1. bookVolume 14 (2021): Issue 3 (December 2021)
Zeitschriftendaten
License
Format
Zeitschrift
Erstveröffentlichung
20 Jun 2008
Erscheinungsweise
3 Hefte pro Jahr
Sprachen
Englisch
access type Open Access

Analysis of Land Use Land Cover Changes with Land Surface Temperature Using Spatial-Temporal Data for Nagpur City, India

Online veröffentlicht: 18 Jan 2022
Seitenbereich: 52 - 64
Eingereicht: 13 Jul 2021
Akzeptiert: 16 Aug 2021
Zeitschriftendaten
License
Format
Zeitschrift
Erstveröffentlichung
20 Jun 2008
Erscheinungsweise
3 Hefte pro Jahr
Sprachen
Englisch

Akyürek, D., Koç, Ö., Akbaba, E. M., & Sunar, F. (2018). Land Use/Land Cover Change Detection Using Multi–Temporal Satellite Dataset: A Case Study in Istanbul New Airport. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-3/W4, 17-22. https://doi.org/10.5194/isprs-archives-XLII-3-W4-17-201810.5194/isprs-archives-XLII-3-W4-17-2018 Search in Google Scholar

Alves, D. S., & L Skole, D. (1996). Characterizing land cover dynamics using multi-temporal imagery. International Journal of Remote Sensing, 17(4), 835-839. https://doi.org/10.1080/0143116960894904910.1080/01431169608949049 Search in Google Scholar

Bokaie, M., Zarkesh, M. K., Arasteh, P. D., & Hosseini, A. (2016). Assessment of Urban Heat Island based on the relationship between land surface temperature and Land Use/Land Cover in Tehran. Sustainable Cities and Society, 23, 94-104. https://doi.org/https://doi.org/10.1016/j.scs.2016.03.00910.1016/j.scs.2016.03.009 Search in Google Scholar

Brus, J., Pechanec, V., & Machar, I. (2018). Depiction of uncertainty in the visually interpreted land cover data. Ecological Informatics, 47, 10-13. https://doi.org/10.1016/j.ecoinf.2017.10.01510.1016/j.ecoinf.2017.10.015 Search in Google Scholar

Census. (2011). DistrictCensusHandbook (DCHB). Search in Google Scholar

Chen, X.-L., Zhao, H.-M., Li, P.-X., & Yin, Z.-Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104(2), 133-146. https://doi.org/https://doi.org/10.1016/j.rse.2005.11.01610.1016/j.rse.2005.11.016 Search in Google Scholar

Corner, R. J., Dewan, A. M., & Chakma, S. (2014). Monitoring and Prediction of Land-Use and Land-Cover (LULC) Change. In A. Dewan & R. Corner (Eds.), Dhaka Megacity: Geospatial Perspectives on Urbanisation, Environment and Health (pp. 75-97). Springer Netherlands. https://doi.org/10.1007/978-94-007-6735-5_510.1007/978-94-007-6735-5_5 Search in Google Scholar

Das, N., Mondal, P., Sutradhar, S., & Ghosh, R. (2021). Assessment of variation of land use/land cover and its impact on land surface temperature of Asansol subdivision. The Egyptian Journal of Remote Sensing and Space Science, 24(1), 131-149. https://doi.org/https://doi.org/10.1016/j.ejrs.2020.05.00110.1016/j.ejrs.2020.05.001 Search in Google Scholar

Dutta, S., & Guchhait, S. K. (2020). Assessment of land use land cover dynamics and urban growth of Kanksa Block in Paschim Barddhaman District, West Bengal. GeoJournal. https://doi.org/10.1007/s10708-020-10292-310.1007/s10708-020-10292-3 Search in Google Scholar

Fonseka, H. P. U., Zhang, H., Sun, Y., Su, H., Lin, H., & Lin, Y. (2019). Urbanization and Its Impacts on Land Surface Temperature in Colombo Metropolitan Area, Sri Lanka, from 1988 to 2016. Remote Sensing, 11(8), 957. https://www.mdpi.com/2072-4292/11/8/95710.3390/rs11080957 Search in Google Scholar

