approach to predictive mapping of spatial variation of natural phenomena

Zhu

Zhang

Wang

et al. 2015

International Journal of Geographical Information Science

View full text Add to dashboard Cite

The vast accumulation of environmental data and the rapid development of geospatial visualization and analytical techniques make it possible for scientists to solicit information from local citizens to map spatial variation of geographic phenomena. However, data provided by citizens (referred to as citizen data in this article) suffer two limitations for mapping: bias in spatial coverage and imprecision in spatial location. This article presents an approach to minimizing the impacts of these two limitations of citizen data using geospatial analysis techniques. The approach reduces location imprecision by adopting a frequency-sampling strategy to identify representative presence locations from areas over which citizens observed the geographic phenomenon. The approach compensates for the spatial bias by weighting presence locations with cumulative visibility (the frequency at which a given location can be seen by local citizens). As a case study to demonstrate the principle, this approach was applied to map the habitat suitability of the black-and-white snub-nosed monkey (Rhinopithecus bieti) in Yunnan, China. Sightings of R. bieti were elicited from local citizens using a geovisualization platform and then processed with the proposed approach to predict a habitat suitability map. Presence locations of R. bieti recorded by biologists through intensive field tracking were used to validate the predicted habitat suitability map. Validation showed that the continuous Boyce index (B cont (0.1)) calculated on the suitability map was 0.873 (95% CI: [0.810, 0.917]), indicating that the map was highly consistent with the fieldobserved distribution of R. bieti. B cont (0.1) was much lower (0.173) for the suitability map predicted based on citizen data when location imprecision was not reduced and even lower (−0.048) when there was no compensation for spatial bias. This indicates that the proposed approach effectively minimized the impacts of location imprecision and spatial bias in citizen data and therefore effectively improved the quality of mapped spatial variation using citizen data. It further implies that, with the application of geospatial analysis techniques to properly account for limitations in citizen data, valuable information embedded in such data can be extracted and used for scientific mapping.

show abstract

“…Harvard WorldMap (http://worldmap.harvard.edu/) is an open source SDI and Geospatial Content Management System (GeoCMS) platform developed by the Centre for Geographic Analysis (CGA) to lower the barrier for scholars who wish to explore, visualize, edit and publish geospatial information (Guan et al, 2012). Registered users are able to upload geospatial content, in the form of vector or raster datasets (layers), and combine them with existing layers to create maps.…”

Section: Introductionmentioning

confidence: 99%

Enhancing discovery in spatial data infrastructures using a search engine

Corti

Kralidis

Lewis

2018

PeerJ Computer Science

View full text Add to dashboard Cite

A spatial data infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide an efficient and flexible way to use spatial information. One of the key software components of an SDI is the catalogue service which is needed to discover, query and manage the metadata. Catalogue services in an SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard which defines common interfaces for accessing the metadata information. A search engine is a software system capable of supporting fast and reliable search, which may use 'any means necessary' to get users to the resources they need quickly and efficiently. These techniques may include full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting, recommendations and many others. In this paper we present an example of a search engine being added to an SDI to improve search against large collections of geospatial datasets. The Centre for Geographic Analysis (CGA) at Harvard University re-engineered the search component of its public domain SDI (Harvard WorldMap) which is based on the GeoNode platform. A search engine was added to the SDI stack to enhance the CSW catalogue discovery abilities. It is now possible to discover spatial datasets from metadata by using the standard search operations of the catalogue and to take advantage of the new abilities of the search engine, to return relevant and reliable content to SDI users.

show abstract

WorldMap – a geospatial framework for collaborative research

Cited by 23 publications

References 4 publications

Local Perceptions of Climate Change Impacts in St. Kitts (Caribbean Sea) and Malé, Maldives (Indian Ocean)

Local Perceptions of Climate Change Impacts in St. Kitts (Caribbean Sea) and Malé, Maldives (Indian Ocean)

A citizen data-based approach to predictive mapping of spatial variation of natural phenomena

Enhancing discovery in spatial data infrastructures using a search engine

Contact Info

Product

Resources

About