Analysis of the relationship among land surface temperature (LST), land use land cover (LULC), and normalized difference vegetation index (NDVI) with topographic elements in the lower Himalayan region

Ullah, Waheed; Ahmad, Khalid; Ullah, Siddique; Tahir, Adnan Ahmad; Javed, Muhammad Faisal; Nazir, Abdul; Abbasi, Arshad Mehmood; Mohamed, Abdullah

doi:10.1016/j.heliyon.2023.e13322

Cited by 42 publications

(12 citation statements)

References 46 publications

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“…Areas with more built-up lands are often warmer than their surroundings. Our finding on built up area has experienced higher LST is similar with other previous researchers like Tran et al (2017), Karakus, (2019), Simwanda et al (2019), Hassan et al (2021) and Ullah et al (2023).…”

Section: Discussionsupporting

confidence: 92%

Monitoring land use land cover transformations and its effects on land surface temperature using geospatial approach in Jharsuguda District, Odisha, India

Mansingh,

Kujur,

Sahoo

et al. 2024

EEC

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The aim of the work was to analyse Land use land cover (LU/LC) changes and their correlation with the increased Land surface temperature (LST) in Jharsuguda district, Odisha using geospatial techniques and transformation analysis in ArcGIS 10.4 software. Remotely sensed data from Landsat 8 operational land imager (OLI) for March 2013 and Landsat 9 OLI for March 2023 were utilized to investigate LU/LC and LST changes. The satellite data was classified using the maximum likelihood supervised classification algorithm (MLSC) to derive LULC maps. The overall accuracy of these classified LULC maps was determined to be more than 85% in both years. In order to obtain LST information from the satellite images, the spectral radiance model was utilized. The findings of the study revealed a clear correlation between the loss of vegetation cover (VC) and the expansion of built-up areas, which consequently contributed to an increase in the urban heat islands (UHI). The LU/LC estimation indicates substantial changes in the landscape over the past ten years. Specifically, there was a notable net increase in urban area (UA) by 55.12%, while very dense forest (VDF) experienced a reduction of 49.28%, moderately dense forest (MDF) decreased by 18.60%, and open forest (OF) by 42.58% as well as non-forest (NF) by 1.76% between 2013 and 2023. Furthermore, the study observed that the maximum temperature of the city rises from 46.8°C in 2013 to 48.3°C in 2023. So, the municipal authority can take new decision policies and management to reduce the effects of LST for sustainable development in the further future.

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Section: Discussionsupporting

confidence: 92%

Monitoring land use land cover transformations and its effects on land surface temperature using geospatial approach in Jharsuguda District, Odisha, India

Mansingh,

Kujur,

Sahoo

et al. 2024

EEC

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“…The study revealed that vegetation in Kaduna Metropolis is significantly declining. This is similar to findings of Richards and Belcher (2019) that the global south is experiencing decline in urban vegetation cover, and all over the world, decrease in vegetation health and density is linked in increase in land surface temperature (Ullah et al, 2023). Furthermore, the study also found an increase in the distribution and intensity of land surface temperature.…”

Section: Implicationsupporting

confidence: 89%

Assessment of the Relationship Between Land Surface Temperature and Vegetation Using Modis Ndvi and LST Timeseries Data in Kaduna Metropolis, Nigeria

Abubakar,

Thomas,

Ahmed

et al. 2024

FJS

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This study assessed the relationship between land surface temperature (LST) and vegetation using MODIS NDVI and LST timeseries data in Kaduna Metropolis. MOD13Q1 and MOD11A2 datasets were accessed using Google Earth Engine. Mann-Kendall trend test was used to analyse the trends in LST and NDVI. Pearson Moment Correlation Coefficient and Linear Regression were used to examine the relationship between LST and NDVI. Mann-Kendall trend test revealed monotonic downward trend in NDVI with a Z-statistics of -1.2758, but upward trend in daytime and nighttime LST, with a Z-statistics of 0.567 and 2.107 respectively. For the relationship, vegetation showed strong negative relationship with daytime LST with -0.704. Vegetation also showed weak positive relationship with nighttime LST. The linear regression analysis revealed that vegetation was able to predict 49.5% of LST in Kaduna Metropolis, with R2 value of 0.495 and a standard error of estimate is 2.459. The study concluded that loss of vegetation is responsible for the increase in land surface temperature. The study therefore recommended regulatory agencies should ensure that trees are planted whenever they are removed due to infrastructural development in order to prevent UHI phenomenon and planting of trees should be encouraged in order to regulate the urban climate.

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“…Moreover, the findings indicated that the expansion of artificial surfaces comes at the expense of vegetation cover, a factor crucial for maintaining equilibrium among land surface and atmospheric parameters [72][73][74]. Recent studies [16,72,75] have argued that transition in LC classes, specifically an extension of artificial surfaces, affects the LST and severely influences the local and regional climate. The diversity in surface roughness and reflectance among different land cover classes leads to corresponding variations in the absorption and radiation of energy [76][77][78].…”

Section: Discussionmentioning

confidence: 99%

Investigating Land Cover Changes and Their Impact on Land Surface Temperature in Khyber Pakhtunkhwa, Pakistan

Ul Hussan,

Li,

Liu

et al. 2024

Sustainability

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Restoration of degraded land is a significant concern in the 21st century in order to combat the impacts of climate change. For this reason, the provisional government of Khyber Pakhtunkhwa (KPK), Pakistan, initialized a Billion Tree Tsunami Project (BTTP) in 2013 and finished it in 2017. Although a few researchers have investigated the land use transitions under BTTP in the short term by merging all the vegetation types into one, analysis of the long-term benefits of the project and future persistence were missing. Furthermore, the previous studies have not discussed whether the prime objective of the BTTP was achieved. Considering the existing gaps, this research mainly involves analyzing (i) fluctuations in the green fraction by employing a land change modeler (LCM), along with the spatial location of gain-loss and exchange analysis using a high-resolution dataset (GLC30); (ii) forest cover changes under the influence of the BTTP; (iii) impacts of green fraction changes towards land surface temperature (LST) by utilizing the less-explored technique of curve fit linear regression modeling (CFLR); and finally, (iv) assessing the persistence of the NDVI and LST trends by employing the Hurst exponent. Research findings indicate that as an output of BTTP, despite the government’s claim of increasing the forest cover by 2%, a significant gain of grassland (3904.87 km2) was observed at the cost of bare land. In comparison, the overall increase in forest cover was only 0.39%, which does not satisfy the main objective of this project. On the other hand, the CFLRM-based actual contributions of land cover change (LCC) transition to LST indicate a significant decline in LST in the areas with gains in green fraction for both grassland and forest. At the same time, an increase was observed with reverse transitions. Although the results appear positive for climatic impacts in the short term, the HURST model-based persistence analysis revealed that the spatial locations of increasing vegetation and decreasing LST trends fall under the weakly persistent category, therefore these trends may not continue in the near future. Despite some positive impact on LST attributed to the green fraction increase, this project cannot be regarded as a complete success due to its failure to achieve its prime objective.

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Analysis of the relationship among land surface temperature (LST), land use land cover (LULC), and normalized difference vegetation index (NDVI) with topographic elements in the lower Himalayan region

Cited by 42 publications

References 46 publications

Monitoring land use land cover transformations and its effects on land surface temperature using geospatial approach in Jharsuguda District, Odisha, India

Monitoring land use land cover transformations and its effects on land surface temperature using geospatial approach in Jharsuguda District, Odisha, India

Assessment of the Relationship Between Land Surface Temperature and Vegetation Using Modis Ndvi and LST Timeseries Data in Kaduna Metropolis, Nigeria

Investigating Land Cover Changes and Their Impact on Land Surface Temperature in Khyber Pakhtunkhwa, Pakistan

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