Fu, P., & Weng, Q. (2016). A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery. Remote Sensing of Environment, 175, 205-214. https://doi.org/https://doi.org/10.1016/j.rse.2015.12.04010.1016/j.rse.2015.12.040 Search in Google Scholar

Gazi, M. Y., Rahman, M. Z., Uddin, M. M., & Rahman, F. M. A. (2020). Spatio-temporal dynamic land cover changes and their impacts on the urban thermal environment in the Chittagong metropolitan area, Bangladesh. GeoJournal. https://doi.org/10.1007/s10708-020-10178-410.1007/s10708-020-10178-4 Search in Google Scholar

Ghosh, S., Chatterjee, N. D., & Dinda, S. (2019). Relation between urban biophysical composition and dynamics of land surface temperature in the Kolkata metropolitan area: a GIS and statistical based analysis for sustainable planning. Modeling Earth Systems and Environment, 5(1), 307-329. https://doi.org/10.1007/s40808-018-0535-910.1007/s40808-018-0535-9 Search in Google Scholar

Khan, F., & Das, B. (2021, 2021/06/01). Geospatial approach to determine Soil bearing capacity of Nagpur city, Maharashtra India IOP Conference Series: Earth and Environmental Science, http://dx.doi.org/10.1088/1755-1315/796/1/01206910.1088/1755-1315/796/1/012069 Search in Google Scholar

Khan, F., Das, B., Ram Krishna Mishra, S., & Awasthy, M. (2021). A review on the Feasibility and Application of Geospatial Techniques in Geotechnical Engineering Field. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2021.02.10810.1016/j.matpr.2021.02.108 Search in Google Scholar

Khandelwal, S., Goyal, R., Kaul, N., & Mathew, A. (2018). Assessment of land surface temperature variation due to change in elevation of area surrounding Jaipur, India. The Egyptian Journal of Remote Sensing and Space Science, 21(1), 87-94. https://doi.org/https://doi.org/10.1016/j.ejrs.2017.01.00510.1016/j.ejrs.2017.01.005 Search in Google Scholar

Kumar, M., Tripathi, D. K., Maitri, V., & Biswas, V. (2017). Impact of Urbanisation on Land Surface Temperature in Nagpur, Maharashtra. In P. Sharma & S. Rajput (Eds.), Sustainable Smart Cities in India: Challenges and Future Perspectives (pp. 227-241). Springer International Publishing. https://doi.org/10.1007/978-3-319-47145-7_1510.1007/978-3-319-47145-7_15 Search in Google Scholar

Mahmood, R., Pielke, R. A., Hubbard, K. G., Niyogi, D., Bonan, G., Lawrence, P., McNider, R., McAlpine, C., Etter, A., Gameda, S., Qian, B., Carleton, A., Beltran-Przekurat, A., Chase, T., Quintanar, A. I., Adegoke, J. O., Vezhapparambu, S., Conner, G., Asefi, S., Sertel, E., Legates, D. R., Wu, Y., Hale, R., Frauenfeld, O. W., Watts, A., Shepherd, M., Mitra, C., Anantharaj, V. G., Fall, S., Lund, R., Treviño, A., Blanken, P., Du, J., Chang, H.-I., Leeper, R., Nair, U. S., Dobler, S., Deo, R., & Syktus, J. (2010). Impacts of Land Use/Land Cover Change on Climate and Future Research Priorities. Bulletin of the American Meteorological Society, 91(1), 37-46. https://doi.org/10.1175/2009bams2769.110.1175/2009BAMS2769.1 Search in Google Scholar

Mishra, P. K., Rai, A., & Rai, S. C. (2020). Land use and land cover change detection using geospatial techniques in the Sikkim Himalaya, India. The Egyptian Journal of Remote Sensing and Space Science, 23(2), 133-143. https://doi.org/10.1016/j.ejrs.2019.02.00110.1016/j.ejrs.2019.02.001 Search in Google Scholar

Mitsuda, Y., & Ito, S. (2011). A review of spatial-explicit factors determining spatial distribution of land use/land-use change. Landscape and Ecological Engineering, 7(1), 117-125. https://doi.org/10.1007/s11355-010-0113-410.1007/s11355-010-0113-4 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 Sensing of Environment, 173, 145-155. https://doi.org/https://doi.org/10.1016/j.rse.2015.11.02710.1016/j.rse.2015.11.027 Search in Google Scholar

