Detection of Land-Use and Surface Temperature Change at Different Resolutions

DOI: 10.4236/jgis.2012.43024   PDF   HTML     9,353 Downloads   15,018 Views   Citations


Understanding the relationship between land-use/land-cover change (LULCC) and environment is seriously important to manage arid land. However, information on how environmental factors influence the LULCC patterns at different scales in arid area is lacking. This paper investigates the application of RS/GIS for detecting LULCC and assessing its impact on surface temperature in the Ismailia Governorate, Egypt. Landsat images have been utilized to quantify the changes from 1984 to 2011. The images were pre-processed using calibration techniques and the geometric and atmos- pheric corrections were performed. Different ratios, indices, and optimized index factor were implemented to decide the best band combination. Supervised classification using Maximum Likelihood technique and spatial reclassification have been employed. Six land-use/land-cover categories (urban, vegetation, waterlogged 1 and 2, bare land, and water) were identified. The highest overall accuracy and Kappa coefficient is 93.04% and 80.65%, respectively. The integration of RS and GIS was further applied to examine the impact of land-use change on surface temperatures. The results revealed a notable land-use change in the study area. The Built-up area has rapidly increased in Ismailia during the 27 years pe- riod. The built-up area (37.65?C in 1984 and 43.876?C in 2011) and Barren land (37.34?C in 1984 and 42.801?C in 2011) exhibit the highest surface radiant temperature, while vegetated surfaces (28.73?C in 1984 and 32.96?C in 2011), water (25.94?C in 1984 and 27.32?C in 2011), waterlogged1 (34.54?C in 1984 and 35.60?C in 2011) recorded low radiant temperature respectively. Waterlogged2 is the class that shows an unexpected radiant temperature (26.38?C in 1984 and 27.75?C in 2011). The urban development between 1984 and 2011 has given rise to an average of 6.23?C in surface radiant temperature. During 27 years, the change rate of land-use types which are decreased are barren land (1.12% an- nually) and waterlogged1 and 2 (0.76 and 6.61% annually). The area of vegetation, water, and built-up are increased by 0.98%, 0.82%, and 0.61% per year, respectively.

Share and Cite:

E. Omran, "Detection of Land-Use and Surface Temperature Change at Different Resolutions," Journal of Geographic Information System, Vol. 4 No. 3, 2012, pp. 189-203. doi: 10.4236/jgis.2012.43024.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] G. Kirk, “Views on the Future of Soil Science,” In: A. Hartemink, Ed., The Future of Soil Sciences, International Union of Soil Sciences, 2006.
[2] El. E. Omran, “Is Soil Science Dead and Buried? Future Image in the world of 10 billion people,” CATRINA, Vol. 3, No. 2, 2008, pp. 59-68.
[3] W. N. Adger, N. W. Arnell and E. L. Tompkins, “Successful Adaptation to Climate Change across Scales,” Global Environmental Change, Vol. 15, No. 2, 2005, pp. 77-86. doi:10.1016/j.gloenvcha.2004.12.005
[4] E. Erle and P. Robert, “Land-Use and Land-Cover Change,” In: J. C. Cutler, Ed., Encyclopedia of Earth, Environmental Information Coalition, National Council for Science and the Environment, Washington DC, 2010.
[5] J. A. Foley, R. DeFries, G. P. Asner, C. Barford and G. Bonan, “Global Consequences of Land Use,” Science, Vol. 309, No. 5734, 2005, pp. 570-574. doi:10.1126/science.1111772
[6] J. K. Parikh and K. Parikh, “Climate Change: India’s Perceptions, Positions, Policies and Possibilities,” India Gandhi Institute of Development Research, 2002.
[7] UNFCCC, “Climate Change: Impacts, Vulnerabilities and Adaptation in Developing Countries,” United Nations Framework Convention on Climate Change, 2007.
[8] El. E. Omran, “A Proposed Simplified Method to Improve Land-Use Mapping Accuracy,” Agricultural Research Journal, Vol. 9, No. 3, 2009, pp. 123-132.
[9] R. Manonmani and D. S. Mary, “Remote Sensing and GIS Application In Change Detection Study In Urban Zone Using Multi Temporal Satellite,” International Journal of Geomatics and Geosciences, Vol. 1, No. 1, 2010.
[10] V. G. Pece, “Assessment of Land Use and Land Cover Changes around Ohrid and Prespa Lakes Using Landsat Imagery,” BALWOIS, Ohrid, Republic of Macedonia, 2008.
[11] Z. Qiming, L. Baolin and S. Bo, “Modelling Spatio-Temporal Pattern of Landuse Change Using Multi- temporal Remotely Sensed Imagery,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part B7, 2008.
[12] R. Sel?uk, “Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey,” Sensors, Vol. 8, No. 10, 2008, pp. 6188-6202. doi:10.3390/s8106188
[13] M. T. Wubet, “Estimation of Absolute Surface Temperature by Satellite Remote Sensing,” M.Sc Thesis, International Institute for Geoinformation Science and Earth Observation, Netherlands, 2003.
[14] R. C. Balling and S. W. Brazell, “High Resolution Surface Temperature Patterns in a Complex Urban Terrain,” Photogrammetric Engineering & Remote Sensing, Vol. 54, No. 9, 1988, pp. 1289-1293.
[15] K. P. Gallo, A. L. McNab, T. R. Karl, J. F. Brown, J. J. Hood and J. D. Tarpley, “The Use of NOAA AVHRR Data for Assessment of the Urban Heat Island Effect,” Journal of Applied Meteorology, Vol. 32, No. 5, 1993, pp. 899-908. doi:10.1175/1520-0450(1993)032<0899:TUONAD>2.0.CO;2
[16] S. Q. Kidder and H. T. Wu, “A Multispectral Study of the St. Louis Area under Snow Covered Conditions Using NOAA-7 AVHRR Data,” Remote Sensing of Environment, Vol. 22, No. 2, 1987, pp. 159-172. doi:10.1016/0034-4257(87)90056-3
[17] M. Roth, T. R. Oke and W. J. Emery, “Satellite Derived Urban Heat Islands from Three Coastal Cities and the Utilisation of Such Data in Urban Climatology,” International Journal of Remote Sensing, Vol. 10, No. 11, 1989, pp. 1699-1720. doi:10.1080/01431168908904002
[18] W. H. Carnahan and R. C. Larson, “An Analysis of an Urban Heat Sink,” Remote Sensing of Environment, Vol. 33, No. 1, 1990, pp. 65-71. doi:10.1016/0034-4257(90)90056-R
[19] Q. Weng, “Fractal Analysis of Satellite-Detected Urban Heat Island Effect,” Photogrammetric Engineering & Remote Sensing, Vol. 69, No. 5, 2003, pp. 555-566.
[20] Q. Weng, “Thermal Infrared Remote Sensing for Urban Climate and Environmental Studies: Methods, Applications, and Trends,” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 64, No. 4, 2009, pp. 335-344. doi:10.1016/j.isprsjprs.2009.03.007
[21] M. Reda and El. E. Omran, “Strategy for the Exploitation of Land Resources to Ismailia Governorate until 2017,” 1997 (Unpublished report).
[22] F. Sabins, “Remote Sensing: Principles and Interpretation,” WH Freeman & Co., New York, 1996.
[23] A. Almutairi and A. T. Warner, “Change Detection Accuracy and Image Properties: A Study Using Simulated Data,” Remote Sensing, Vol. 2, No. 6, 2010, pp. 1508- 1529. doi:10.3390/rs2061508
[24] P. C. Alexandre and W. Eleonore, “Change Detection for Updates of Vector Database through Region-Based Classification of VHR Satellite Data,” Proceedings of SPIE, Vol. 6749, 2007, pp. 11-10.
[25] J. Gong, H. Sui, G. Ma and Q. Zhou, “A Review of Multi-Temporal Remote Sensing Data Change Detection Algorithms,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part B7, 2008.
[26] A. Singh, “Digital Change Detection Techniques Using Remotely Sensed Data,” International Journal of Remote Sensing, Vol. 10, No. 6, 1989, pp. 989-1003. doi:10.1080/01431168908903939
[27] D. Yuan, C. D. Elvidge and R. S. Lunetta, “Survey of MULTISPECTRAL methods for Land Cover Change Analysis,” In: R. S. Lunetta and C. D. Elvidge, Eds., Remote Sensing Change Detection: Environmental Monitoring Methods and Applications, Taylor & Francis, London, 1999, pp. 21-39.
[28] G. Chander, B. L. Markham and D. L. Helder, “Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors,” Remote Sensing of Environment, Vol. 113, No. 5, 2009, pp. 893-903. doi:10.1016/j.rse.2009.01.007
[29] K. P. Gallo, A. L. McNab, T. R. Karl, J. F. Brown, J. J. Hood and J. D. Tarpley, “The Use of a Vegetation Index for Assessment of the Urban Heat Island Effect,” International Journal of Remote Sensing, Vol. 14, No. 11, 1993, pp. 2223-2230. doi:10.1080/01431169308954031
[30] R. R. Gillies and T. N. Carlson, “Thermal Remote Sensing of Surface Soil Water Content with Partial Vegetation Cover for Incorporation into Climate Models,” Journal of Applied Meteorology, Vol. 34, 1995, pp. 745-756. doi:10.1175/1520-0450(1995)034<0745:TRSOSS>2.0.CO;2
[31] C. T. Kok, S. L. Hwee, Z. M. Mohd and A. Khiruddin, “Landsat Data to Evaluate Urban Expansion and Determine Land Use/Land Cover Changes in Penang Island, Malaysia,” Environmental Earth Sciences, Vol. 60, No. 7, 2010, pp. 1509-1521. doi:10.1007/s12665-009-0286-z
[32] K. R. Martha, C. C. Josefino, A. W. Donald and V. David, “Relationship between Satellite-Derived Land Surface Temperatures, Arctic Vegetation Types, and NDVI,” Remote Sensing of Environment, Vol. 112, No. 4, 2008, pp. 1884-1894. doi:10.1016/j.rse.2007.09.008
[33] W. Qihao, L. Dengsheng and S. Jacquelyn, “Estimation of Land Surface Temperature-Vegetation Abundance Relationship for Urban Heat Island Studies,” Remote Sensing of Environment, Vol. 89, No. 4, 2004, pp. 467-483. doi:10.1016/j.rse.2003.11.005
[34] A. H. S. Salah, “Remote Sensing and GIS Techniques for Urban Growth Monitoring of Basarah City,” International Journal of Remote Sensing and Earth Sciences, Vol. 7, 2010, pp. 73-83.
[35] H. L. Long, G. K. Heilig, X. B. Li and M. Zhang, “Socio- Economic Development and Land-Use Change: Analysis of Rural Housing Land Transition in the Transect of the Yangtse River, China,” Land Use Policy, Vol. 24, No. 1, 2007, pp. 141-153. doi:10.1016/j.landusepol.2005.11.003
[36] H. L. Long, Y. S. Liu, X. Q. Wu, G. H. Dong, “Spatio- Temporal Dynamic Patterns of Farmland and Rural Settlements in Su-Xi-Chang Region: Implications for Building a New Countryside in Coastal China,” Land Use Policy, Vol. 26, No. 2, 2009, pp. 322-333. doi:10.1016/j.landusepol.2008.04.001
[37] J. Wang, Y. Chen, X. Shao, Y. Zhang and Y. Cao, “Land- Use Changes and Policy Dimension Driving Forces in China: Present, Trend and Future,” Land Use Policy, Vol. 29, No. 4, 2012, pp. 737-749. doi:10.1016/j.landusepol.2011.11.010
[38] El. E. Omran, “Evaluation of the Egyptian Soil Maps Accuracy,” Egyptian Journal of Soil Sciences, 2012, In Press.
[39] R. G. Congalton, “A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data,” Remote Sensing of Environment, Vol. 37, No. 1, 1991, pp. 35-46. doi:10.1016/0034-4257(91)90048-B
[40] T. M. Lillesand and R. W. Kiefer, “Remote Sensing and Image Interpretation,” John Wiley& Sons Inc, New York, 2000.
[41] L. F. Janssen and W. J. Vander, “Accuracy A Review,” Photogrammetric Engineering & Remote Sensing, 1994, pp. 419-425.
[42] J. L. Van Genderen, B. F. Lock and P. A. Vass, “Remote Sensing: Statistical Testing of Thematic Map Accuracy,” Remote Sensing of Environment, Vol. 7, No. 1, 1978, pp. 3-14. doi:10.1016/0034-4257(78)90003-2
[43] J. F. Anderson, E. E. Hardy, J. T. Roach and R. E. Witmer, “A Land Use and Land Cover Classification System for Use with Remote Sensor Data,” U.S. Geological Survey Professional Paper 964, US Geological Survey, Washington DC, 1976, p. 28.
[44] H. Y. Araya and P. Cabral, “Analysis and Modeling of Urban Land Cover Change in Setúbal and Sesimbra, Portugal,” Remote Sensing, Vol. 2, 2010, pp. 1549-1563.
[45] F. Bektas, “Remote Sensing and Geographic Information Integration: A Case Study, Bozcaada &Gokceada Island,” M.Sc Thesis, Institution of Science and Technology, Istanbul Technical University, 2003.
[46] ESRI, “ArcMap version 9.3 User Manual,” Redlands, CA, USA, 2008.
[47] D. J. Booth and R. B. Oldfield, “A Comparison of Classification Algorithms in Terms of Speed and Accuracy after the Application of a Post Classification Modal Filter,” International Journal of Remote Sensing, Vol. 10, No. 7, 1989, pp. 1271-1276. doi:10.1080/01431168908903965
[48] S. K. Alvipanah and M. Masoudi, “Land Use Mapping Using Land Sat TM Data and GIS (Case Study: Mouk Area, Iran),” Journal of Agricultural Science and Natural Resources, Vol. 8, No. 1, 2001.
[49] A. P. Carleer, O. Debeir and E. Wolff, “Assessment of Very High Spatial Resolution Satellite Image Segmentations,” Photogrammetric Engineering & Remote Sensing, Vol. 71, No. 11, 2005, pp. 1285-1294.
[50] G. M. Smith and R. M. Fuller, “An Integrated Approach to Land Cover Classification: An Example in the Island of Jersey,” International Journal of Remote Sensing, Vol. 22, No. 16, 2001, pp. 3123-3142. doi:10.1080/01431160152558288
[51] R. G. Congalton and K. Green, “Assessing the Accuracy of Remotely Sensed Data: Principles and Practices,” Lewis Publisher, Boca Raton, 1999.

comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.