PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Analyzing dynamic behavior of land use and land surface temperature in the city of Imphal, India

Autorzy
Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The study has been conducted over the Imphal city using multi-temporal satellite imageries. The study investigated the pattern land surface temperature (LST) development over the hill city of Imphal and its relation to land use pattern and population density. The result revealed an ascending growth of LST as a consequence of population growth and rapid land use dynamics. The Imphal city exhibited a remarkable change in the land use structure, especially in the built-up land, vegetation and crop land. Addition of built-up land of 667.44 hectares in the city territory has consequently upsurged the mean LST of the city from 23.23 °C to 30.30 °C in summer and 14.74–18.10 °C in winter during the period of 26 years (1994–2020). Summer season witnessed a consistently increasing intensity of LST in the city whereas winter depicted a completely opposite scenario during 1994–2020. Among all the land use classes, built-up land expressed maximum LST dynamics in both seasons during the period 1994 to 2020. The high positive correlation coefficient between built-up land with LST and strong negative correlation between vegetation cover and LST paved the way for maximum LST development in the city province.
Słowa kluczowe
Czasopismo
Rocznik
Strony
2275--2290
Opis fizyczny
Bibliogr. 37 poz.
Twórcy
Bibliografia
  • 1. Achmad A, Hasyim S, Dahlan B, Aulia DN (2015) Modeling of Urban growth in tsunami-prone city using logistic regression: analysis of Banda Aceh, Indonesia. Appl Geo 62:237–246. https://doi.org/10.1016/j.apgeog.2015.05.001
  • 2. Artis DA, Carnahan WH (1982) Survey of emissivity variability in thermography of urban areas. Remote Sens Environ 12:313–329
  • 3. Cammerer H, Thieken AH, Verburg PH (2013) Spatiotemporal dynamics in the flood exposure due to land use changes in the Alpine Lech Valley in Tyrol (Austria)”. Nat Hazards 68:1243–1270. https://doi.org/10.1007/s11069-012-0280-8
  • 4. Dale VH, Santer BD, Wigley TML, Boyle GJSDJ, Hnilo JJ, Nychka D et al (1997) Statistical significance of trends and trend differences in layer-average atmospheric temperature time series”. J Geophys Res 105(1):7337–7356
  • 5. Dubovyk O, Sliuzas R, Flacke J (2011) Spatio-temporal modeling of informal settlement development in Sancaktepe District, Istanbul, Turkey”. ISPRS J Photog Rem Sens. https://doi.org/10.1016/j.isprsjprs.2010.10.002
  • 6. Government of Manipur. City Development Plan: Imphal, Imphal Municipal Council. http://manipur.gov.in/IMC/CDP_Imphal.pdf
  • 7. Grimm NB, Faeth SH, Golubiewski NE et al (2008) Global change and the ecology of cities. Science 319:756–760
  • 8. Khan MMH, Bryceson I, Kolivras KN, Faruque F, Rahman MM, Haque U (2014) Natural disasters and land use/ land-cover change in the Southwest Coastal Areas of Bangladesh. Reg Environ Change 15:241–250. https://doi.org/10.1007/s10113-014-0642-8
  • 9. Kruse PW, McGlauchlin LD, McQuistan RB (1962) Elements of infrared technology: generation, transmission and detection, Wiley, NewYork
  • 10. Kumar P, Husain A, Singh RB et al (2018) Impact of land cover change on land surface temperature: a case study of Spiti Valley. J Mt Sci. https://doi.org/10.1007/s11629-018-4902-9
  • 11. Li X, Zhou W, Ouyang Z (2013a) Forty years of urban expansion in beijing: what is the relative importance of physical, socioeconomic, and neighborhood factors? Appl Geogr 38:1–10. https://doi.org/10.1016/j.apgeog.2012.11.004
  • 12. Li Z-L, Tang B-H, Wu H et al (2013b) Satellite-derived land surface temperature: current status and perspectives. Remote Sens Environ 131:14–37
  • 13. Lu D, Mausel P, Brondizio E, Moran E (2002) Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research. Int J Remote Sens 23(13):2651–2671. https://doi.org/10.1080/01431160110109642
  • 14. Mallick J, Kant Y, Bharath B (2008) Estimation of Land Surface Temperature over Delhi Using Landsat-7 ETM+. J Indian Geophys Union 12:131–140
  • 15. Mustafa A, Heppenstall A, Omrani H, Saadi I, Cools M, Teller J (2018) Modelling built-up expansion and densification with multinomial logistic regression, cellular automata and genetic algorithm”. Comput Environ Urban Syst 67:147–156. https://doi.org/10.1016/j.compenvurbsys.2017.09.009
  • 16. Mustafa EK, Co Y, Liu G, Kaloop MR, Beshr AA, Zarzoura F, Sadek M (2020) Study for predicting land surface temperature (LST) using landsat data: a comparison of four algorithms. Adv Civ Eng. https://doi.org/10.1155/2020/7363546
