Overview of the third Special Section of papers from the 10 th Southern Forestry and Natural Resource Management GIS Conference

Pete Bettinger, Krista Merry

Abstract


This is the third Special Section of papers from the 10 th Southern Forestry and Natural Resource Management GIS Conference (SOFOR GIS). The conference was held nearly two years ago in Athens, Georgia (USA). In this Special Section resides two papers that have passed the peer review process. One paper consists of a geographical analysis of the meandering of the Congaree River in South Carolina over the last 130 years. The second paper consists of a geographical analysis of the distribution of an invasive plant species, multiflora rose (Rosa multiflora Thunb.) in the Midwestern United States. Each of these research papers has undergone peer review by respected experts in associated fields.

Keywords


Symposium proceedings, geographic information systems, spatial information technologies, mapping technologies, SOFOR GIS

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References


Bettinger, P., K. Merry, and C. Cieszewski. 2016. The importance of mapping technology knowledge and skills for students seeking entry-level forestry positions: Evidence from job advertisements. Mathematical and Computational Forestry & Natural-Resource Sciences. 8(1): 14-24.

Crosby, M.K., and A.B. Self. 2016. Spatial assessment of meadow vole herbivory on a replanted field in Mississippi. Mathematical and Computational Forestry & Natural-Resource Sciences. 8(2): 18-24.

Kauffman, J.S., and S.P. Prisley. 2016. Automated estimation of forest stand age using Vegetation Change Tracker and machine learning. Mathematical and Computational Forestry & Natural-Resource Sciences. 8(1): 4-13.

Williams, T.M., D.C. Shelley, and B. Song. 2017. GIS analysis of historical maps: A case study from an 1885 survey of the Congaree River. Mathematical and Computational Forestry & Natural-Resource Sciences. 9(2): xx-xx.

Yu, W., Z. Fan, and W.K. Moser. 2017. Incorporating a local-statistics-based spatial weight matrix into a spatial regression model to predict the distribution of invasive Rosa multiflora in the Upper Midwest forestlands. Mathematical and Computational Forestry & Natural-Resource Sciences. 9(2): xx-xx.


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