Geographically weighted regression to measure the role of intra-urban drivers for urban growth modelling in Kathmandu, Central Himalayas.

The present study analyzes spatio-temporal urban growth in Kathmandu Urban Agglomeration (KUA) and its impact on ecological infrastructures between 2000 and 2020. A geographically weighted regression (GWR) approach was used to investigate intra-urban drivers of urban growth between 2000-2010 (epoch 1) and 2010-2020 (epoch 2), and to predict built-up growth for the year 2030. The study makes crucial contributions to the urban growth modelling literature by (a) investigating six different neighborhood sizes (3 × 3 to 13 × 13) for computing proportion of built-up cells and (b) eliminating/selecting covariates using correlation check and global lasso regression. The superiority of GWR model over global regression model has been evaluated using the Akaike information criterion score and the stationarity test. The chronological urban growth analysis of KUA highlights rapid growth in mountainous landscape from 54.90 to 166 km 2 during 2000-2020 and is projected to increase to 224.22 km 2 during 2000-2030. This has significantly altered the forest-agriculture landscape during 2000-2020 (111.2 km 2 ) and is expected to affect a large segment of ecological (blue-green) infrastructure (138 km 2 ) by 2030. The findings of this study may be used for policy formulation, appropriate land use planning, and sustainable urban development.