Estimation of impacts of land use and land cover (LULC) changes on land surface temperature (LST) within greater Imphal urban area using geospatial technique

• Autorzy: Khan Rahul , Aribam Bindiya , Alam Wazir

Identyfikatory

DOI

10.1007/s11600-023-01159-5

• Języki publikacji: EN

Abstrakty

EN

The rapid increase in the urbanisation process and other developmental activities across the globe have increased the land surface temperature of built-up areas which is considered as an emerging urban environmental problem. The rapid unplanned urban sprawl has influenced the land use and land cover of the urban area leading to the development of the phenomenon of Urban Heat Island. The present study highlights how land use and land cover changes have impacted the land surface temperature and urban heat islands phenomenon in the greater Imphal city of Manipur in India. The study was carried out with multi-spectral and multi-temporal satellite imageries of 1988, 2000, 2011, and 2021, respectively. The extracted information from the rectified imageries highlights a significant increase in the land surface temperature in the built-up area of the city. The findings illustrate that the maximum and minimum LST of the Imphal urban area has significantly increased from 28.77 to 31.25℃ and 10.44 to 11.47℃, respectively, for the month of February from 1988 to 2021. The increase in land surface temperature is directly attributed to the increased built-up area (24.06% to 44.85%) and reduction in the urban forest cover (28.17% to 16.65%). Cumulatively, there is a 2.44℃ and 1.03℃ rise in maximum and minimum LST over three decades. The variability in the LST shows positive correlations with the NDBI and negative correlations with NDVI. The study witnessed nearly about 0.74℃ (maximum) and 0.31℃ (minimum) decadal changes in the overall LST in the greater Imphal area.

Słowa kluczowe

EN

land surface temperature; urban heat island; land use and land cover; NDBI; NDVI

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2023
• Tom: Vol. 71, no. 6
• Strony: 2811--2823
• Opis fizyczny: Bibliogr. 39 poz., rys., tab.

Twórcy

autor

Khan Rahul

• Department of Forestry and Environmental Science, Manipur University, Imphal, Manipur, 795003, India

autor

Aribam Bindiya

• Department of Forestry and Environmental Science, Manipur University, Imphal, Manipur, 795003, India

autor

Alam Wazir

• Department of Forestry and Environmental Science, Manipur University, Imphal, Manipur, 795003, India