  • 17. Myneni CJ, Chapman L, Ornes JE, Baker C (2011) Remote sensing land surface temperature for meteorology and climatology: a review. Meteorolog Appl 18(3):296–306
  • 18. Ndossi MI, Avdan U (2016) Application of open source coding technologies in the production of Land Surface Temperature (LST) maps from Landsat: A PyQGIS plugin. Remote Sens 8:413
  • 19. Neog R (2021) Evaluation of temporal dynamics of land use and land surface temperature (LST) in Agartala city of India. Environ Dev Sustain. https://doi.org/10.1007/s10668-021-01572-0
  • 20. Neog R, Acharjee S, Hazarika J (2020) Spatiotemporal analysis of road surface temperature (RST) and building wall temperature (BWT) and its relation to the traffic volume at Jorhat urban environment India. Environ Dev Sustain. https://doi.org/10.1007/s10668-020-01047-8
  • 21. Pal S, Akoma O (2009) Water scarcity in wetland area within kandi block of West Bengal: a hydro-ecological assessment. Ethiopc J Environ Stud Manag. https://doi.org/10.4314/ejesm.v2i3.48260
  • 22. Pawe CK, Saikia A (2018) Unplanned urban growth: land use/land cover change in the Guwahati Metropolitan Area. India Geografisk Tidsskrift-Danish Journal of Geography 118(1):88–100
  • 23. Rimal B, Sharma R, Kunwar R, Keshtkar H, Stork NE, Rijal S, Rahman SA, Baral H (2019) Effects of land use and land cover change on ecosystem services in the Koshi River Basin. Eastern Nepal Ecosyst Serv 38:100963. https://doi.org/10.1016/j.ecoser.2019.100963
  • 24. Sagan C, Toon OB, Pollack JB (1979) Anthropogenic albedo changes and the earth’s climate. Science 206:1363–1368. https://doi.org/10.1126/science.206.4425.1363
  • 25. Sajib MQU, Wang T (2020) Estimation of land surface temperature in an agricultural region of Bangladesh from Landsat 8: intercomparison of four algorithms. Sensors 20:1778. https://doi.org/10.3390/s20061778
  • 26. Singh AM, Devi KR (2016) Land use and land cover change detection of fringe areas of Imphal City Manipur, India, IOSR Journal of Humanities and Social Science (IOSR-JHSS), 21(2), 09–16
  • 27. Sinha S, Pandey PC, Sharma LK, Nathawat MS, Kumar P, Kanga S (2014) Remote estimation of land surface temperature for different lulc features of a moist deciduous tropical forest region. Remote Sensing Applications in Environmental Research; Springer: Berlin. Germany; Heidelberg, Germany, pp 57–68
  • 28. Sobrino U, Jovanovska G (2016) Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data. J Sens. https://doi.org/10.1155/2016/1480307
  • 29. Tang BH, Wu H, Li C, Li ZL (2011) Estimation of broadband surface emissivity from narrowband emissivities. Opt Express 19:185–192
  • 30. Thome KJ, Biggar SF, Gellman DL, Slater PN (1994) Absoluteradiometric calibration of Landsat-5 thematic mapper and the proposed calibration of the advanced space borne thermal emission and reflection radiometer. Paper presented at the geosciences and remote sensing symposium, 1994. IGARSS’94. Surface and atmospheric remote sensing: technologies, data analysis and interpretation. https://doi.org/10.1109/IGARSS.1994.399718.
  • 31. Trotter L, Dewan A, Robinson T (2017) Effects of rapid urbanization on the urban thermal environment between 1990 and 2011 in Dhaka Megacity Bangladesh. AIMS Environ Sci 4:145–167
  • 32. Tungnung Z and Anand S (2017). Dynamics of urban sprawl and land use change in Imphal of Manipur, India, space and culture, India, https://doi.org/10.20896/saci.v5i2
  • 33. Vandegriend A, Owe M, Vugts H, Ramothwa G (1992) Botswana water and surface energy balance research program. Part 1: Integrated approach and field campaign results; NASA Goddard Space Flight Center: Greenbelt, MD, USA
  • 34. Wang, S.L.L. (2012). Chapter 8—Land-surface temperature and thermal infrared emissivity. In advanced remote sensing; Wang, S.L.L., Ed.; Academic Press: Boston, FL, USA, pp. 235–271
  • 35. Yambem S (2018) Urban risks to hazards: a study of the Imphal Urban Area. Develop Disast Manag. https://doi.org/10.1007/978-981-10-8485-0_23
  • 36. Zhang J, Wang Y, Li YA (2006) C++ program for retrieving land surface temperature from the data of landsat TM/ETM+ band6. Comput Geosci 32:1796–1805
  • 37. Zhu W, Lu A, Jia S (2013) Estimation of daily maximum and minimum air temperature using modis land surface temperature products. Remote Sens Environ 130:62–73. https://doi.org/10.1016/j.rse.2012.10.034
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7733ebe8-3ac5-48c1-934a-8e70d278a6b2
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.