Geoscience Reference
In-Depth Information
7.2.1.2 Generation of Landslide Inducing Factor Maps
First, the contour map at 20 m interval was prepared and digitized from the SOI
Topo-sheet (1987, 78B/5) at the scale of 1:50,000 and subsequently employed for
generating the Digital Elevation Model (DEM) using ARC GIS Software. Then
slope gradient, slope curvature and slope aspect map were derived from DEM and
classi
cation was made to derive all these parameters in raster value domain fol-
lowing the earlier works of Dhakal et al. (
2000
). Surface curvature is a topographic
attribute that describes the convexity/concavity of a terrain surface. Curvature
depicts the slope gradient or slope direction (aspect), usually in a particular
direction. A positive curvature indicates that the surface is upwardly convex at a
grid cell and a negative curvature indicates that the surface is upwardly concave at
that grid cell. A value of zero indicates that the surface is flat. The expected values
of all three output raster images for a hilly area can vary from
0.5 to 0.5; for steep,
−
rugged mountains the value can vary between
4 and 4.
The lithological map of the study area was collected from Geological Survey
India (GSI), Kolkata (Eastern Region) and necessary modi
−
cations were incorpo-
rated after intensive
field investigation. Final lithological map was prepared and
transformed into raster value domain on ARC GIS Platform. Class weight value for
each lithological class was assigned according to rock mass strength, described by
GSI. A Drainage density map (length of drainage/m
2
) was made from the topo-
graphical map (78B/5, 1987) and classi
ed into ten equal intervals.
The lineament exhibits the zone of weakness surface of some linear to curvi-
linear features such as fracture, joint, fault etc. in the geological structure. There are
no basic differences between these three features. All these linear to curvilinear
features were identi
ed as the same deformed surface where the propensity of slope
instability is very high. To generate lineament map (distance from lineament in
meters) of the Shiv-khola watershed, PCI-GEOMATICA was used and in the
extraction process 3 SRTM bands of wavelengths were taken into account: Near
Infrared (Band-I; 0.7
1.3
µ
m), Red (Band-II; 0.6
0.7
µ
m) and Green (Band-III;
-
-
0.5
0.6
µ
m). The
'
Lineament extraction
'
algorithm was used to prepare lineament
-
map. The study area was classi
ed into ten classes on the basis of the distance (m)
from lineaments.
Upslope Contributing Area is an effective indicator of drainage concentration
over space. The place with more contributing area encompasses more soil saturation
that reduces soil cohesion. The speci
c contributing area (total contributing area
divided by the contour length) is computed by distributing flow from a pixel among
its entire lower elevation neighbour pixel (Borga et al.
1998
). Quinn et al. (
1991
)
proposed that the Fraction of Flow (Fi)
i
) allocated to each lower neighbour (i) is
determined by using Eq. 7.1. An upslope contributing area map was prepared based
on calculated contributing area value for each (0.25 km
2
) grid and it was divided
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