EH 
An Ecological Assessment of the Louisiana Tensas River Basin Chapter 3 
Vegetation Change 
In the previous sections, we discussed landscape 
change based on NALC images that had been classi¬ 
fied. Another method is to calculate indices directly 
from the satellite imagery. It is interesting to compare 
the results of the preceding landscape change analy¬ 
sis with those presented in the following discussion. 
A common perception is that patterns of forest and 
agriculture and urban areas remain constant over time. 
In this section we present patterns of vegetation 
change measured by comparing satellite images from 
1972 and a composite of 1991 and 1992. The change 
is determined by using a vegetation index called Nor¬ 
malized Difference Vegetation Index (NDVI) which was 
calculated for each pixel on each of the two dates. 
When the NDVI values are essentially the same at both 
dates, then there has been no change. When the 
value is greater in 1972 than 1991/92, we interpret this 
as vegetation loss. When the value in 1972 is less than 
1991/92, we interpret this as vegetation gain. Total 
vegetation change is taken to be the sum of loss and 
gain on an area basis. 
The NDVI can be derived from satellite images because 
the near infrared band produces a large reflectance 
compared to the visible red band when looking at vegeta¬ 
tion. The formula for NDVI is: 
NDVI = Infrared Band - Visible Red Band 
Infrared Band + Visible Red Band 
The NDVI also has the advantage of compensating for 
changing illumination conditions like surface slope, 
aspect, and other factors. Indexes derived by NDVI 
range from -1.0 to 1.0, where negative index values 
represent clouds, water, and snow. Index values near 
zero represent barren soil and rock, and positive index 
values are indicators of the variation in vegetation. 
Comparison of temporal changes in reflectance mea¬ 
sures from satellites, such as NDVI, can be useful for 
gaining insight into land cover changes when land cover 
maps from two different dates are not available. Inter¬ 
preting the measurements relative to land cover change 
is not straightforward though because some changes in 
reflectance are not changes in land cover. Crop rotation 
is a good example. Change in NDVI measurements 
may be the result of seeing a field in production on one 
date and fallow on the other. Interpretation of these 
measurements for actual land cover change requires a 
lot of additional work beyond calculating their difference 
over time. 
Despite the complications, the amount and spatial pat¬ 
tern of NDVI change is important. For example, many of 
the decreases in NDVI turn out to be associated with 
road improvements, new residential developments, 
urbanization projects, and construction of reservoirs. 
Gains in NDVI may be the result of crop rotation or matur¬ 
ing vegetation in residential developments. Gains in NDVI 
appear to be associated with both natural and anthropo¬ 
genic processes, whereas non-crop rotation NDVI losses 
appear to be more consistently associated with anthropo¬ 
genic activities. 
These examples show that, after calibration, NDVI 
changes over time can help answer several ecologically 
important questions such as: (1) how much change has 
occurred? (2) is vegetation change evenly distributed 
over all the watersheds in the region, and (3) is vegeta¬ 
tion change concentrated in the headwater regions of 
streams? Figure 3.13 shows the vegetation change from 
1972 through 1991/92. 
Tensas River Basin Agriculture Field. 