Sahana, M., Ahmed, R., & Sajjad, H. (2016). Analyzing land surface temperature distribution in response to land use/land cover change using split window algorithm and spectral radiance model in Sundarban Biosphere Reserve, India. Modeling Earth Systems and Environment, 2(2), 81. https://doi.org/10.1007/s40808-016-0135-510.1007/s40808-016-0135-5 Search in Google Scholar

Sakhre, S., Dey, J., Vijay, R., & Kumar, R. (2020). Geospatial assessment of land surface temperature in Nagpur, India: an impact of urbanization. Environmental Earth Sciences, 79(10), 226. https://doi.org/10.1007/s12665-020-08952-110.1007/s12665-020-08952-1 Search in Google Scholar

Sansare, D. A., & Mhaske, S. Y. (2020). Land use change mapping and its impact on storm water runoff using Remote sensing and GIS: a case study of Mumbai, India. IOP Conference Series: Earth and Environmental Science, 500, 012082. https://doi.org/10.1088/1755-1315/500/1/01208210.1088/1755-1315/500/1/012082 Search in Google Scholar

Sansare, D. A., & Mhaske, S. Y. (2020). Natural hazard assessment and mapping using remote sensing and QGIS tools for Mumbai city, India. Natural Hazards, 100(3), 1117-1136. https://doi.org/10.1007/s11069-019-03852-510.1007/s11069-019-03852-5 Search in Google Scholar

Sobrino, J. A., Jiménez-Muñoz, J. C., & Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90(4), 434-440. https://doi.org/https://doi.org/10.1016/j.rse.2004.02.00310.1016/j.rse.2004.02.003 Search in Google Scholar

United Nations. (2018). World Urbanization Prospects: The 2018 Revision, Methodology. (ESA/P/WP.252). Retrieved December 8, 2020, from https://population.un.org/wup/Publications/Files/WUP2018-Methodology.pdf Search in Google Scholar

Urgessa, T., & Lemessa, D. (2020). Spatiotemporal Landuse Land Cover Changes in Walmara District, Central Oromia, Ethiopia. Earth Sciences, 9(1). https://doi.org/10.11648/j.earth.20200901.1410.11648/j.earth.20200901.14 Search in Google Scholar

USGS. (2017). Landsat 8 OLI and TIRS Calibration Notices. Retrieved December 8, 2020, from https://www.usgs.gov/core-science-systems/nli/landsat/landsat-8-oli-and-tirs-calibration-notices Search in Google Scholar

USGS. (2019). Landsat 8 (L8)Data Users Handbook (Vol. version 5). USGS. Search in Google Scholar

Weng, Q. (2001). A remote sensing?GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing, 22(10), 1999-2014. https://doi.org/10.1080/71386078810.1080/713860788 Search in Google Scholar

Yao, R., Wang, L., Huang, X., Niu, Z., Liu, F., & Wang, Q. (2017). Temporal trends of surface urban heat islands and associated determinants in major Chinese cities. Science of The Total Environment, 609, 742-754. https://doi.org/https://doi.org/10.1016/j.scitotenv.2017.07.21710.1016/j.scitotenv.2017.07.217 Search in Google Scholar

Yu, W., Zang, S., Wu, C., Liu, W., & Na, X. (2011). Analyzing and modeling land use land cover change (LUCC) in the Daqing City, China. Applied Geography, 31(2), 600-608. https://doi.org/https://doi.org/10.1016/j.apgeog.2010.11.01910.1016/j.apgeog.2010.11.019 Search in Google Scholar

Yuan, F., & Bauer, M. E. (2007). Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of Environment, 106(3), 375-386. https://doi.org/https://doi.org/10.1016/j.rse.2006.09.00310.1016/j.rse.2006.09.003 Search in Google Scholar

Zhou, D., Zhao, S., Liu, S., Zhang, L., & Zhu, C. (2014). Surface urban heat island in China's 32 major cities: Spatial patterns and drivers. Remote Sensing of Environment, 152, 51-61. https://doi.org/https://doi.org/10.1016/j.rse.2014.05.01710.1016/j.rse.2014.05.017 Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo