Alpopi, C., Manole, C., & Colesca, S. E. (2011). Assessment of the sustainable urban development level through the use of indicators of sustainability. Theoretical and Empirical Researches in Urban Management, 6(2), 78-87.
Abd El-Kawy, O. R., Rød, J. K., Ismail, H. A., & Suliman, A. S. (2011). Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data. Applied geography, 31(2), 483-494. https://doi.org/10.1016/j.apgeog.2010.10.012
Alsharif, A. A., & Pradhan, B. (2014). Urban sprawl analysis of Tripoli Metropolitan city (Libya) using remote sensing data and multivariate logistic regression model. Journal of the Indian Society of Remote Sensing, 42(1), 149-163. https://doi.org/10.1007/s12524-013-0299-7
Avdan U & Jovanovska G. (2016). Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data. Journal of Sensors, 2016. Cohen J. (1968). Weighted kappa: nominal scale agreement provision for scaled disagreement or partial credit. Psychological bulletin, 70(4), 213. https://psycnet.apa.org/doi/10.1037/h0026256
Aithal, B. H., & Ramachandra, T. V. (2016). Visualization of urban growth pattern in Chennai using geoinformatics and spatial metrics. Journal of the Indian Society of Remote Sensing, 44(4), 617-633. https://doi.org/10.1007/s12524-015-0482-0
Bhatta, B., Saraswati, S., & Bandyopadhyay, D. (2010). Urban sprawl measurement from remote sensing data. Applied geography, 30(4), 731-740. https://doi.org/10.1016/j.apgeog.2010.02.002
Belal, A. A., & Moghanm, F. S. (2011). Detecting urban growth using remote sensing and GIS techniques in Al Gharbiya governorate, Egypt. The Egyptian Journal of Remote Sensing and Space Science, 14(2), 73-79. https://doi.org/10.1016/j.ejrs.2011.09.001
Bharath, H. A., Chandan, M. C., Vinay, S., & Ramachandra, T. V. (2017). Modelling the growth of two rapidly urbanizing Indian cities. Journal of Geomatics, 11(12), 149-166.
Ca L, Li P, Zhang L & Chen T. (2008). Remote sensing image-based analysis of the relationship between urban heat island and vegetation fraction. The international Archives of Photogrammetry, remote sensing and spatial information sciences, 37.
Cheruto MC, Kauti MK, Kisangau DP, & Kariuki PC. (2016). Assessment of land use and land cover change using GIS and remote sensing techniques: a case study of Makueni County, Kenya. http://repository.seku.ac.ke/handle/123456789/3062
Chatterjee, N. D., Chatterjee, S., & Khan, A. (2016). Spatial modeling of urban sprawl around Greater Bhubaneswar city, India. Modeling Earth Systems and Environment, 2(1), 14.
Chettry, V., & Surawar, M. Assessment of urban sprawl characteristics in Indian cities using remote sensing: case studies of Patna, Ranchi, and Srinagar. Environment, Development and Sustainability, 1-23. https://doi.org/10.1007/s10668-020-01149-3
Dadras, M., Shafri, H. Z., Ahmad, N., Pradhan, B., & Safarpour, S. (2015). Spatio-temporal analysis of urban growth from remote sensing data in Bandar Abbas city, Iran. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 35-52. https://doi.org/10.1016/j.ejrs.2015.03.005
Dhali, M. K., Chakraborty, M., & Sahana, M. (2019). Assessing spatio-temporal growth of urban sub-centre using Shannon’s entropy model and principle component analysis: A case from North 24 Parganas, lower Ganga River Basin, India. The Egyptian Journal of Remote Sensing and Space Science, 22(1), 25-35. https://doi.org/10.1016/j.ejrs.2018.02.002
Dadashpoor, H., & Salarian, F. (2020). Urban sprawl on natural lands: Analyzing and predicting the trend of land use changes and sprawl in Mazandaran city region, Iran. Environment, Development and Sustainability, 22(2), 593-614. https://doi.org/10.1007/s10668-018-0211-2
Fang, S., Gertner, G. Z., Sun, Z., & Anderson, A. A. (2005). The impact of interactions in spatial simulation of the dynamics of urban sprawl. Landscape and urban planning, 73(4), 294-306. https://doi.org/10.1016/j.landurbplan.2004.08.006
Frenkel, A., & Ashkenazi, M. (2008). Measuring urban sprawl: how can we deal with it?. Environment and Planning B: Planning and Design, 35(1), 56-79. https://doi.org/10.1068%2Fb32155
Fertner, C., Jørgensen, G., Nielsen, T. A. S., & Nilsson, K. S. B. (2016). Urban sprawl and growth management–drivers, impacts and responses in selected European and US cities. Future cities and environment, 2(1), 1-13. https://doi.org/10.1186/s40984-016-0022-2
Fei, W., & Zhao, S. (2019). Urban land expansion in China's six megacities from 1978 to 2015. Science of The Total Environment, 664, 60-71. https://doi.org/10.1016/j.scitotenv.2019.02.008
Gutman G Huang C, Chander G, Noojipady P & Masek JG. (2013). Assessment of the NASA–USGS global land survey (GLS) datasets. Remote sensing of environment, 134, 249-265.
