algorithm. The Landsat MSS image of 1975 
was resampled to 30 meter-pixel resolution 
using nearest neighbor algorithm and then 
registered to the 1993 Landsat TM image. 
Two images were 18 years and 159 days apart 
from each other, thus significant sun angle 
differences between the two may exist. 
However, at this time no effort was made to 
minimize the sun angle differences. To 
overcome the sensor calibration and sensitivity 
differences, images were converted to 
exoatmospheric reflectance using radiance 
transformations suggested by (Markham and 
Barker, 1986). A Digital Elevation Model 
(DEM) was prepared using Survey of 
Pakistan's 1:50,000 topographic maps. These 
maps come with a 1000 meter grid, which 
significantly enhanced their utility for such 
purposes. First, all the grid intersections were 
digitized. Then, elevations read from the 
contour line at each grid intersection. Over 
1000 elevation points were manually recorded 
on a sheet of paper. Second, the elevation 
points were imported to ARC/INFO in ASCII 
format, and the KIRIGING procedure was used 
for surface interpolation, which produced a 100 
meter DEM. Finally, the 100 meter resolution 
DEM was resampled to match 30 meter-pixel 
resolution of TM. 
6.1 Image Classification 
An unsupervised classification scheme 
was used for clustering purposes. This utilizes 
a Iterative Self Organizing Data Analysis 
Technique (ISODATA) to partition the data 
into homogeneous spectral classes. The intent 
of the ISODATA is to minimize the cluster 
variance and to maximize the distance between 
clusters. Statistical and visual analysis of the 
data was then used to build meaningful clusters 
of forest and non-forest vegetation classes for 
both images. 
120 
The Landsat MSS classification results 
were significantly satisfactory compared to 
Landsat TM. TM image was acquired during 
a time of year, that is considered a “prime 
vegetation season” in this part of the 
Himalayas. The presence of healthy green 
cultivated fields and orchards on the Pakhli 
Plain in Siran Valley introduced considerable 
spectral confusion in delineation of forests on 
the surrounding mountains. The MSS on the 
other hand was acquired in a time of year, 
when forests are the only vegetation in the 
region. Most of the agricultural land on the 
plain lies as fallow land, because cultivation of 
winter wheat does not start until January. The 
absence of agriculture greatly facilitated the 
delineation process of forest classes in the 
MSS image. 
The problem of spectral confusion 
encountered in the TM data was overcome by 
using the DEM model. The knowledge of the 
region’s physiography and vegetation was 
incorporated in formulating logical rules to 
stratify the vegetation types based on elevation 
criteria. According to these rules, the 
agriculture on the Pakhli Plain was restricted 
to maximum elevation of 909 meters. 
Agriculture in the valleys, which is mostly 
terraced rice fields or corn was restricted to the 
maximum elevation of 1090 meters. Any 
vegetation above this elevation was considered 
forest. Thus, the vegetation was classified into 
three classes, a) forests b) terraced cultivation, 
and c) agriculture on the plains. The 30 meter 
DEM was recoded using ARC/INFO to above 
mentioned three elevation classes. The 
recoded DEM assisted in delineation of 
argiculture on the plain from the forest pixels 
on the surrounding hills. The forest-type maps 
on a 1:50,000 scale, prepared by the forest 
department were also used in classification 
processes for both images. 
  
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