Assessing land surface temperature and land use change through spatio-temporal analysis: a case study of select major cities of India

Aithal, Bharath H.; Chandan, M. C.; Nimish, G.

doi:10.1007/s12517-019-4547-1

Cited by 30 publications

(4 citation statements)

References 54 publications

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“…Changing land use land cover (LULC) has very significant impact on weather, climate and aerosols (Mahmood et al, 2010). It is well stabilised fact that the LULC change has direct relation with land surface temperature, vehicular emission and anthropogenic activity (Aithal and MC, 2019). Which motivated the present study for the further analysis for…”

Section: Introductionmentioning

confidence: 93%

Measurement report: Intra-annual Variability of Black/Brown Carbon and Its Interrelation with Meteorological Conditions over Gangtok, Sikkim

Kumar,

Sharma,

Malu

et al. 2023

Preprint

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Abstract. Black carbon (BC) and brown carbon (BrC) have versatile nature, and they have apparent role in the climate variability and changes. As the anthropogenic activity is surging, the BC and BrC are also reportedly increasing. So, the monitoring of BC/BrC and observation of land use land cover changes (LULCC) at regional level are necessary for the various interconnected meteorological phenomenal changes. The current study investigates BC, BrC, CO2, BC from fossil fuels (BCff), BC from biomass burning (BCbb), LULCC, and their relationship to the corresponding meteorological conditions over Gangtok in Sikkim Himalayan region. The concentration of BC (BrC) 43.5 μg/m3 (32.0 μg/m3) is found to be highest during the March-2022 (April-2021). Surface pressure has been found to have a significant positive correlation with BC, BCff, BCbb and BrC. The boundary layer is calmer and more stable when the surface pressure is higher, which keeps contaminants deposited there. The wind, on the other hand, appears to represent the dispersion of pollutants with a strong negative correlation. The fact that all pollutants and precipitation have been shown to behave similarly points to moist scavenging of the pollutants. Despite the dense cloud cover, the area is not receiving convective precipitation, implying that orographic precipitation is occurring over the region. Most of Sikkim receives convective rain from May to September, indicating that the region has significant convective activity contributed from the Bay of Bengal during monsoon season. Furthermore, monsoon months have the lowest concentrations of BC, BCbb, BCff, and BrC, suggesting the potential of convective rain (as rain out scavenging) to remove most of the pollutants. Moreover, BC and BrC show positive radiative feedback.

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Section: Introductionmentioning

confidence: 93%

Measurement report: Intra-annual Variability of Black/Brown Carbon and Its Interrelation with Meteorological Conditions over Gangtok, Sikkim

Kumar,

Sharma,

Malu

et al. 2023

Preprint

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“…The obtained dispersion, breed and spread values were less (best-fit = 1), indicating lesser spontaneous growth. According to Aithal et al (2019), the values of dispersion and breed coefficients for major four Indian cities Delhi, Mumbai, Kolkata and Hyderabad was found to be low. This similar behaviour specifies the lesser chances of outward dispersive growth and formation of new urban centres on its own.…”

Section: Model Predictionmentioning

confidence: 99%

Urban modelling and forecasting of landuse using SLEUTH model

Kumar

Agrawal

2022

Int. J. Environ. Sci. Technol.

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The present study performs landcover modelling using the SLEUTH model. The urban land use changing factors are calibrated to predict the Land Use Land Cover (LULC) for a densely populated and developing smart city, Prayagraj, India. This research aims to use the SLEUTH model for simulating the future urban growth with the help of historical LULC (1990LULC ( -2020, road network and elevation data. The influence of road gravity and slope resistant coefficients is very significant in this study's outcome. The built-up area of the region increased from 40.22 km 2 (5.10% of total area) in 1990 to 85.89 km 2 (10.89%) in 2020. According to prediction results, in the next 20 years, the built-up growth rate would be 1.9% and approximated built-up area would be 118.66 km 2 (14.98%) in the year 2040. The quality of the result has been quantified in terms of best fit value of Optimal SLEUTH Metric (OSM) and validated against the existing LULC. The study utilises a spatially explicit urban growth model with 30 m resolution remote sensing data and provides future landuse of Prayagraj city.

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“…Urban researchers have studied various modelling techniques to estimate future urban growth, policy implementations and planning aspects to combat adverse effects on the environment. These techniques include cellular automata (CA) models (Sante et al, 2010), agent-based models (QuanLi et al, 2015), artificial neural network models (Yatoo et al, 2020), fuzzy and analytical hierarchical process (AHP) based model (Parry et al, 2018), and SLEUTH-UGM (Bharath et al, 2019;Chaudhuri and Clarke, 2019;Jafarnezhad et al, 2016;Wu et al, 2009). To predict land change, the preliminary step is to acknowledge the status of Spatio-temporal dynamics.…”

Section: Role Of Satellite Data and Models In Assessing City Dynamicsmentioning

confidence: 99%

Impact assessment of Corridor Oriented development

Chandrashekar

Aithal

2021

IRSPSD International

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Rapid urbanisation has been a factor affecting cities negatively and irreversibly in developing countries like India, adversely leading to depleting natural resources and promoting unbalanced and uneven urbanism. To handle the influx of population into core urban regions and to promote holistic, sustainable development, government and planning agencies are now looking upon regional development. Developing countries like India has laid plans for future urban corridor-oriented development. This study aims to understand the urban growth of two major developing cities influenced by transport corridor through a methodological approach using multi-temporal satellite data and its position in India's network of cities. Land use analysis was validated with the aid of measures such as overall accuracy and kappa statistics, with good values of more than 85% and 0.75 respectively were achieved. The hierarchical network analysis indicated five different clusters based on the urban growth rate. Among these clusters, Bangalore, Ahmedabad and Pune cluster was further shortlisted for analysis based on the urban transport corridor affecting the growth of these cities. Cellular automata-based SLEUTH model was adopted in this work to carefully observe sub-division level details of the region under the influence of the corridor. Exhaustive calibration, with three phases of coarse, fine and final, validation procedure along with statistical fit measures reveal urban expansion for Ahmedabad region has witnessed an increase from 497.50 km 2 (2017) to 826.24 km 2 (2025) while Pune region has experienced tremendous urban area transformation of 901.11 km 2 in the year 2025 against 497.27 km 2 in 2017. Results of this analysis would help policymakers and planners to inculcate decisions concerning future urban trends accommodating safer, healthier, sustainable and liveable urban ecosystem.

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Assessing land surface temperature and land use change through spatio-temporal analysis: a case study of select major cities of India

Cited by 30 publications

References 54 publications

Measurement report: Intra-annual Variability of Black/Brown Carbon and Its Interrelation with Meteorological Conditions over Gangtok, Sikkim

Measurement report: Intra-annual Variability of Black/Brown Carbon and Its Interrelation with Meteorological Conditions over Gangtok, Sikkim

Urban modelling and forecasting of landuse using SLEUTH model

Impact assessment of Corridor Oriented development

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