Research Papers

Monitoring oak-hickory forest change during an unprecedented red oak borer outbreak in the Ozark Mountains: 1990 to 2006

[+] Author Affiliations
Joshua S. Jones, Fred M. Stephen

University of Arkansas, Department of Entomology, Fayetteville, Arkansas 72701

Jason A. Tullis

University of Arkansas, Department of Geosciences and Center for Advanced Spatial Technologies, Fayetteville, Arkansas 72701

Laurel J. Haavik

University of Arkansas, Department of Entomology, Fayetteville, Arkansas 72701

Great Lakes Forestry Centre, 1219 Queen Street East, Sault Ste. Marie, Ontario, P6A 2E5 Canada

James M. Guldin

USDA Forest Service Southern Research Station, 100 Reserve Street, Hot Springs, Arkansas 71902

J. Appl. Remote Sens. 8(1), 083687 (Jan 23, 2014). doi:10.1117/1.JRS.8.083687
History: Received April 26, 2013; Revised October 29, 2013; Accepted December 12, 2013
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Abstract.  Upland oak-hickory forests in Arkansas, Missouri, and Oklahoma experienced oak decline in the late 1990s and early 2000s during an unprecedented outbreak of a native beetle, the red oak borer (ROB), Enaphalodes rufulus (Haldeman). Although remote sensing supports frequent monitoring of continuously changing forests, comparable in situ observations are critical for developing an understanding of past and potential ROB damage in the Ozark Mountains. We categorized forest change using a normalized difference water index (NDWI) applied to multitemporal Landsat TM and ETM+ imagery (1990, 2001, and 2006). Levels of decline or growth were categorized using simple statistical thresholds of change in the NDWI over time. Corresponding decline and growth areas were then observed in situ where tree diameter, age, crown condition, and species composition were measured within variable radius plots. Using a machine learning decision tree classifier, remote sensing-derived decline and growth was characterized in terms of in situ observation. Plots with tree quadratic mean diameter at breast height 21.5cm were categorized remotely as in severe decline. Landsat TM/ETM+-based NDWI derivatives reveal forest decline and regrowth in post-ROB outbreak surveys. Historical and future Landsat-based canopy change detection should be incorporated with existing landscape-based prediction of ROB hazard.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Joshua S. Jones ; Jason A. Tullis ; Laurel J. Haavik ; James M. Guldin and Fred M. Stephen
"Monitoring oak-hickory forest change during an unprecedented red oak borer outbreak in the Ozark Mountains: 1990 to 2006", J. Appl. Remote Sens. 8(1), 083687 (Jan 23, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083687


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