5. Roles and Uses of Models and Geographic Information Systems in Natural Resource Management

2002 ◽  
pp. 133-156
Keyword(s):  
Information Systems ◽  
Resource Management ◽  
Geographic Information Systems ◽  
Natural Resource Management ◽  
Natural Resource ◽  
Geographic Information

Geographic Information System for Natural Resource Management of Pakistan

2006 ◽  
Vol 23 ◽  
Author(s):  
Hammad Hassan Tariq ◽  
Zia Ul Hasan Shah ◽  
Ghulam Mujtaba ◽  
Shahina Tariq ◽  
Mohammad Zafar ◽  
...  
Keyword(s):  
Information System ◽  
Resource Management ◽  
Geographic Information System ◽  
Natural Resource Management ◽  
Natural Resource ◽  
Geographic Information

scholarly journals Integrating Drones into a Natural-Resource Curriculum at Stephen F. Austin State University

2019 ◽  
Vol 117 (4) ◽  
pp. 398-405
Author(s):  
Daniel R Unger ◽  
David L Kulhavy ◽  
I-Kuai Hung ◽  
Yanli Zhang ◽  
Pat Stephens Williams
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Natural Resource ◽  
Geographic Information ◽  
Academic Experience ◽  
State University ◽  
Decisionmaking Process

AbstractFaculty within the Arthur Temple College of Forestry and Agriculture (ATCOFA) at Stephen F. Austin State University in Nacogdoches, Texas are integrating drone technology into their curriculum to introduce students to the use of high-end technology within a natural-resource-based decisionmaking process. Drones are currently being integrated across the curriculum within ATCOFA, including 10 geographic information systems (GIS) courses for students pursuing the B.S. in Spatial Science and within six non-GIS specific courses for students pursuing the B.S. in Forestry. Results indicate that drone technology can be an effective tool in enhancing a student’s academic experience and provides students with a skill set required for future natural-resource professionals.

scholarly journals Privacy-Aware Visualization of Volunteered Geographic Information (VGI) to Analyze Spatial Activity: A Benchmark Implementation

2020 ◽  
Vol 9 (10) ◽  
pp. 607 ◽  
Author(s):  
Alexander Dunkel ◽  
Marc Löchner ◽  
Dirk Burghardt
Keyword(s):  
Resource Management ◽  
Natural Resource Management ◽  
Natural Resource ◽  
Volunteered Geographic Information ◽  
Well Being ◽  
Geographic Information ◽  
User Privacy ◽  
Creative Commons ◽  
Surrounding Environment ◽  
Privacy Risks

Through volunteering data, people can help assess information on various aspects of their surrounding environment. Particularly in natural resource management, Volunteered Geographic Information (VGI) is increasingly recognized as a significant resource, for example, supporting visitation pattern analysis to evaluate collective values and improve natural well-being. In recent years, however, user privacy has become an increasingly important consideration. Potential conflicts often emerge from the fact that VGI can be re-used in contexts not originally considered by volunteers. Addressing these privacy conflicts is particularly problematic in natural resource management, where visualizations are often explorative, with multifaceted and sometimes initially unknown sets of analysis outcomes. In this paper, we present an integrated and component-based approach to privacy-aware visualization of VGI, specifically suited for application to natural resource management. As a key component, HyperLogLog (HLL)—a data abstraction format—is used to allow estimation of results, instead of more accurate measurements. While HLL alone cannot preserve privacy, it can be combined with existing approaches to improve privacy while, at the same time, maintaining some flexibility of analysis. Together, these components make it possible to gradually reduce privacy risks for volunteers at various steps of the analytical process. A specific use case demonstration is provided, based on a global, publicly-available dataset that contains 100 million photos shared by 581,099 users under Creative Commons licenses. Both the data processing pipeline and resulting dataset are made available, allowing transparent benchmarking of the privacy–utility tradeoffs.

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