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NDVI in 2002

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Using Landsat Imagery to Monitor Post-fire Forest Dynamics in Upland Oak Forests on the Cumberland Plateau, Kentucky

Three (spring) fire treatments for each of the three study areas (each site ~150-300 acres; 8-12 plots per site):

• Fire-excluded • Less-frequent Burn (2003, 2009) • Frequent Burn (2003, 2004, 2006, 2008)

Throughout the central hardwood and southern Appalachian regions forest managers use prescribed fire to achieve a suite of management objectives. Monitoring is mandated on federal lands in order to determine the efficacy of prescribed fire to achieve stated objectives, yet limited funding for such efforts restricts the number, size, and spatial array of monitoring plots. Monitoring is typically done with a small number of plots across very large landscapes, and therefore is limited in its ability to reveal the true landscape-scale impact of forest management. Based on its use in other forested ecosystems, remote sensing data have the potential to provide accurate and relatively inexpensive information in support of landscape-scale fire management in central hardwood and southern Appalachian forests. Here we describe our preliminary efforts to develop this approach.

Special thanks to the USDA-USDI Joint Fire Science Program, Daniel Boone National Forest, U.S.F.S. Southern Research Station, and the University of Kentucky Agricultural Experiment Station

Funding was provided by the Cooperative State Research, Education and Extension Service, U.S. Department of Agriculture, under Agreement No. 2009-34628-20231, and by a mini-grant from KentuckyView - the Commonwealth’s Remote Sensing Consortium (www.kentuckyview.org).

Study areas

• Summer multi-temporal Landsat 5 Thematic Mapper imagery was used to:

(1) calculate the NDVI, (2) examine changes in the NDVI with burn treatment, and (3) analyze the relationships between NDVI and canopy cover.

Methods

4x Burn (Spring ‘03, ‘04, ‘06, ‘08)

Fire excluded

2x Burn (Spring ‘03, ‘09)

NDVI and canopy cover were weakly, but significantly, related over all treatments prior to the first prescribed burn in 2003 (Adj. R2 0.11, p=0.03).

Does NDVI vary among burn treatments? Linear regression was used to evaluate relationships between pre- and post-fire NDVI values.

Is NDVI related to canopy cover? Linear regression was used to examine relationships between Canopy Cover and NDVI before and after prescribed fire. Where do we go from here?

After the first prescribed burn in 2003, there was a strong, positive relationship between canopy cover and NDVI over all treatments (Adj. R2 0.50, p<0.0001).

In 2007, after three burns on Frequent sites and one burn on Less Frequent sites, there was still a strong, positive relationship between canopy cover and NDVI (Adj. R2 0.38, p<0.0001).

The greatest magnitude of reduction in NDVI occurred after the first prescribed fire in 2003 at both Frequently and Less Frequently burned sites. Less Frequently burned sites continued to recover until they were burned again in 2009. Frequently burned sites exhibited reduced NDVI values across most years compared to the Control and Less Frequently burned sites.

In addition to the NDVI, we are examining several other spectral vegetation indices (SVIs) in relationship to prescribed burning treatments in our study area, e.g. the Kauth-Thomas brightness, greenness and wetness indices.

To further test the value of Landsat imagery for monitoring the effects of prescribed fire on forest structure, we plan to:

• Examine relationships between SVIs and crown health;

• Explore the influence of landscape position on post-fire SVIs; and

• Determine whether combinations of SVIs can be used to distinguish between canopy cover and understory sprouting response to burning.

NDVI images before (2002, left) and after (2003, right) the first prescribed burn. Study areas are outlined according to burn frequency (see study area map above).

Year2002 2003 2004 2005 2006 2007 2008 2009 2010

NDVI

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Control Frequent Less Frequent

Orange arrows denote fire on less frequent sites Red arrows denote fire on frequent sites

* A A A A B B A B AB A A A A B A A B A AB A B A AB B A B A

* Different letters within years denote statistically significant differences among treatments.

The problem

Role of fire frequency? NDVI differences among treatments (ANOVA)

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NDVI in 2002

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NDVI in 2002

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Control: R2=0.53; p<0.0001 Frequent: R2=0.17; p=0.0142 Less Frequent: R2=0.21; p=0.0059

Control: R2=0.67; p<0.0001 Frequent: R2=0.31; p=0.0008 Less Frequent: R2=0.63; p<0.0001

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Canopy Cover (%) in 2003

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Canopy Cover (%) in 2007

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While there was some landscape scale variability in NDVI prior to the first prescribed burn in 2003, there was little variability in NDVI among treatments between 2001 and 2002 (R2=0.66, p<0.0001).

Mary Arthur1, Christine McMichael2, and Gretchen Sovkoplas1 1University of Kentucky, Dept. of Forestry, 2School of Public Affairs, Morehead State University, Morehead, KY

Wolf Pen Chestnut

Cliffs

Buck Creek

• Hemispherical photography was used in a subset of plots to measure canopy cover from 2002-2007.

• Data analysis was conducted using linear regression and analysis of variance (ANOVA).

In the growing season after prescribed fire was first applied to both the Frequent and Less Frequent sites, the NDVI was lower on burned sites overall. The lower R2 for burned sites reflects much greater variability in NDVI in 2003 compared to 2002.

Frequent sites were burned again in 2006, and had significantly lower NDVI values that year compared to pre-burn conditions (2002). Even so, NDVI in burned areas was ‘recovering’, as illustrated by R2 values approaching that of the control area.

Results

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Canopy Cover (%) in 2002

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