Gazi MA & Mondal I. (2018). Urban Heat Island and its effect on Dweller of Kolkata Metropolitan area using geospatial techniques. International Journal of Computer Sciences and Engineering, 6(10), 741-753.
Hassan Z, Shabbir R, Ahmad SS, Malik AH, Aziz N, Butt A & Erum S. (2016). Dynamics of land use and land cover change (LULCC) using geospatial techniques: a case study of Islamabad Pakistan. Springer Plus, 5(1), 812. https://doi.org/10.1186/s40064-016-2414-z.
Halder B, Banik P & Bandyopadhyay J. Mapping and monitoring land dynamic due to urban expansion using geospatial techniques on South Kolkata. Saf. Extreme Environ. (2021). https://doi.org/10.1007/s42797-021-00032-2
Inostroza, L., Baur, R., & Csaplovics, E. (2013). Urban sprawl and fragmentation in Latin America: A dynamic quantification and characterization of spatial patterns. Journal of environmental management, 115, 87-97. https://doi.org/10.1016/j.jenvman.2012.11.007
Ji, W., Ma, J., Twibell, R. W., & Underhill, K. (2006). Characterizing urban sprawl using multi-stage remote sensing images and landscape metrics. Computers, Environment and Urban Systems, 30(6), 861-879. https://doi.org/10.1016/j.compenvurbsys.2005.09.002
Jensen R, Mausel P, Dias N, Gonser R, Yang C, Everitt J, & Fletcher R. (2007). Spectral analysis of coastal vegetation and land cover using AISA+ hyperspectral data. Geocarto International, 22(1), 17-28. https://doi.org/10.1080/10106040701204354
Jat, M. K., Garg, P. K., & Khare, D. (2008). Monitoring and modelling of urban sprawl using remote sensing and GIS techniques. International journal of Applied earth Observation and Geoinformation, 10(1), 26-43. https://doi.org/10.1016/j.jag.2007.04.002
Kadhim, N., Mourshed, M., & Bray, M. (2016). Advances in remote sensing applications for urban sustainability. Euro-Mediterranean Journal for Environmental Integration, 1(1), 1-22. https://doi.org/10.1007/s41207-016-0007-4
Lu D & Weng Q. (2006). Use of impervious surface in urban land-use classification. Remote Sensing of Environment, 102(1-2), 146-160. https://doi.org/10.1016/j.rse.2006.02.010
Kumar, J., Biswas, B., & Walker, S. (2020). Multi-temporal LULC Classification using Hybrid Approach and Monitoring Built-up Growth with Shannon’s Entropy for a Semi-arid Region of Rajasthan, India. Journal of the Geological Society of India, 95(6), 626-635. https://doi.org/10.1007/s12594-020-1489-x
Meshesha TW, Tripathi SK. & Khare D. (2016). Analyses of land use and land cover change dynamics using GIS and remote sensing during 1984 and 2015 in the Beressa Watershed Northern Central Highland of Ethiopia. Modeling Earth Systems and Environment, 2(4), 1-12. https://link.springer.com/article/10.1007/s40808-016-0233-4
Mosammam, H. M., Nia, J. T., Khani, H., Teymouri, A., & Kazemi, M. (2017). Monitoring land use change and measuring urban sprawl based on its spatial forms: The case of Qom city. The Egyptian Journal of Remote Sensing and Space Science, 20(1), 103-116. https://doi.org/10.1016/j.ejrs.2016.08.002
MohanRajan, S. N., Loganathan, A., & Manoharan, P. (2020). Survey on Land Use/Land Cover (LU/LC) change analysis in remote sensing and GIS environment: Techniques and Challenges. Environmental Science and Pollution Research, 27, 29900-29926. https://doi.org/10.1007/s11356-020-09091-7
Owojori A & Xie H. (2005, March). Landsat image-based LULC changes of San Antonio, Texas using advanced atmospheric correction and object-oriented image analysis approaches. In 5th international symposium on remote sensing of urban areas, Tempe, AZ.
Ozturk, D. (2017). Assessment of urban sprawl using Shannon’s entropy and fractal analysis: a case study of Atakum, Ilkadim and Canik (Samsun, Turkey). Journal of environmental engineering and landscape management, 25(3), 264-276. https://doi.org/10.3846/16486897.2016.1233881
Punia, M., & Singh, L. (2012). Entropy approach for assessment of urban growth: a case study of Jaipur, India. Journal of the Indian Society of Remote Sensing, 40(2), 231-244. https://doi.org/10.1007/s12524-011-0141-z
Patra, S., Sahoo, S., Mishra, P., & Mahapatra, S. C. (2018). Impacts of urbanization on land use/cover changes and its probable implications on local climate and groundwater level. Journal of Urban Management, 7(2), 70-84. https://doi.org/10.1016/j.jum.2018.04.006
Ramachandra, T. V., Bharath, H. A., & Vinay, S. (2013). Land use land cover dynamics in a rapidly urbanising landscape. SCIT J, 13, 1-12.
Roy DP, Wulder MA, Loveland TR, Woodcock CE, Allen RG, Anderson MC., ... & Zhu Z. (2014). Landsat-8: Science and product vision for terrestrial global change research. Remote sensing of Environment, 145, 154-172.
Rasul A, Balzter H & Smith C. (2015). Spatial variation of the daytime Surface Urban Cool Island during the dry season in Erbil, Iraqi Kurdistan, from Landsat 8. Urban climate, 14, 176-186.
Rawat, J. S., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 77-84. https://doi.org/10.1016/j.ejrs.2015.02.002
Rubiera Morollón, F., González Marroquin, V. M., & Pérez Rivero, J. L. (2016). Urban sprawl in Spain: differences among cities and causes. European Planning Studies, 24(1), 207-226. https://doi.org/10.1080/09654313.2015.1080230
Rahman, M., Avtar, R., Yunus, A. P., Dou, J., Misra, P., Takeuchi, W., ... & Agustiono Kurniawan, T. (2020). Monitoring effect of spatial growth on land surface temperature in Dhaka. Remote Sensing, 12(7), 1191. https://doi.org/10.3390/rs12071191
Ramaiah, M., Avtar, R., & Rahman, M. (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
Semenza JC, Rubin CH, Falter KH, Selanikio JD, Flanders WD, Howe HL, & Wilhelm JL. (1996). Heat-related deaths during the July 1995 heat wave in Chicago. New England journal of medicine, 335(2), 84-90.
Sobrino JA, Raissouni N & Li ZL. (2001). A comparative study of land surface emissivity retrieval from NOAA data. Remote Sensing of Environment, 75(2), 256-266. https://doi.org/10.1016/S0034-4257(00)00171-1
Sudhira, H. S., Ramachandra, T. V., & Jagadish, K. S. (2004). Urban sprawl: metrics, dynamics and modelling using GIS. International Journal of Applied Earth Observation and Geoinformation, 5(1), 29-39. https://doi.org/10.1016/j.jag.2003.08.002
Sun, H., Forsythe, W. & Waters, N. Modeling Urban Land Use Change and Urban Sprawl: Calgary, Alberta, Canada. Netw Spat Econ 7, 353–376 (2007). https://doi.org/10.1007/s11067-007-9030-y
Sarvestani, M. S., Ibrahim, A. L., & Kanaroglou, P. (2011). Three decades of urban growth in the city of Shiraz, Iran: A remote sensing and geographic information systems application. Cities, 28(4), 320-329. https://doi.org/10.1016/j.cities.2011.03.002
Sandhya Kiran, G., & Joshi, U. B. (2013). Estimation of variables explaining urbanization concomitant with land-use change: a spatial approach. International Journal of Remote Sensing, 34(3), 824-847. https://doi.org/10.1080/01431161.2012.720738
Scarano M & Sobrino JA. (2015). On the relationship between the sky view factor and the land surface temperature derived by Landsat-8 images in Bari, Italy. International Journal of Remote Sensing, 36(19-20), 4820-4835.
