Netra Bahadur Katuwal, Indra Kumar Subedi, Jung-Sup Um, Daejong Kim
Accurate prediction of land use and land cover (LULC) is essential for effective
conservation, sustainable development planning, and managing competing user
demands. This study employs an ANN-Cellular Automation model to simulate and
predict future LULC maps in Chitwan District, Nepal. Three spatial variables, namely
DEM, distance from road and river, and aspect play a significant role in predicting the
LULC map of the area. The model achieves a high accuracy level, with a Kappa value
of 0.95636 indicating a strong agreement between observed and predicted 2020 LULC
maps. By utilizing the 2010 and 2015 LULC maps in combination with the same spatial
variables, the study projects the LULC maps for 2020 and 2030. The results reveal that
due to anthropogenic pressures, there will be a conversion of forest land and other
categories into built-up and cropland areas. The study also identifies dynamic changes
in land use and land cover patterns within Chitwan District. The area of water bodies
initially decreased from 76.88 sq. km in 2010 to 72.14 sq. km in 2015 but underwent a
significant expansion to 99.81 sq. km in 2020 and further to 106.39 sq. km in 2030.
Forest area exhibits a minor reduction from 1506.14 sq. km in 2010 to 1528.78 sq. km
in 2020, followed by a small increase to 1539.53 sq. km in 2030. Built-up areas witness
a steady increase from 3.90 sq. km in 2010 to 14.69 sq. km in 2020 and further growth
to 18.86 sq. km in 2030. The agricultural area shows a decline from 597.05 sq. km in
2010 to 519.36 sq. km in 2020, continuing the slight decline to 511.62 sq. km in 2030.
The study also observes an increase in the area of other wooded land from 35.99 sq. km
in 2010 to 57.34 sq. km in 2020, but a subsequent decrease to 43.58 sq. km in 2030.
Additionally, the analysis of land surface temperature (LST) maps in December for
2010, 2015, and 2020 reveals distinct patterns, with settlement areas consistently
displaying higher temperatures than forest areas. These findings highlight the impact of
land cover on local microclimates, potentially leading to increased urban heat island
effects in settlements. The study underscores the significance of considering land use
and land cover changes when managing urban and forest environments in Chitwan
District, Nepal.
Keywords: Land use and Land cover; ANN- Multi-layer perception; Predicted LULC,
MOLUSCE, QGIS
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