scholarly journals Analysis of Land Use Land Cover Changes with Land Surface Temperature Using Spatial-Temporal Data for Nagpur City, India

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Farhan Khan ◽  
Bhumika Das ◽  
R. K. Mishra ◽  
Brijesh Patel
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Spatial Data ◽  
Land Surface ◽  
Water Bodies ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Barren Land

Abstract Remote sensing and Geographic Information System (GIS) are the most efficient tools for spatial data processing. This Spatial technique helps in generating data on natural resources such as land, forests, water, and their management with planning. The study focuses on assessing land change and surface temperature for Nagpur city, Maharashtra, for two decades. Land surface temperature and land use land cover (LULC) are determined using Landsat 8 and Landsat 7 imageries for the years 2000 and 2020. The supervised classification technique is used with a maximum likelihood algorithm for performing land classification. Four significant classes are determined for classification, i.e., barren land, built-up, vegetation and water bodies. Thermal bands are used for the calculation of land surface temperature. The land use land cover map reveals that the built-up and water bodies are increasing with a decrease in vegetation and barren land. Likewise, the land surface temperature map showed increased temperature for all classes from 2000 to 2020. The overall accuracy of classification is 98 %, and the kappa coefficients are 0.98 and 0.9 for the years 2000 and 2020, respectively. Due to urban sprawl and changes in land use patterns, the increase in land surface temperature is documented, which is a global issue that needs to be addressed.

scholarly journals Land-Use/Land Cover Changes Contribute to Land Surface Temperature: A Case Study of the Upper Indus Basin of Pakistan

2022 ◽  
Vol 14 (2) ◽  
pp. 934
Author(s):  
Akhtar Rehman ◽  
Jun Qin ◽  
Amjad Pervez ◽  
Muhammad Sadiq Khan ◽  
Siddique Ullah ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Sustainable Land Use ◽  
Indus Basin ◽  
Land Use Land Cover ◽  
Rapid Urbanization ◽  
Barren Land

Land-use/land cover (LULC) changes have an impact on land surface temperature (LST) at the local, regional, and global scales. To simulate the LULC and LST changes of the environmentally important area of northern Pakistan, this research focused on spatio-temporal LULC and associated LST changes since 1987 and made predictions to 2047. We classified LULC from Landsat TM and ETM data, using the maximum probability supervised categorization approach. LST was retrieved using the Radiative Transfer Equation (RTE) methodology. Furthermore, we simulated LULC using the integrated approaches of Cellular Automata (CA) and Weighted Evidence (WE) and used a regression model to predict LST. The built-up areas and vegetation have increased by 2.1% and 11% due to a decline in the barren land by −8.5% during the last 30 years. The LULC is expected to increase, particularly the built-up and vegetation classes by 2.74% and 13.66%, respectively, and the barren land would decline by −4.2% by 2047. Consequently, the higher LST classes (i.e., 27 °C to <30 °C and ≥30 °C) soared up by about 25.18% and 34.26%, respectively, during the study period, which would further expand to 30.19% and 14.97% by 2047. The lower LST class (i.e., 12 °C to <21 °C) indicated a downtrend of about −41.29% and would further decrease to −3.13% in the next 30 years. The study findings are useful for planning and management, especially for climatologists, land-use planners, and researchers in sustainable land use with rapid urbanization.

scholarly journals Land Use/Land Cover Changes and the Relationship with Land Surface Temperature Using Landsat and MODIS Imageries in Cameron Highlands, Malaysia

Land ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 372
Author(s):  
Darren How Jin Aik ◽  
Mohd Hasmadi Ismail ◽  
Farrah Melissa Muharam
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Cameron Highlands ◽  
The Impact