Srivastava, A., Sahoo, B., Raghuwanshi, N. S., & Singh, R. (2017). Evaluation of variable-infiltration capacity model and MODIS-terra satellite-derived grid-scale evapotranspiration estimates in a River Basin with Tropical Monsoon-Type climatology. Journal of Irrigation and Drainage Engineering, 143(8), 04017028.
Singh, S. K., Srivastava, P. K., Szabó, S., Petropoulos, G. P., Gupta, M., & Islam, T. (2017). Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets. Geocarto international, 32(2), 113-127. https://doi.org/10.1080/10106049.2015.1130084
Sahani, S., & Raghavaswamy, V. (2018). Decoding patterns of urban dynamics in class-1 city of khammam, Telangana State, India. Journal of the Indian Society of Remote Sensing, 46(5), 749-759. https://doi.org/10.1007/s12524-017-0718-2
Sisodia, P. S., Tiwari, V., & Dahiya, A. K. (2018). Urban sprawl monitoring using remote sensing and GIS techniques of the city Jaipur, India. In E-Planning and Collaboration: Concepts, Methodologies, Tools, and Applications (pp. 716-728). IGI Global.
Sahana, M., Hong, H., & Sajjad, H. (2018). Analyzing urban spatial patterns and trend of urban growth using urban sprawl matrix: A study on Kolkata urban agglomeration, India. Science of the Total Environment, 628, 1557-1566. https://doi.org/10.1016/j.scitotenv.2018.02.170
Shukla, A., & Jain, K. (2019). Modeling urban growth trajectories and spatiotemporal pattern: a case study of Lucknow City, India. Journal of the Indian Society of Remote Sensing, 47(1), 139-152. https://doi.org/10.1007/s12524-018-0880-1
Shooshtari, S. J., Silva, T., Namin, B. R., & Shayesteh, K. (2020). Land use and cover change assessment and dynamic spatial modeling in the Ghara-su Basin, Northeastern Iran. Journal of the Indian Society of Remote Sensing, 48(1), 81-95. https://doi.org/10.1007/s12524-019-01054-x
Tewolde, M. G., & Cabral, P. (2011). Urban sprawl analysis and modeling in Asmara, Eritrea. Remote Sensing, 3(10), 2148-2165. https://doi.org/10.3390/rs3102148
USGS (2001) Landsat Science Data User’s handbooks https://www.usgs.gov/land-resources/nli/landsat/landsat- 8-data-users-handbook
Verzosa, L. C. O., & Gonzalez, R. M. (2010). Remote sensing, geographic information systems and Shannon’s entropy: Measuring urban sprawl in a mountainous environment.
Vani, M., & Prasad, P. R. C. (2020). Assessment of spatio-temporal changes in land use and land cover, urban sprawl, and land surface temperature in and around Vijayawada city, India. Environment, Development and Sustainability, 22(4), 3079-3095. https://doi.org/10.1007/s10668-019-00335-2
Weng Q & Lo CP. (2001). Spatial analysis of urban growth impacts on vegetative greenness with Landsat TM data. Geocarto international, 16(4), 19-28.
Weber, C., & Puissant, A. (2003). Urbanisation pressure and modelling of urban growth: Example of the Tunis Metropolitan Area. Remote Sensing of Environment, 86(3), 341–352.
Wu, Y., Li, S., & Yu, S. (2016). Monitoring urban expansion and its effects on land use and land cover changes in Guangzhou city, China. Environmental monitoring and assessment, 188(1), 54.
Xiao H & Weng Q. (2007). The impact of land use and land cover changes on land surface temperature in a karst area of China. Journal of environmental management, 85(1), 245-257.
Yeh, A. G. O., & Li, X. (2001). Measurement and monitoring of urban sprawl in a rapidly growing region using entropy. Photogrammetric engineering and remote sensing, 67(1), 83-90.
Yu X, Guo X & Wu Z. (2014). Land surface temperature retrieval from Landsat 8 TIRS—Comparison between radiative transfer equation-based method, split window algorithm and single channel method. Remote sensing, 6(10), 9829-9852.