Abstract:
The landslide susceptibility (LS) of any mountainous
region is signifcantly affected by the land-use land-cover (LULC)
change. Recently, LULC change effects on landslides have been
investigated by many researchers. However, the future prediction
of the LS using these LULC changes has not been quantifed. The
main objective of this study is to predict the future LS map considering the future LULC change scenario for the Tehri region, India.
To achieve this objective, we frst prepared a geospatial database of
past landslide events. These events data were clustered into three
major temporal categories, 2005–2010, 2010–2015, and 2015–2020.
Second, the artifcial neural network (ANN) approach was adopted
to prepare LS maps for the years 2010, 2015, and 2020. Then, for
the same years, LULC maps were also developed. Third, the future
scenario of LULC for the year 2030 was simulated using the ANNcellular automata model, and the future LULC changes were derived
using the change detection technique. Finally, the future LS map
for 2030 was projected using derived future LULC changes. The
LULC change results reveal that the region is expected to see a signifcant growth in the built-up area by 34.1%, water body by 6.3%,
and agriculture land by 1%. Further, a shrink in dense forest area
by 2.4% and sparse forest area by 0.9% is expected in the future.
Additionally, the projected LS results reveal a 33% increment in the
very high LS zone. This information about the increase in future LS
due to rapid urban growth in the mountains can help the various
government agencies to scientifcally plan the various developmental activities.
