Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan

Abstract

Alteration in Land Use/Cover (LULC) considered a major challenge over the recent decades, as it plays an important role in diminishing biodiversity, altering the macro and microclimate. Therefore, the current study was designed to examine the past 30 years (1987–2017) changes in LULC and Land Surface Temperature (LST) and also simulated for next 30 years (2047). The LULC maps were developed based on maximum probability classification while the LST was retrieved from Landsat thermal bands and Radiative Transfer Equation (RTE) method for the respective years. Different approaches were used, such as Weighted Evidence (WE), Cellular Automata (CA) and regression prediction model for the year 2047. Resultantly, the LULC classification showed increasing trend in built-up and bare soil classes (13 km2 and 89 km2), and the decreasing trend in vegetation class (−144 km2) in the study area. In the next 30 years, the built-up and bare soil classes would further rise with same speed (25 km2 and 36.53 km2), and the vegetation class would further decline (−147 km2) until 2047. Similarly for LST, the temperature range for higher classes (27 -< 30 °C) increased by about 140 km2 during 1987–2017, which would further enlarge (409 km2) until 2047. The lower LST range (15 °C to <21 °C) showed a decreasing trend (−54.94 km2) and would further decline to (−20 km2) until 2047 if it remained at the same speed. Prospective findings will be helpful for land use planners, climatologists and other scientists in reducing the increasing LST associated with LULC changes.

Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach

“…Since majority of the people moves to Ghaziabad in search of employment opportunities, the residential area has expanded in the past decade along with the LST, as was mentioned earlier, Ghaziabad is situated in the National Capital Region (NCR), and the district is also recognised as an industrial hub. As a result, Land Use (LU) planners, will be able to reduce the rising LST caused by changes in LULC by using the potential findings (Rehman et al, 2022).…”

Unveiling the Dynamics of Thermal Characteristics Related to LULC Changes via ANN

“…Remote sensing techniques offer advanced support for monitoring spatio-temporal LULCC, ecological conditions, and thermal patterns at local, regional, and global scales [10]. Satellite missions, such as Landsat and Sentinel, coupled with improvements in the accuracy of global navigation satellite system (GNSS) techniques [11][12][13][14], provide freely available remotely sensed images that can be used for obtaining LULC and LST [15,16].…”