Next Article in Journal
A Deep Look at Metal Additive Manufacturing Recycling and Use Tools for Sustainability Performance
Next Article in Special Issue
Cooling Effect of Paddy on Land Surface Temperature in Cold China Based on MODIS Data: A Case Study in Northern Sanjiang Plain
Previous Article in Journal
Diversity, Equity, and Inclusion and the Salience of Publicly Disclosing Demographic Data in American Environmental Nonprofits
Previous Article in Special Issue
Evaluating Land Use and Land Cover Change in the Gaborone Dam Catchment, Botswana, from 1984–2015 Using GIS and Remote Sensing
Open AccessArticle

Remote Sensing-Based Quantification of the Relationships between Land Use Land Cover Changes and Surface Temperature over the Lower Himalayan Region

1
Department of Environmental Sciences, COMSATS University Islamabad (CUI), Abbottabad Campus, Abbottabad 22060, Pakistan
2
Department of Civil Engineering, COMSATS University Islamabad (CUI), Abbottabad Campus, Abbottabad 22060, Pakistan
3
Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada
4
Spatial Sciences Discipline, School of Earth and Planetary Sciences, Curtin University, Kent St, Bentley WA 6102, Australia
*
Authors to whom correspondence should be addressed.
Sustainability 2019, 11(19), 5492; https://doi.org/10.3390/su11195492
Received: 22 July 2019 / Revised: 28 September 2019 / Accepted: 30 September 2019 / Published: 3 October 2019
(This article belongs to the Special Issue Modelling Land Use Change and Environmental Impact)
Population growth and population inflow from other regions has caused urbanization which altered land use land cover (LULC) in the lower Himalayan regions of Pakistan. This LULC change increased the land surface temperature (LST) in the region. LULC and LST changes were assessed for the period of 1990–2017 using Landsat data and the support vector machine (SVM) method. A combined cellular automata and artificial neural network (CA-ANN) prediction model was used for simulation of LULC changes for the period of 2032 and 2047 using transition potential matrix obtained from the data years of 2002 and 2017. The accuracy of the CA-ANN model was validated using simulated and classified images of 2017 with correctness value of 70% using validation modules in QGIS. The thermal bands of Landsat images from the years 1990, 2002 and 2017 were used for LST derivation. LST acquired for this period was then modeled for 2032 and 2047 using urban indices (UI) and linear regression analysis. The SVM land cover classification results showed a 5.75% and 4.22% increase in built-up area and bare soil respectively, while vegetation declined by 9.88% during 1990–2017. The results of LST for LULC classes showed that the built-up area had the highest mean LST as compared to other classes. The future projection of LULC and LST showed that the built-up area may increase by 12.48% and 14.65% in 2032 and 2047, respectively, of the total LULC area which was ~11% in 2017. Similarly, the area with temperature above 30 °C could be 44.01% and 58.02% in 2032 and 2047, respectively, of the total study area which was 18.64% in 2017. This study identified major challenges for urban planners to mitigate the urban heat island (UHI) phenomenon. In order to address the UHI in the study area, an urban planner might focus on urban plantation and decentralization of urban areas. View Full-Text
Keywords: artificial neural network; cellular automata; support vector machine; urban heat island; urban indices artificial neural network; cellular automata; support vector machine; urban heat island; urban indices
Show Figures

Figure 1

MDPI and ACS Style

Ullah, S.; Tahir, A.A.; Akbar, T.A.; Hassan, Q.K.; Dewan, A.; Khan, A.J.; Khan, M. Remote Sensing-Based Quantification of the Relationships between Land Use Land Cover Changes and Surface Temperature over the Lower Himalayan Region. Sustainability 2019, 11, 5492.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop