1. bookTom 15 (2022): Zeszyt 3 (December 2022)
Informacje o czasopiśmie
Pierwsze wydanie
20 Jun 2008
Częstotliwość wydawania
3 razy w roku
Otwarty dostęp

A Seasonal Investigation on Land Surface Temperature and Spectral Indices in Imphal City, India

Data publikacji: 08 Dec 2022
Tom & Zeszyt: Tom 15 (2022) - Zeszyt 3 (December 2022)
Zakres stron: 1 - 18
Otrzymano: 05 Aug 2022
Przyjęty: 14 Sep 2022
Informacje o czasopiśmie
Pierwsze wydanie
20 Jun 2008
Częstotliwość wydawania
3 razy w roku

Ali, J.M., Marsh, S.H., Smith, M.J. (2017). A comparison between London and Baghdad surface urban heat islands and possible engineering mitigation solutions. Sustain Cities Soc 29: 159-168. https://doi.org/10.1016/j.scs.2016.12.010 Search in Google Scholar

Arnfield, J. (2003). Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. Int J Climatol 23: 1–26. https://doi.org/10.1002/joc.859 Search in Google Scholar

Artis, D.A., Carnahan, W.H. (1982). Survey of emissivity variability in thermography of urban areas. Remote Sens Environ 12(4), 313–329.10.1016/0034-4257(82)90043-8 Search in Google Scholar

Balew, A., Korme, T. (2020). Monitoring land surface temperature in Bahir Dar city and its surrounding using Landsat images. Egypt J Remote Sens Space Sci https://doi.org/10.1016/j.ejrs.2020.02.001 Search in Google Scholar

Carlson, T.N., Ripley, D.A. (1997). On the Relation between NDVI, Fractional Vegetation Cover, and Leaf Area Index. Remote Sens Environ 62: 241-252. https://doi.org/10.1016/S0034-4257(97)00104-1 Search in Google Scholar

Chen, L., Li, M., Huang, F., Xu, S. (2013). Relationships of LST to NDBI and NDVI in Wuhan City based on Landsat ETM+ image. In 6th International Congress on Image and Signal Processing (CISP) (pp. 840-845), Hangzhou, 2013.10.1109/CISP.2013.6745282 Search in Google Scholar

Chen, X.L., Zhao, H.M., Li, P.X., Yi, Z.Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens Environ 104(2): 133–146. https://doi.org/10.1016/j.rse.2005.11.016 Search in Google Scholar

Chen, X., Zhang, Y. (2017). Impacts of urban surface characteristics on spatiotemporal pattern of land surface temperature in Kunming of China. Sustain Cities Soc. 32: 87-99. https://doi.org/10.1016/j.scs.2017.03.013 Search in Google Scholar

Deilami, K., Kamruzzaman, M., Liu, Y. (2018). Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures. Int J Appl Earth Obs Geoinf 67: 30-42. https://doi.org/10.1016/j.jag.2017.12.009 Search in Google Scholar

Equere, V., Mirzaei, P.A., Riffat, S. (2020). Definition of a new morphological parameter to improve prediction of urban heat island. Sustain Cities Soc 56: 102021. https://doi.org/10.1016/j.scs.2020.102021 Search in Google Scholar

Essa, W., Verbeiren, B., Van der Kwast, J., Van de Voorde, T., Batelaan, O. (2012)., Evaluation of the DisTrad thermal sharpening methodology for urban areas. Int J Appl Earth Obs Geoinf 19: 163-172. https://doi.org/10.1016/j.jag.2012.05.010 Search in Google Scholar

Feng, Y., Li, H., Tong, X., Chen, L., Liu, Y. (2018). Projection of land surface temperature considering the effects of future land change in the Taihu Lake Basin of China. Global Planet Change 167: 24-34. https://doi.org/10.1016/j.gloplacha.2018.05.007 Search in Google Scholar

Ferrelli, F., Huamantinco, M.A., Delgado, D.A., Piccolo, M.C. (2018). Spatial and temporal analysis of the LST-NDVI relationship for the study of land cover changes and their contribution to urban planning in Monte Hermoso, Argentina. Doc Anal Geogr 64 (1): 25-47. https://doi.org/10.5565/rev/dag.355 Search in Google Scholar

Feyisa, G.L., Meilby, H., Jenerette, G.D., Pauliet, S. (2016). Locally optimized separability enhancement indices for urban land cover mapping: Exploring thermal environmental consequences of rapid urbanization in Addis Ababa, Ethiopia. Remote Sens Environ 175: 14-31. https://doi.org/10.1016/j.rse.2015.12.026 Search in Google Scholar

Filho, WLFC, De Barros, Santiago, D., De Oliveira-Júnior, J.F., Da Silva Junior, C.A. (2019). Impact of urban decadal advance on land use and land cover and surface temperature in the city of Maceió, Brazil. Land Use Policy 87: 104026. https://doi.org/10.1016/j.landusepol.2019.104026 Search in Google Scholar

Gorgani, S.A., Panahi, M., Rezaie, F. (2013). The relationship between NDVI and LST in the Urban area of Mashhad, Iran. International Conference on Civil Engineering Architecture and Urban Sustainable Development. November, Tabriz, Iran. Search in Google Scholar

Guha, S., Govil, H. (2021). Annual assessment on the relationship between land surface temperature and six remote sensing indices using Landsat data from 1988 to 2019. Geocarto International. https://doi.org/10.1080/10106049.2021.1886339 Search in Google Scholar

Guha, S., Govil, H., Mukherjee, S. (2017). Dynamic analysis and ecological evaluation of urban heat islands in Raipur city, India. Journal of Applied Remote Sensing. 11(3): 036020. https://doi.org/10.1117/1.JRS.11.036020 Search in Google Scholar

Guha, S., Govil, H., Taloor, A.K., Gill, N., Dey, A. (2022). Land surface temperature and spectral indices: A seasonal study of Raipur City. Geodesy and Geodynamics. 13(1): 72-82. https://doi.org/10.1016/j.geog.2021.05.002 Search in Google Scholar

Jamei, Y., Rajagopalan, P., Sun, Q.C. (2019). Spatial structure of surface urban heat island and its relationship with vegetation and built-up areas in Melbourne, Australia. Sci Total Environ 659: 1335-1351. https://doi.org/10.1016/j.scitotenv.2018.12.30831096344 Search in Google Scholar

Kalota, D. (2017). Exploring relation of land surface temperature with selected variables using geographically weighted regression and ordinary least square methods in Manipur State, India. Geocarto Int 32(10): 1105-1119. https://doi.org/10.1080/10106049.2016.1195883 Search in Google Scholar

Liang, B.P., Li, Y., Chen, K.Z. (2012). A Research on Land Features and Correlation between NDVI and Land Surface Temperature in Guilin City. Remote Sens Tech Appl 27: 429–435. Search in Google Scholar

Li, J., Song, C., Cao, L., Meng, X., Wu, J. (2011). Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China. Remote Sens Environ 115: 3249–3263. Search in Google Scholar

Lopez, J.M.R., Heider, K., Scheffran, J. (2017). Frontiers of urbanization: Identifying and explaining urbanization hot spots in the south of Mexico City using human and remote sensing. Appl Geogr 79: 1-10. Search in Google Scholar

Ma, X., Peng, S. (2022). Research on the spatiotemporal coupling relationships between land use/land cover compositions or patterns and the surface urban heat island effect. Environ Sci Pollut Res Int 29(26): 39723-39742. https://doi.org/10.1007/s11356-022-18838-335107726 Search in Google Scholar

Maishella, A., Dewantoro, B.E.B., Aji, M.A.P. (2018). Correlation Analysis of Urban Development and Land Surface Temperature Using Google Earth Engine in Sleman Regency, Indonesia. IOP Conf. Series: Earth and Environmental Science 540 (2020) 012018. https://doi.org/10.1088/1755-1315/540/1/012018 Search in Google Scholar

Marzban, F., Sodoudi, S., Preusker, R. (2018). The influence of land-cover type on the relationship between LST-NDVI and LST-Tair. Int J Remote Sens 39(5): 1377-1398. https://doi.org/10.1080/01431161.2017.1462386 Search in Google Scholar

Mirzaei, P.A. (2015). Recent challenges in modeling of urban heat island. Sustain Cities Soc 19: 200–206. https://doi.org/10.1016/j.scs.2015.04.001 Search in Google Scholar

Mondal, A., Guha, S., Kundu, S. (2021). Dynamic status of land surface temperature and spectral indices in Imphal city, India from 1991 to 2021. Geomatics, Natural Hazards and Risk. 12(1): 3265-3286. https://doi.org/10.1080/19475705.2021.2008023 Search in Google Scholar

Mushore, T.D., Odindi, J., Dube, T., Matongera, T.N., Mutangam, O. (2017). Remote sensing applications in monitoring urban growth impacts on in-and-out door thermal conditions: A review. Remote Sens Appl Soc Environ 8: 83-93. https://doi.org/10.1016/j.rsase.2017.08.001 Search in Google Scholar

Nie, Q., Man, W., Li, Z., Huang, Y. (2016). Spatiotemporal Impact of Urban Impervious Surface on Land Surface Temperature in Shanghai, China. Can J Remote Sens 42(6): 680-689. http://dx.doi.org/10.1080/07038992.2016.121748410.1080/07038992.2016.1217484 Search in Google Scholar

Nimish, G., Bharath, H.A., Lalitha, A. (2020). Exploring temperature indices by deriving relationship between land surface temperature and urban landscape. Remote Sens Appl Soc Environ 18: 100299. https://doi.org/10.1016/j.rsase.2020.100299 Search in Google Scholar

Pearsall, H. (2017). Staying cool in the compact city: Vacant land and urban heating in Philadelphia, Pennsylvania. Appl Geogr 79: 84–92. http://dx.doi.org/10.1016/j.apgeop.2016.12.010 Search in Google Scholar

Peng, J., Xie, P., Liu, Y., Ma, J. (2016). Urban Thermal Environment Dynamics and Associated Landscape Pattern Factors: A Case Study in the Beijing Metropolitan Region. Remote Sens Environ 173: 145–155. Search in Google Scholar

Prehodko, L., Goward, S.N. (1997). Estimation of Air Temperature from Remotely Sensed Surface Observations. Remote Sens Environ 60: 335–346. https://doi:10.1016/S0034-4257(96)00216-710.1016/S0034-4257(96)00216-7 Search in Google Scholar

Rinner, C., Hussain, M. (2011). Toronto’s urban heat island exploring the relationship between land use and surface temperature. Remote Sens 3: 1251-1265. https://doi.org/10.3390/rs3061251 Search in Google Scholar

Rizwan, A.M., Dennis, L.Y.C., Liu, C. (2008). A review on the generation, determination and mitigation of Urban Heat Island. J Environ Sci 20: 120–128. Search in Google Scholar

Roy, S., Pandit, S., Eva, E.A., Bagmar, M.S.H., Papia, M., Banik, L., Dube, T., Rahman, F., Razi, M.A. (2020). Examining the nexus between land surface temperature and urban growth in Chattogram Metropolitan Area of Bangladesh using long term Landsat series data. Urban Clim 32: 100593. https://doi.org/10.1016/j.uclim.2020.100593 Search in Google Scholar

Sharma, R., Joshi, P.K. (2016). Mapping environmental impacts of rapid urbanization in the National Capital Region of India using remote sensing inputs. Urban Clim 15: 70–82. https://doi.org/10.1016/j.uclim.2016.01.004 Search in Google Scholar

Sobrino, J.A., 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 Search in Google Scholar

Sobrino, J.A., Jimenez-Munoz, J.C., Paolini, L. (2004). Land surface temperature retrieval from Landsat TM5. Remote Sens Environ 9: 434–440. https://doi:10.1016/j.rse.2004.02.00310.1016/j.rse.2004.02.003 Search in Google Scholar

Song, X., Hansen, M.C., Stehman, S.V., Potapov, P.V., Tyunkvina, A., Vermote, E.F., Townshend, J.R. (2018). Global land change from 1982 to 2016. Nature 560: 639–643. https://doi:10.1038/s41586-018-0411-910.1038/s41586-018-0411-9636633130089903 Search in Google Scholar

Son, N.T., Chen, C.F., Chen, C.R. (2020). Urban expansion and its impacts on local temperature in San Salvador, El Salvador. Urban Clim 32: 100617. https://doi.org/10.1016/j.uclim.2020.100617 Search in Google Scholar

Son, Y.S., Kang, M.K., Yoon, W.J. (2014). Lithological and mineralogical survey of the Oyu Tolgoi region, South-eastern Gobi, Mongolia using ASTER reflectance and emissivity data. Int J Appl Earth Obs Geoinf 26: 205–216. Search in Google Scholar

Song, J., Du, S., Feng, X., Guo, L. (2014). The Relationships Between Landscape Compositions and Land Surface Temperature: Quantifying Their Resolution Sensitivity With Spatial Correlation Models. Landsc Urban Plan 123: 145–157. Search in Google Scholar

Sun, D., Kafatos, M. (2007). Note on the NDVI-LST Relationship and the Use of Temperature-Related Drought Indices over North Aerica. Geophys Res Lett 34. http://doi:10.1029/2007GL03148510.1029/2007GL031485 Search in Google Scholar

Taripanah, F., Ranjbar, A. (2021). Quantitative analysis of spatial distribution of land surface temperature (LST) in relation Ecohydrological, terrain and socio- economic factors based on Landsat data in mountainous area. Adv Space Res 68(9): 3622-3640. https://doi.org/10.1016/j.asr.2021.07.008 Search in Google Scholar

Tucker, C.J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8(2): 127–150. Search in Google Scholar

Weng, Q.H., Lu, D.S., Schubring, J. (2004). Estimation of Land Surface Temperature–Vegetation Abundance Rela-tionship for Urban Heat Island Studies. Remote Sens Environ 89: 467-483. https://doi:10.1016/j.rse.2003.11.00510.1016/j.rse.2003.11.005 Search in Google Scholar

Xu, H. (2006). Modification of normalized difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27(14): 3025–3033. Search in Google Scholar

Yue, W., Xu, J., Tan, W., Xu, L. (2007). The Relationship between Land Surface Temperature and NDVI with Remote Sensing. Application to Shanghai Landsat 7 ETM+ data. Int J Remote Sens 28: 3205–3226. https://doi.org/10.1080/01431160500306906 Search in Google Scholar

Zhang, Y., Odeh, I.O.A., Han, C. (2009). Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis. Int J Appl Earth Obs Geoinf 11(4): 256-264. https://doi.org/10.1016/j.jag.2009.03.001 Search in Google Scholar

Zhao, H.M., Chen, X.L. (2005). Use of normalized difference bareness index in quickly mapping bare areas from TM/ETM+. Geoscience and Remote Sensing Symposium, 3(25–29): 1666−1668. https://doi.org/10.1109/IGARSS.2005.1526319 Search in Google Scholar

Zhao, M., Cai, H., Qiao, Z., Xu, X. (2016). Influence of urban expansion on the urban heat island effect in Shanghai. Int J Geogr Inf Sci 30(12): 2421–2441. https://doi.org/10.1080/13658816.2016.1178389 Search in Google Scholar

Zha, Y., Gao, J., Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int J Remote Sens 24(3): 583-594. https://doi.org/10.1080/01431160304987 Search in Google Scholar

Website: http://earthexplorer.usgs.gov/ https://earth.google.com/web/ https://imc.mn.gov.in/ Search in Google Scholar

Polecane artykuły z Trend MD

Zaplanuj zdalną konferencję ze Sciendo