Natural like Rendition of Yellowstone National park …...Natural-like Rendition of Yellowstone National park After the Fire on October , Figure . This image was created with the band

Fire Severity and Vegetation Recovery in Yellowstone National Park, Wyoming, USA

Introduction

In August 1988, Yellowstone National Park had a series of devastating wild

fires that were considered the largest forest fire burn event in the recorded

history of the national park. (Scullery, 1989). The fire started as a series of

smaller fires which were exacerbated by increasing winds and drought which

burned for several months. Thousands of firefighters and military personal

fought the fire but it was not until early October that the fire was brought

under control by cool and moist weather conditions. This project aims to

evaluate burn severity following the forest fire along with the vegetation re-

covery response 23 years later. This process was done through the use of re-

mote sensing technology which has been proven to be an accurate tool to

evaluate forest fires and ecological recovery.

Natural-like Rendition of Yellowstone National park After the Fire on October 10, 1988

Figure 1. This image was created with the band combination of 7,4,2 which provides a natural-like ren-

dition while also penetrating smoke and atmospheric particles. Red indicates a recent forest fire,

bright green areas indicate healthy vegetation, pink represents barren soil, and blue areas represent

water.

Burn Severity Assessment Using Normalized Burn Ratio in 1988

NDVI Change

No Change

Increase (Moderate)

Increase (High)

NDVI Change and Vegetation Recovery of Severe Burned areas as of 2011

No

Change

Increase

(Moderate)

Increase

(High)

Percent of

High severity

Area

0.24% 53.60% 46.16%

Table 2. NDVI Change between 2011 and

the days after the fire in 1988

Methodology

Three images for Yellowstone National Park were acquired from Landsat

5. The first image was acquired for September 22, 1987, which was a year

before the wild fire started. The second image was acquired for October 10,

1988 which was eight days directly after the fire. The third image was ac-

quired for September 24, 2011 which was 23 years after the fire. The dates

were chosen as close to the day and month of each other as possible to

avoid any spectral variances due to the time of year.

To analyze the severity of the forest fire, Normalized Burn Ratio (NBR)

was used. NBR utilizes the short-wave infrared bands which are not affected

by dust, smoke and atmospheric particles (Avery & Berlin, 1998; Eva & Lamb-

in, 1998). Cocke et al. (2005) states that several studies have concluded that

using this band combination provides the highest accuracy for burn severity

analysis. The NBR algorithm was applied on the pre-fire and post-fire images

and then a change in NBR was calculated through an image differencing al-

gorithm. The unsupervised classification was then combined with the

change in the NBR map in a GIS software to create a fire severity index seen

in Figure 3.

To analyze the restoration of the damaged forest, change detection using

normalized vegetation index (NDVI) was used. NDVI gives an indication of

the amount of green vegetation and is effective in detecting vegetation re-

covery after a fire event (Delgado et al., 2003). Change in NDVI values were

examined in high severity burned areas since those areas experienced com-

plete vegetation loss.

Results and discussion

Burned area was classified based on how much damage the forest canopy

sustained and was characterized by four categories: low severity, moderate-

low severity, moderate-high severity and high severity (Figure 3). With a rela-

tively even distribution of percent burned areas in each category (Table 1), it

becomes clear that certain areas of forest were affected by the fire to a

different degree. Further ground based research could indicate what tree

species or environmental factors contribute to each severity category.

Within the high severity burned areas, NDVI change detection revealed

that 53.6% of this area experienced a moderate increase in vegetation while

46.16% experienced a high increase in vegetation. This indicates, without a

doubt, that the forest within high severity category is recovering to some de-

gree.

Low

Severity

Moderate-

Low

Severity

Moderate-

High Severity

High Severity

Percent of

Burned

Area

21.61% 22.46% 32.77% 23.16%

Table 1. Fire Severity Established Through Normalized Burn Ratio

References

Avery T. E, Berlin G. L .(1992) ‘Fundamentals of remote sensing and air photo interpretation.’ (Prentice Hall: Upper Saddle River, NJ) 472 pp.

Cocke, A. E, Fule, P. Z, & Crouse, J. E. (2005). Comparison of burn severity assessments using differenced Normalized Burn Ratio and ground

data. International Journal of Wildland Fire Vol 14, 198-198.

Delgado, D, Lloret, F, & Pons, X. (2003). Influence of fire severity on plant regeneration by means of remote sensing imagery. International

Journal of Remote Sensing Vol 24, No. 8, 1751-1763.

Eva H, Lambin E. F. (1998) Burnt area mapping in Central Africa using ATSR data. International Journal of Remote Sensing 19, 3473–3497.

Schullery, P. 1989. The fires and fire policy. Bioscience 39: 686-695.

1988-2011 NDVI Composite

Figure 2. This image combines both NDVI images from October 10, 1988 and September 24, 2011 to

a show change in NDVI values . Bright cyan indicates an increase in vegetation, bright red indicates a

decrease in vegetation, black represents water, grey indicates barren soil, light red indicates forests

that have no change and light cyan indicates grassland that have not increased in vegetation values.

Fire Severity

High Severity

Moderate-high Severity

Moderate-low Severity

Low Severity

0 30 6015 Km

0 30 6015 Km 0 30 6015 Km

0 30 6015 KmFigure 3. Figure 4.

More Information

Data source: Landsat 5

Adriano Nicolucci -Poster presented for partial fulfillment of The Professional Geographer (GEO871).