Spatio-temporal assessment of land use/ land cover dynamics and urban heat island of Jaipur city using satellite data

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn XL-8, Issue 1, 2014, Pages 767-772

  Jalan, Seema ^a   Sharma, Kavita ^b  

^a M L SUKHADIA UNIVERSITY   (India)

^b UNIVERSITY OF RAJASTHAN   (India)

Author keywords

Land cover; Land use; Landsat; Temperature; Urban

Indexed keywords

LAND USE; LANDFORMS; SATELLITE IMAGERY; SURFACE MEASUREMENT; SURFACE PROPERTIES; TEMPERATURE; VEGETATION;

LAND COVER; LAND SURFACE TEMPERATURE; LAND USE/ LAND COVERS; LAND USE/LAND COVER; LANDSAT; SPATIO-TEMPORAL CHANGES; SURFACE TEMPERATURES; URBAN;

ATMOSPHERIC TEMPERATURE;

EID: 84918536382     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5194/isprsarchives-XL-8-767-2014     Document Type: Conference Paper

References (27)

1. Buyantuyev A. and Wu, J., 2010. Urban heat islands and landscape heterogeneity: linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns. Landscape Ecology, 25, pp. 17-33.
2. Chen, X. L., Wang, Q., Zheng, J. and Xiaobin, L., 2002. A study on urban thermal field in summer based on satellite remote sensing. Remote Sensing for Land and Resources, 4, pp. 55-59.
3. Chen, X.L., Zhao, H.M., Li, P.X. and Yin, Z. Y., 2006. Remote sensing image-based analysis of the relation between urban heat island and land use /land cover changes. Remote Sensing of Environment, 104, pp. 133-146.
4. Dai, X., Zhongyang, G., Zhang, L. and Li, D., 2010. Spatiotemporal exploratory analysis of urban surface temperature field in Shanghai, China. Stochastic Environmental Research & Risk Assessment, 24, pp. 247-257.
5. Deosthali, V., 2000. Impact of rapid urban growth on heat and moisture islands in Pune City, India. Atmospheric Environment, 34, pp. 2745-2754.
6. Dousset, B. and Gourmelon, F., 2003. Satellite multi-sensor data analysis of urban surface temperatures and land cover. ISPRS Journal of Photogrammetry & Remote Sensing, 58, pp. 43-54.
7. Gallo, K.P., Tarpley, J.D. and McNab, A.L., 1995. Assessment of urban heat island: a satellite perspective. Atmospheric Research, 37, pp. 37-43.
8. Giridharan, R., Ganesan, S. and Lau, S. S. Y., 2004. Daytime urban heat island effect in high-rise and high-density residential developments in Hong Kong. Energy and Buildings, 36(6), pp. 525-534.
9. Janssen, M., 1998. Modeling Global Change- The Art of Integrated Assessment Modeling. Elgar, Edward
10. Keller, C.F., 2008. Global warming: a review of mostly settled issue. Stochastic Environmental Research & Risk Assessment, doi: 10.1007/s00477-008-0253-3.
11. Kim, Y. H. and Baik, J. J., 2002. Maximum Urban Heat Island Intensity in Seoul. Journal of Applied Meteorology, 41, pp. 651-653.
12. Li, L., Tan, Y., Ying, S., Yu, Z., Li, Z. and Lan, H., 2014. Impact of land cover and population density on land surface temperature: case study in Wuhan, China. Journal of Applied Remote Sensing, 8, doi: 1117/1.JRS.8.084993.
13. Nieuwolt, S., 1966. The urban microclimate of Singapore. The Journal of Tropical Geography, 22, pp. 30-37.
14. Oke, T. R., 1987. Boundary Layer Climates (2nd edition). Methuen, London, pp. 435.
15. Owen, T.W., Carlson, T.N. and Gillies, R.R.,1998. An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climate effect of urbanization. International Journal of Remote Sensing, 19, pp. 1663-1681.
16. Schott, J. R. and Volchok, W. J., 1985. Thematic Dapper thermal infrared calibration. Photogrammetric Engineering and Remote Sensing, 51(9), pp. 1351-1357.
17. Streutker, D. R., 2003. Satellite-measured growth of the urban heat island of Houston, Texas. Remote Sensing of Environment, 85, pp. 282-289.
18. Tamerius, J.D., Wise E.K., Uejio, C.K., McCoy, A.L. and Comrie A.C., 2007. Climate and human health: synthesizing environmental complexity and uncertainty. Stochastic Environmental Research & Risk Assessment, 21, pp. 601-613.
19. Tian, Q. and Xiangjun, M., 1998. Advances in study on vegetation indices. Advance in Earth Sciences, 13(4), pp. 327-333.
20. Wan, Z. and Dozier, J.A., 1996. Generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Trans Geosci Remote Sens, 34, pp. 892-905.
21. Weng, Q., 2009. Thermal infrared remote sensing for urban climate and environmental studies: methods, application and trends. ISPRS Journal of Photogrammetry and Remote Sensing, 64, pp. 335-344.
22. Weng, Q., Liu, H. and Lu, D., 2007. Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis, United States. Urban Ecosystems, 10, pp. 203-219.
23. Xiao, R., Weng, Q., Ouyang, Z., Li, W., Schienke, E.W. and Zhang, W., 2008. Land surface temperature variation and major factors in Beijing, China. Photogrammetric Engineering & Remote Sensing, 74 (4), pp. 451-461.
24. Yuan, F. and Bauer M.E., 2007. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface heat island effects in Landsat imagery. Remote Sensing of Environment, 106, pp. 375-386.
25. Census of India, 2001a. District census handbook, Town directory of Jaipur, Directorate of Census Operations, Rajasthan, India.
26. Census of India, 2011b. District census handbook, Town directory of Jaipur, Directorate of Census Operations, Rajasthan, India.
27. JDA, 2011. Master Plan handbook. Jaipur Development Authority, Jaipur, Rajasthan, India http://atmcorr.gsfc.nasa.gov