Vegetation Responses to Seasonal Climatic Variability in Blacksburg, Va
By Logan Sleezer
ES775: Advanced Image Processing
Blacksburg, home to Virginia Polytechnic and State University, is a town of 42,620 people as of the 2010
US Census (US Census Bureau, 2010), located in western Virginia. Sitting at an elevation of around 640 meters above sea level (US Climate Data, 2017),
Blacksburg represents an interesting climatic transition zone between the Blue Ridge mountains just to
the north and west and the lowlands of the Atlantic Coastal Plain to the east. The Koppen climate
classification system characterizes Blacksburg’s climate as humid continental with a cool summer (Dfb)
according to 30-year normals (NCDC, 2017). However, climatic averages cannot tell the whole story as there exists a
great deal of seasonal variability in climate in this region from year-to-year. This seasonal variability has
implications for landcover patterns, especially seasonal vegetation patterns that can be monitored using
Using climatic data from the National Climatic Data Center (NCDC), I identified months and years that
represented the range of weather possible in the highly variable autumn and late winter/early spring time
periods in Blacksburg. After identifying candidate years that best showed the range of conditions that
were possible in these two seasons, I conducted a search for Landsat satellite imagery taken during
these time periods using USGS Earth Explorer. After finding suitable, nearly cloud-free imagery for
comparison between years, the Landsat multiband image data was downloaded and Idrisi Selva
software was used to construct NDVI images to aid in comparison of vegetative characteristics between
years. All imagery used in this study was derived from Landsat 4/5 multiband scenes downloaded from
Earth Explorer (USGS, 2017). Each NDVI image was also reclassified using Idrisi, with the goal of
creating categories to quantitatively compare active vegetation land coverage between years and between
seasons. The large Landsat tiles were clipped to a smaller study area that includes the city of Blacksburg
near the center of the scene, but also the New River, which runs south to north across the western
portion of the scene. The portion of the New River shown in this scene runs through the Blue Ridge
Mountains and includes two major reservoirs, Bluestone Reservoir and Claytor Reservoir, which
represent the northern and southern extent of the study area respectively.
The first image comparison shows the study area in late October during the consecutive years of 1988
and 1989. The natural color and NDVI image comparisons below show that vegetation, especially the
deciduous forest dominated ridges of the Blue Ridge Mountains, have begun to change leaf colors and
go dormant in the 1989 image, while remaining active and green in the 1988 image. NDVI (Normalized
Difference Vegetation Index) is an image processing method utilizing the ratio of band 3 (red) to
band 4 (infrared) to create an image that isolates highly active vegetation due to the highly distinctive
pattern of high infrared reflectance and low red reflectance of green plants. Areas with high NDVI
values (indicating high levels of vegetation activity) appear dark green while less active areas
appear lighter green to yellow/orange for the lowest vegetation activity.
In general, there are three major factors that affect timing of leaf die-off in the fall. These factors are photoperiod,
moisture/precipitation, and temperature. Because these images are only three days apart in consecutive years, the effect
of photoperiod on vegetative differences in these two scenes should be negligable. However, weather patterns were
drastically different in 1988 and 1989 in Blacksburg. Surprisingly, 1988 was both drier and colder than 1989 as indicated
by the table below, but still had more active vegetation in October. While the actual cause of this strange phenomenon is
a mystery, abnormally heavy rains in September and October of 1989 could have contributed to early leaf die-off. In a similar
study, Aber et al. (2002) found that decreases in NDVI values for forests may lag a year or two behind periods of drought
because of the dependence of tree growth on food storage from previous years. This lag effect may be a more likely cause of
the early leaf die-off in the warm, wet fall season of 1989 because of the delayed effects of the comparable drought conditions
The second image comparison shows the study area in mid-March during the consecutive years of 1999
and 2000. The most obvious difference between the scene in 1999 and in 2000 is the snow cover in 1999,
showing up light blue on the natural color image, but absent in 2000. The NDVI image comparison shows the
expected dearth of active vegetation in 1999 compared to the same time in 2000, due to the harsher
late winter in 1999.
Heavy March snowfall in 1999 was well above average in this month when considering 30 year climatic normals as shown
in the table below. The year of 2000 was much more reflective of a normal snowfall pattern in Blacksburg, with January
being the month with the highest snowfall total and a more mild late winter.
Reclassification of NDVI images allowed a means of comparison between the two October scenes and two March scenes in
terms of the total area of the study site covered by highly active vegetation. For the purposes of this study, NDVI
values greater than 0.5 were considered areas of highly active vegetation. The scene with the highest area covered by
highly active vegetation was the October 1988 scene at approximately 4322 square kilometers. The March 2000 scene had
the second greatest highly active vegetation area at 802 square kilometers, followed by October 1989 at 649 square
kilometers, and March 1999 at 482 square kilometers. The image comparisons below are reclassified NDVI images compared
between the same season (October and March) in consecutive years. Categories 3 and 4 in the images below are those that
were included in the calculation of total areas covered with highly active vegetation.
Reclassified NDVI Images
Seasonal weather patterns are highly variable in the Blacksburg area and can have a profound and sometimes surprising
effect on landcover characteristics, especially activity of vegetation. Comparing fall and early winter variability,
land coverage by highly active vegetation was most variable in the fall, as the October 1988 scene had over 6 times the
highly active vegetation coverage as the October 1989 scene. Late winter variability was less, but still significant in this
study as the highly active vegetation coverage in the March 2000 scene was nearly twice the coverage seen in March 1999.
Aber, J.S., Wallace, J.W., and Nowak, M.C., 2002. Response of Forest to Climatic Events and Human Management at Fort Leavenworth, Kansas. Current Research in Earth Sciences, Bulletin 248, part 1, p. 1-24.
NCDC, 2017. Data Tools: 1981-2010 Normals. https://www.ncdc.noaa.gov/cdo-web/datatools/normals. Date Accessed: 05/01/2017.
US Census Bureau, 2010. QuickFacks: Blacksburg town, Virginia. https://www.census.gov/quickfacts/table/PST045215/5107784. Date Accessed: 05/01/2017.
US Climate Data, 2017. Map of Blacksburg - Virginia. http://www.usclimatedata.com/map.php?location=USVA0068. Date Accessed: 05/01/2017.
USGS, 2017. EarthExplorer. https://earthexplorer.usgs.gov/. Date Accessed: 04/25/2017.