The Spatial Historian: Creating a Spatially Aware Historical Research System

The intent of this study is to design a geospatial information system capable of facilitating the extraction and analysis of the fragmentary snapshots of history contained in hand-written historical documents. This customized system necessarily bypasses off-the-shelf GIS in order to support these unstructured primary historical research materials and bring long dormant spatial stories previously hidden in archives, libraries, and other documentary storage locations to life. The software platform discussed here integrates the tasks of information extraction, data management, and analysis while simultaneously giving primary emphasis to supporting the spatial and humanistic analysis and interpretation of the data contents. The premise of this research study is that by integrating the collection of data, the extraction of content, and the analysis of information from what has traditionally been post-data collection analysis and research process, more efficient processing and more effective historical research can be achieved

Agricultural land systems : modelling past, present and future regional dynamics

This thesis arises from the understanding of how the integration of concepts, tools, techniques, and methods from geographic information science (GIS) can provide a formalised knowledge base for agricultural land systems in response to future agricultural and food system challenges. To that end, this thesis focuses on understanding the potential application of GIS-based approaches and available spatial data sources for modelling regional agricultural land-use and production dynamics in Portugal. The specific objectives of this thesis are addressed in seven chapters in Parts II through V, each corresponding to one scientific article that was either published or is being considered for publication in peer-reviewed international scientific journals. In Part II, Chapter 2 summarises the body of knowledge and provides the context for the contribution of this thesis within the scientific domain of agricultural land systems. In Part III, Chapters 3 and 4 explore remotely sensed and Volunteered Geographic Information (VGI) data, multitemporal and multisensory approaches, and a variety of statistical methods for mapping, quantifying, and assessing regional agricultural land dynamics in the Beja district. In Part IV, Chapters 5–7 explore the CA-Markov model, Markov chain model, machine learning, and model-agnostic approach, as well as a set of spatial metrics and statistical methods for modelling the factors and spatiotemporal changes of agricultural land use in the Beja district. In Part V, Chapter 8 explores an area-weighting GIS-based technique, a spatiotemporal data cube, and statistical methods to model the spatial distribution across time for regional agricultural production in Portugal. The case studies in the thesis contribute practical and theoretical knowledge by demonstrating the strengths and limitations of several GIS-based approaches. Together, the case studies demonstrate the underlying principles that underpin each approach in a way that allows us to infer their potentiality and appropriateness for modelling regional agricultural land-use and production dynamics, stimulating further research along this line. Generally, this thesis partly reflects the state-of-art of land-use modelling and contribute significantly to the introduction of advances in agricultural system modelling research and land-system science

Big Data in Bioeconomy

This edited open access book presents the comprehensive outcome of The European DataBio Project, which examined new data-driven methods to shape a bioeconomy. These methods are used to develop new and sustainable ways to use forest, farm and fishery resources. As a European initiative, the goal is to use these new findings to support decision-makers and producers – meaning farmers, land and forest owners and fishermen. With their 27 pilot projects from 17 countries, the authors examine important sectors and highlight examples where modern data-driven methods were used to increase sustainability. How can farmers, foresters or fishermen use these insights in their daily lives? The authors answer this and other questions for our readers. The first four parts of this book give an overview of the big data technologies relevant for optimal raw material gathering. The next three parts put these technologies into perspective, by showing useable applications from farming, forestry and fishery. The final part of this book gives a summary and a view on the future. With its broad outlook and variety of topics, this book is an enrichment for students and scientists in bioeconomy, biodiversity and renewable resources

The Nexus Between Security Sector Governance/Reform and Sustainable Development Goal-16

