Geoscience Reference
In-Depth Information
latitude
and
1011290
to
1011440E
longitude,
with
approximate
area
of
1975 km
2
.
The major types of landcover in the study area comprises of settlement, peat
swamp forest, and abandoned mining, grassland and few shrub areas. The overall
temperature of the area ranges between 29 and 32 C. The average precipitation
varies from 58 to 240 (mm/month), which trap large amount of water leading to a
high pore-water pressure that decreases the shear stress stability (Malaysian
Meteorological Services Department). Also, the deforestation activity play some
role in destabilizing the slopes (Evett et al.
2006
). More about geological and
geomorphological characteristics of the study area can be seen in Althuwaynee
et al. (
2012a
,
b
).
3 Data
Since this is a follow-up article to (Althuwaynee et al.
2012a
,
b
), therefore the
basic data and other characteristics of the study area can be referred to those
aforementioned articles. The landslide inventory consists of 219 landslides, was
collected over the past 25 years mainly by using remote sensing sources:
• An archived 1:5000-1:50,000 aerial photos, SPOT 5 panchromatic satellite
image and archived landslide location map and previous reports.
• A 1:25,000 scale topographic map used to model a digital elevation model,
• The geological map at scale 1:63,000 was used to produce the lithological map
and distance from the faults.
• The Soil map at the scale 1:100,000 was used to extract the soil properties.
• The precipitation map was prepared using the past 29 years (1981-2010) of
rainfall data. Enhanced Thematic Mapper (ETM +) satellite data was used to
extract the land cover and NDVI (Normalize difference vegetation index) maps.
4 Methodology
Bothe landslide inventory map and conditioning factors were constructed and
converted to a common pixel unit size. The NNI method will test the spatial
pattern of landslides, then the output will be used as a training dataset for EBF
modeling to produce landslide susceptible map LSM2.
LMS2 should be validated by comparing it with previous LMS1 produced by
using random inventory selection technique (Althuwaynee et al.
2012a
). Finally,
the results were evaluated by using the landslides location which was not used
during the model building process (Fig.
1
).