• https://orcid.org/0000-0002-6043-7795

Bibliografia

• 1. Adebowale BI, Kayode SE (2015) Geospatial assessment of urban expansion and land surface temperature in Akure, Nigeria. In: Proceedings of the ICUC9—9th international conference on urban climate jointly with 12th Symposium on the Urban Environment, Toulouse, France, pp 20–24
• 2. Artis DA, Carnahan WH (1982) Survey of emissivity variability in thermography of urban areas. Remote Sens Environ 12(4):313–329. https://doi.org/10.1016/0034-4257(82)90043-8
• 3. Caprotti F (2018) Future cities: moving from technical to human needs. Palgrave Commun 4(35):1–4. https://doi.org/10.1057/s41599-018-0089-5
• 4. Carlson TN, Ripley DA (1997) The relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens Environ 62(3):241–252. https://doi.org/10.1016/S0034-4257(97)00104-1
• 5. Census (2011) District Census Handbook, Bishnupur, Census of India, Series 15, Part XII-B. Directorate of Census Operation, Government of Manipur
• 6. Congedo L (2013) Semi-automatic classification plugin for QGIS. Sapienza University, Rome
• 7. Dhar RB, Chakraborty S, Chattopadhyay R, Sikdar PK (2019) Impact of land-use/land-cover change on land surface temperature using satellite data: a case study of Rajarhat Block, North 24-Parganas District, West Bengal. J Ind Soc Remote Sens 47:331–348. https://doi.org/10.1007/s12524-019-00939-1
• 8. Dissanayake DMSLB (2020) Land use change and its impacts on land surface temperature in Galle city, Sri Lanka. Climate 8(5):65. https://doi.org/10.3390/cli8050065
• 9. Gaur A, Eichenbaum MK, Simonovic SP (2018) Analysis and modelling of surface urban Heat Island in 20 Canadian cities under climate and land-cover change. J Environ Manag 206:145–157. https://doi.org/10.1016/j.jenvman.2017.10.002
• 10. Guha S, Govil H, Mukherjee S (2017) Dynamic analysis and ecological evaluation of urban heat islands in Raipur city, India. J Appl Remot Sens 11(3):036020. https://doi.org/10.1117/1.JRS.11.036020
• 11. Hay A (1988) The derivation of global estimates from a confusion matrix. Int J Remote Sens 9(8):1395–1398
• 12. Huang S, Tang L, Hupy JP, Wang Y, Shao G (2021) A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. J For Res 32:1–6. https://doi.org/10.1007/s11676-020-01155-1
• 13. Kumar P, Husain A, Singh RB, Kumar M (2018) Impact of land cover change on land surface temperature: a case study of Spiti Valley. J Mt Sci 15(8):1658–1670. https://doi.org/10.1007/s11629-018-4902-9
• 14. Mohan M, Pathan SK, Narendrareddy K, Kandya A, Pandey S (2011) Dynamics of urbanization and its impact on land-use/land-cover: a case study of megacity Delhi. J Environ Prot 2(09):1274. https://doi.org/10.4236/jep.2011.29147
• 15. Mondal A, Guha S, Kundu S (2021) Dynamic status of land surface temperature and spectral indices in Imphal city, India from 1991 to 2021. Geomat Nat Hazards Risk 12(1):3265–3286. https://doi.org/10.1080/19475705.2021.2008023
• 16. MoUD (2016) Annual Report 2016-17, Ministry of Urban Development, Government of India, Govt. of India Press, New Delhi
• 17. MSAPCC (2013) Manipur State Action Plan for Climate Change, Directorate of Environment. Govt. of Manipur, India
• 18. Neog R (2021) Analyzing dynamic behaviour of land use and land surface temperature in the city of Imphal, India. Acta Geophys 69:2275–2290. https://doi.org/10.1007/s11600-021-00659-6
• 19. Nungate R, Alam W (2022) Traffic noise pollution assessment in major road junctions of Imphal City, Manipur (India). Nat Environ Poll Technol 21(2):457–468
• 20. Pal S, Ziaul S (2017) Detection of land use and land cover change and land surface temperature in English Bazar urban centre. Egypt J Remote Sens Space Sci 20(1):125–145. https://doi.org/10.1016/j.ejrs.2016.11.003
• 21. Petropoulos GP, Kalivas DP, Georgopoulou IA, Srivastava PK (2015) Urban vegetation cover extraction from hyperspectral imagery and geographic information system spatial analysis techniques: case of Athens, Greece. J Appl Remote Sens 9(1):096088. https://doi.org/10.1117/1.JRS.9.096088
• 22. Ramaiah M, Avtar R, Rahman MM (2020) Land cover influences on LST in two proposed smart cities of India: comparative analysis using spectral indices. Land 9(9):292. https://doi.org/10.3390/land9090292
• 23. Ranagalage M, Estoque RC, Zhang X, Murayama Y (2018) Spatial changes of urban heat island formation in the Colombo District, Sri Lanka: implications for sustainability planning. Sustainability 10(5):1367. https://doi.org/10.3390/su10051367
• 24. Rehman Z, Kazmi SJH, Khanum F, Samoon ZA (2015) Analysis of land surface temperature and NDVI using geospatial technique: a case study of Keti Bunder, Sindh, Pakistan. J Basic App Sci 11:514–527. https://doi.org/10.6000/1927-5129.2015.11.69
• 25. Rizwan AM, Dennis LY, Chunho LIU (2008) A review on the generation, determination and mitigation of Urban Heat Island. J Environ Sci 20(1):120–128. https://doi.org/10.1016/S1001-0742(08)60019-4
• 26. Shukla A, Jain K (2021) Analyzing the impact of changing landscape pattern and dynamics on land surface temperature in Lucknow city, India. Urban For Urban Green 58:1268–1277. https://doi.org/10.1016/j.ufug.2020.126877
• 27. Singh KP, Golson N (2019) A study in the trends and pattern of urbanization of Manipur during last five decades (1951–2011). Trans Inst Ind Georg 41(1):99–110
• 28. Singh SI, Sharma P, Chaudhary S, Sharma MG, Yegemova S, Kumar R (2019) Assessment of ponds surrounding Imphal Valley on the basis of various biological and physicochemical parameters. Lakes Reserv 24(4):324–331. https://doi.org/10.1111/lre.12286
• 29. Sobrino JA, Raissouni N, Li Z (2001) A comparative study of land surface emissivity retrieval from NOAA data. Remote Sens Environ 75(2):256–266. https://doi.org/10.1016/S0034-4257(00)00171-1
• 30. Sobrino JA, Jimenez-Munoz JC, Paolini L (2004) Land surface temperature retrieval from Landsat TM5. Remote Sens Environ 90(4):434–440. https://doi.org/10.1016/j.rse.2004.02.003
• 31. Suckall N, Fraser E, Forster P, Mkwambisi D (2015) Using a migration systems approach to understand the link between climate change and Urbanization in Malawi. Appl Georg 63:244–252. https://doi.org/10.1016/j.apgeog.2015.07.004
• 32. Sun L, Chen J, Li Q, Huang D (2020) Dramatic uneven urbanization of large cities throughout the world in recent decades. Nat Comm 11(1):1–9. https://doi.org/10.1038/s41467-020-19158-1
• 33. UNFPA (2022) State of the World’s Population report, Ensuring rights and choices for all, United Nations Population Fund’s, 605, Third Avenue, New York
• 34. USGS (2022) United States Geological Survey (USGS) Landsat Missions: Landsat Science Products. https://www.usgs.gov/land-resources/nli/landsat/landsat-science-products. Accessed 7 July 2021
• 35. Van Rossum G (2007) Python programming language. In: USENIX annual technical conference, 31, p 36
• 36. Yambem S (2018) Urban risks to hazards: a study of the Imphal urban area. In: Singh A, Punia M, Haran N, Singh T (eds) Development and disaster management. Palgrave Macmillan, Singapore. https://doi.org/10.1007/978-981-10-8485-0_23.
• 37. Yang L, Qian F, Song DX, Zheng KJ (2016) Research on urban heat-island effect. Proc Eng 169:11–18. https://doi.org/10.1016/j.proeng.2016.10.002
• 38. Zhang J, Wang Y, Li Y (2006) A C++ program for retrieving land surface temperature from the data of Landsat TM/ETM+ band6. Comput Geosci 32(10):1796–1805. https://doi.org/10.1016/j.cageo.2006.05.001
• 39. Zhou X, Chen H (2018) Impact of urbanization-related land use land cover changes and urban morphology changes on the urban heat island phenomenon. Sci Total Environ 635:1467–1476. https://doi.org/10.1016/j.scitotenv.2018.04.091

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).