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Emerging Computing Trends, Web GIS Tools, and Forecasting Methods for Geospatial Environmental Decision Support in Service of Complex Land Management Challenges
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Emerging Computing Trends, Web GIS Tools, and Forecasting Methods for Geospatial Environmental Decision Support in Service of Complex Land Management Challenges. |
| 개인저자 | Matney, Jason Andrew. |
| 단체저자명 | North Carolina State University. |
| 발행사항 | [S.l.]: North Carolina State University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 137 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-03A. Dissertation Abstract International |
| ISBN | 9781088357583 |
| 학위논문주기 | Thesis (Ph.D.)--North Carolina State University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-03, Section: A.
Advisor: Slocumb, William |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | As global ecological concerns associated with climate change grow increasingly salient, professional conservationists, land managers, and public and private decision makers face increasingly complex responsibilities related to these changes. Tasks such as monitoring large-scale environmental change, responding to more frequent natural disasters, and leveraging decision support tools for managing geospatial information are becoming more important in the careers of land managers. This dissertation is comprised of three manuscripts which explore the present and future of web mapping, the application of a web-based geospatial management solution, and a comparison of time series forecasting methods. The overarching rationale is to provide decision support to land managers to assist them in addressing these grand challenges. The dissertation therefore seeks to contribute to the applied GIScience literature from a land management perspective. The first manuscript explores the state of the current era of web mapping as of 2019. The publication is in preparation for submission to Transactions of the Institute of British Geographers. The text explores how six technologies / configurations / implementations are influencing the trajectory of web mapping applications for land management since 2017. Rather than providing results in the manner of a traditional research paper, the manuscript instead (1) historically situates these 2017-2019 web mapping developments, (2) serves as a broad literature review of the subject, and (3) speculates on future directions into the early 2020s.혻The second manuscript uses the case study of the US National Park Service's Rivers, Trails, and Conservation Assistance program as an example of how a standardized geospatial tool can be deployed within a land management decision support context. This manuscript was published in the Journal of Park and Recreation Administration in 2019. The text elucidates the background, implementation, and evaluation of a web mapping tool as developed and deployed for use by staff based in disparate US National Park Service offices. Results show that while many users found that the online tool helped to improve their access to and management of project data, the tool on the whole required migration to a cloud-based platform (e.g., ArcGIS Online) to resolve serious technical errors. The third manuscript considers the capacity different of time series forecasting methods to provide insight and predictions into US National Park Service visitation and geotagged social media post temporal trends. The manuscript is in preparation for submission to the Journal of Environmental Management. Three forecasting methods are compared to each other (two traditionally statistical, one based on artificial intelligence and machine learning concepts) in order to determine which is most effective based on several performance metrics. Forecasting is described for both social media posts drawn from a web-scraped Flickr dataset, as well as US National Park Service recreation visitation for the 12 most-visited parks from 2007 to 2017 (of those parks located within the contiguous US, except those located in heavily populated areas). The Flickr posts are configured as Photo User Days, and only those posts geotagged within the polygonal boundaries of these parks are considered in the analysis. Results include the recommendation that land managers utilize Facebook Prophet for time series visitation forecasting tasks, based on its relative ease of use and comparable performance to more traditional statistical forecasting methods.혻 |
| 일반주제명 | Recreation. Natural resource management. Remote sensing. Geographic information science. Environmental management. Climate change. |
| 언어 | 영어 |
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