Mountainous regions are more sensitive to climatic condition changes and are susceptible to recent increases in temperature. Due to urbanization and land use/land cover (LULC) issues, Cameron Highlands has been impacted by rising land surface temperature (LST) variation. Thus, this study was carried out to explore the impact of the LULC change on LST in the Cameron Highlands from 2009 to 2019 using remote sensing images acquired from Landsat 7 ETM+, Landsat 8 Operational Land Imager (OLI/TIRS), and Moderate Resolution Imaging Spectroradiometer (MODIS) 11A Thermal sensors. A split-window algorithm was applied to Landsat 8 images (2013–2019) to derive the LST. Air temperature data of the study area were also obtained to cross-validate data sources. Based on the validation results, the accuracy of LULC and LST outputs were more than 94.6% and 80.0%, respectively. The results show that the current trend of urban growth continues at a rate of 0.16% per year, and the area experienced an LST increase of 2 °C between 2009 and 2019. This study is crucial for land planners and environmentalists to understand the impacts of LULC change on LST and to propose appropriate policy measures to control development in Cameron Highlands.

scholarly journals Dynamics of human-induced lakes and their impact on land surface temperature in Toshka Depression, Western Desert, Egypt

2021 ◽  
Author(s):  
Rasha Abou Samra
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Research Area ◽  
Western Desert ◽  
Severe Drought ◽  
Land Use Land Cover

Abstract Land surface temperature (LST) is a significant environmental variable that is appreciably influenced by land use /land cover changes. The main goal of this research was to quantify the impacts of land use/land cover change (LULC) from the drying of Toshka Lakes on LST by remote sensing and GIS techniques. Landsat series TM and OLI satellite images were used to estimate LST from 2001 to 2019. Automated Water Extraction Index (AWEI) was applied to extract water bodies from the research area. Optimized Soil-Adjusted Vegetation Index (OSAVI) was utilized to predict the reclaimed land in the Toshka region until 2019. The results indicated a decrease in the lakes by about 1517.79 km2 with an average increase in LST by about 25.02 °C between 2001 and 2019. It was observed that the dried areas of the lakes were converted to bare soil and are covered by salt crusts. The results indicated that the land use change was a significant driver for the increased LST. The mean annual LST increased considerably by 0.6 °C/y between 2001 and 2019. A strong negative correlation between LST and Toshka Lakes area (R-square = 0.98) estimated from regression analysis implied that Toshka Lakes drying considerably affected the microclimate of the study area. Severe drought conditions, soil degradation, and many environmental issues were predicted due to the rise of LST in the research area. There is an urgent need to develop favorable strategies for sustainable environmental management in the Toshka region.

scholarly journals Assessing and Simulating Impacts of Land Use Land Cover Changes on Land Surface Temperature in Mymensingh City, Bangladesh

2021 ◽  
Vol 20 (2) ◽  
pp. 1-19
Author(s):  
Tahmid Anam Chowdhury ◽  
◽  
Md. Saiful Islam ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Bare Soil ◽  
Land Use Land Cover ◽  
Remarkable Change

Urban developments in the cities of Bangladesh are causing the depletion of natural land covers over the past several decades. One of the significant implications of the developments is a change in Land Surface Temperature (LST). Through LST distribution in different Land Use Land Cover (LULC) and a statistical association among LST and biophysical indices, i.e., Urban Index (UI), Bare Soil Index (BI), Normalized Difference Builtup Index (NDBI), Normalized Difference Bareness Index (NDBaI), Normalized Difference Vegetation Index (NDVI), and Modified Normalized Difference Water Index (MNDWI), this paper studied the implications of LULC change on the LST in Mymensingh city. Landsat TM and OLI/TIRS satellite images were used to study LULC through the maximum likelihood classification method and LSTs for 1989, 2004, and 2019. The accuracy of LULC classifications was 84.50, 89.50, and 91.00 for three sampling years, respectively. From 1989 to 2019, the area and average LST of the built-up category has been increased by 24.99% and 7.6ºC, respectively. Compared to vegetation and water bodies, built-up and barren soil regions have a greater LST each year. A different machine learning method was applied to simulate LULC and LST in 2034. A remarkable change in both LULC and LST was found through this simulation. If the current changing rate of LULC continues, the built-up area will be 59.42% of the total area, and LST will be 30.05ºC on average in 2034. The LST in 2034 will be more than 29ºC and 31ºC in 59.64% and 23.55% areas of the city, respectively.

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