TY - JOUR
T1 - Impact of spatiotemporal land-use and land-cover changes on surface urban heat islands in a semiarid region using Landsat data
AU - Kamali Maskooni, Ehsan
AU - Hashemi, Hossein
AU - Berndtsson, Ronny
AU - Daneshkar Arasteh, Peyman
AU - Kazemi, Mohammad
PY - 2021/2
Y1 - 2021/2
N2 - Many factors are involved in urban heat island development, such as lack of green spaces, improper choice of building materials, densification, and other human activities. The aim of this research was to quantify the effects of land-use/land-cover (LU/LC) changes on urban land surface temperature (LST) during a 25-year period (1993–2018) for the semiarid Shiraz City in southern Iran using Landsat data (TM, ETM+, and OLI/TIRS) and machine learning algorithms. Five main LU/LC classes, such as orchard, vegetation, bare surface, asphalt cover, and built-up areas, were identified using a support vector machine algorithm. Landsat images were used to retrieve normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). The results showed that the mean LST over the entire study domain increased considerably between 1993 and 2018, due to urbanization, decrease of green areas, and increasing industrial areas. Built-up areas increased considerably by 25.8% from 80 to 100.6 km2 between 1993 and 2018, while vegetation cover decreased dramatically by 69.3%. Mean LST increased from 38.4 to 40.2°C during the 25-year period with a significant increase of 3.9°C between 2013 and 2018. In addition, the Urban heat island Ratio Index (URI) displayed a substantial upward trend during the 25-year period.
AB - Many factors are involved in urban heat island development, such as lack of green spaces, improper choice of building materials, densification, and other human activities. The aim of this research was to quantify the effects of land-use/land-cover (LU/LC) changes on urban land surface temperature (LST) during a 25-year period (1993–2018) for the semiarid Shiraz City in southern Iran using Landsat data (TM, ETM+, and OLI/TIRS) and machine learning algorithms. Five main LU/LC classes, such as orchard, vegetation, bare surface, asphalt cover, and built-up areas, were identified using a support vector machine algorithm. Landsat images were used to retrieve normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). The results showed that the mean LST over the entire study domain increased considerably between 1993 and 2018, due to urbanization, decrease of green areas, and increasing industrial areas. Built-up areas increased considerably by 25.8% from 80 to 100.6 km2 between 1993 and 2018, while vegetation cover decreased dramatically by 69.3%. Mean LST increased from 38.4 to 40.2°C during the 25-year period with a significant increase of 3.9°C between 2013 and 2018. In addition, the Urban heat island Ratio Index (URI) displayed a substantial upward trend during the 25-year period.
KW - land cover
KW - land use
KW - population density
KW - semiarid
KW - urban heat island
KW - Urbanization
UR - http://www.scopus.com/inward/record.url?scp=85090134035&partnerID=8YFLogxK
U2 - 10.1080/17538947.2020.1813210
DO - 10.1080/17538947.2020.1813210
M3 - Article
AN - SCOPUS:85090134035
SN - 1753-8947
VL - 14
SP - 250
EP - 270
JO - International Journal of Digital Earth
JF - International Journal of Digital Earth
IS - 2
ER -