This Security Sector Reform (SSR) Paper offers a universal and analytical perspective on the linkages between Security Sector Governance (SSG)/SSR (SSG/R) and Sustainable Development Goal-16 (SDG-16), focusing on conflict and post-conflict settings as well as transitional and consolidated democracies. Against the background of development and security literatures traditionally maintaining separate and compartmentalized presence in both academic and policymaking circles, it maintains that the contemporary security- and development-related challenges are inextricably linked, requiring effective measures with an accurate understanding of the nature of these challenges. In that sense, SDG-16 is surely a good step in the right direction. After comparing and contrasting SSG/R and SDG-16, this SSR Paper argues that human security lies at the heart of the nexus between the 2030 Agenda of the United Nations (UN) and SSG/R. To do so, it first provides a brief overview of the scholarly and policymaking literature on the development-security nexus to set the background for the adoption of The Agenda 2030. Next, it reviews the literature on SSG/R and SDGs, and how each concept evolved over time. It then identifies the puzzle this study seeks to address by comparing and contrasting SSG/R with SDG-16. After making a case that human security lies at the heart of the nexus between the UN’s 2030 Agenda and SSG/R, this book analyses the strengths and weaknesses of human security as a bridge between SSG/R and SDG-16 and makes policy recommendations on how SSG/R, bolstered by human security, may help achieve better results on the SDG-16 targets. It specifically emphasizes the importance of transparency, oversight, and accountability on the one hand, and participative approach and local ownership on the other. It concludes by arguing that a simultaneous emphasis on security and development is sorely needed for addressing the issues under the purview of SDG-16

Data access and visualization benefits from implementation of a hydrologic information system

In 2010, the National Science Foundation (NSF) implemented new guidelines for all scientists applying for grants. A Data Management Plan (DMP) is now required for all proposals in which data are created or gathered while working under the grant. Several organizations have produced templates and applications to assist with the construction of DMPs. The data plans provide a good overview of data processing and storage but do not provide any guidance for managing data during the research process. Large temporal hydrologic data sets can provide a rich insight to complex hydrologic and ecological systems. Complications arise when attempting to query and present the data in ways that are useful for exploring and validating research hypotheses. Common tools, such as Excel or Matlab, may be helpful if you know the exact sequence of data you want to analyze. Frequently, this is not the case. Looking at long term trends, adding and removing additional variables, or comparing local results to external national datasets are difficult or impossible with these tools. To overcome the limitations of current data management methods, a Consortium of Universities for the Advancement of Hydrologic Science Inc. - Hydrologic Information System (CUAHSI-HIS) server was deployed in collaboration with Earth Data Analysis Center (EDAC) and the New Mexico Experimental Program to Stimulate Competitive Research (NMEPSCoR). Data products on the server are stored in a relational database using WaterML, an XML based language introducing standardization to the hydrologic community and facilitating distribution and aggregation of hydrologic data. Four project types from different agencies have been selected to explore the process of obtaining and ingesting data into an HIS. Three of the projects are university based with different stakeholders and the fourth is a state funded project carried out by a contractor. Tools developed by CUAHSI for ingesting measurements into the database made processing the raw data straightforward. After the data were formatted properly, automated processes allowed millions of measurements to migrate from Excel files into the HIS. Aggregating the data and metadata without support from the principal investigator proved difficult. Deciphering the provenance of derived data proved exceptionally difficult from a data manager perspective with little experience in specialized disciplines. Datasets that previously required hours to download, aggregate, and visualize are can now be processed in minutes. Repetitive analysis tasks can be automated within the HIS, integrating local regional, and national datasets by spatial and temporal extent and delivered to the research team in a variety of formats. The CUAHSI-HIS components make data discovery and analysis streamlined in addition to satisfying the NSF DMP requirements

Proceedings of the 3rd Open Source Geospatial Research & Education Symposium OGRS 2014

The third Open Source Geospatial Research & Education Symposium (OGRS) was held in Helsinki, Finland, on 10 to 13 June 2014. The symposium was hosted and organized by the Department of Civil and Environmental Engineering, Aalto University School of Engineering, in partnership with the OGRS Community, on the Espoo campus of Aalto University. These proceedings contain the 20 papers presented at the symposium. OGRS is a meeting dedicated to exchanging ideas in and results from the development and use of open source geospatial software in both research and education.  The symposium offers several opportunities for discussing, learning, and presenting results, principles, methods and practices while supporting a primary theme: how to carry out research and educate academic students using, contributing to, and launching open source geospatial initiatives. Participating in open source initiatives can potentially boost innovation as a value creating process requiring joint collaborations between academia, foundations, associations, developer communities and industry. Additionally, open source software can improve the efficiency and impact of university education by introducing open and freely usable tools and research results to students, and encouraging them to get involved in projects. This may eventually lead to new community projects and businesses. The symposium contributes to the validation of the open source model in research and education in geoinformatics

Geoinformatics in Citizen Science

The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science