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Articles

Semi-automatic mapping of anthropogenic impervious surfaces in an urban/suburban area using Landsat 8 satellite data

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Pages 471-494 | Received 17 Sep 2016, Accepted 11 Jan 2017, Published online: 29 Jan 2017

References

  • Anderson, J. R. 1976. A Land Use and Land Cover Classification System for Use with Remote Sensor Data. Vol. 964. Washington, DC: US Government Printing Office.
  • As-Syakur, A. R., I. W. S. Adnyana, I. W. Arthana, and I. W. Nuarsa. 2012. “Enhanced Built-Up and Bareness Index (EBBI) for Mapping Built-Up and Bare Land in an Urban Area.” Remote Sensing 4 (10): 2957–2970. doi:10.3390/rs4102957.
  • Baig, Muhammad Hasan Ali.., L. Zhang, T. Shuai, and Q. Tong. 2014. “Derivation Of A Tasselled Cap Transformation Based On Landsat 8 At-satellite Reflectance.” Remote Sensing Letters 5 (5): 423–431. doi:10.1080/2150704X.2014.915434.
  • Bauer, M. E., N. J. Heinert, J. K. Doyle, and F. Yuan. 2004. “Impervious Surface Mapping and Change Monitoring Using Landsat Remote Sensing.” In ASPRS annual conference proceedings, vol. 10. Bethesda, MD: American Society for Photogrammetry and Remote Sensing.
  • Bhatti, S. S., and N. K. Tripathi. 2014. “Built-Up Area Extraction Using Landsat 8 OLI Imagery.” Giscience & Remote Sensing 51 (4): 445–467. doi:10.1080/15481603.2014.939539.
  • Census of India. 2011. Metadata. Office of the Registrar General & Census Commissioner, India. http://www.censusindia.gov.in/2011census/HLO/Metadata_Census_2011.pdf
  • Chen, J., P. Gong, C. He, R. Pu, and P. Shi. 2003. “Land-Use/Land-Cover Change Detection Using Improved Change-Vector Analysis.” Photogrammetric Engineering & Remote Sensing 69 (4): 369–379. doi:10.14358/PERS.69.4.369.
  • Chen, Y., P. Shi, T. Fung, J. Wang, and X. Li. 2007. “Object‐Oriented Classification for Urban Land Cover Mapping with ASTER Imagery.” International Journal of Remote Sensing 28 (20): 4645–4651. doi:10.1080/01431160500444731.
  • Deng, C., and C. Wu. 2012. “BCI: A Biophysical Composition Index for Remote Sensing of Urban Environments.” Remote Sensing of Environment 127: 247–259. doi:10.1016/j.rse.2012.09.009.
  • Deng, Y., C. Wu, M. Li, and R. Chen. 2015. “RNDSI: A Ratio Normalized Difference Soil Index for Remote Sensing of Urban/Suburban Environments.” International Journal of Applied Earth Observation and Geoinformation 39: 40–48. doi:10.1016/j.jag.2015.02.010.
  • DOE (Department of the Environment). 1975. National Land Use Classification. Londan: HMSO.
  • Gangkofner, U. G., P. S. Pradhan, and D. W. Holcomb. 2008. “Optimizing the High-Pass Filter Addition Technique for Image Fusion.” Photogrammetric Engineering & Remote Sensing 74: 1107–1118. HPF Resolution Merge. In: ERDAS IMAGINE Help. Leica Geosystems Geospatial Imaging, LLC. doi:10.14358/PERS.74.9.1107.
  • George, X., C. Mike, and C. McMahon. 2008. “Quantifying Multi-Temporal Urban Development Characteristics in Las Vegas from Landsat and ASTER Data.” Photogrammetric Engineering & Remote Sensing 74 (4): 473–481. doi:10.14358/PERS.74.4.473.
  • Hao, P., Z. Niu, Y. Zhan, Y. Wu, L. Wang, and Y. Liu. 2016. “Spatiotemporal Changes of Urban Impervious Surface Area and Land Surface Temperature in Beijing from 1990 to 2014.” Giscience & Remote Sensing 53: 63–84. doi:10.1080/15481603.2015.1095471.
  • Harrison, A. R. 2006. National Land Use Database: Land Use and Land Cover Classification (Version 4.4). Office of the Deputy Prime Minister, Queen’s Printer and Controller of Her Majesty’s Stationery Office, London, UK.
  • He, C., P. Shi, D. Xie, and Y. Zhao. 2010. “Improving the Normalized Difference Built-Up Index to Map Urban Built-Up Areas Using a Semiautomatic Segmentation Approach.” Remote Sensing Letters 1 (4): 213–221. doi:10.1080/01431161.2010.481681.
  • Kawamura, M., S. Jayamana, and Y. Tsujiko. 1996. “Relation between Social and Environmental Conditions in Colombo Sri Lanka and the Urban Index Estimated by Satellite Remote Sensing Data.” International Archives of Photogrammetry and Remote Sensing 31: 321–326.
  • Li, W., and C. Wu. 2016. “A Geostatistical Temporal Mixture Analysis Approach to Address Endmember Variability for Estimating Regional Impervious Surface Distributions.” Giscience & Remote Sensing 53: 102–121. doi:10.1080/15481603.2015.1118975.
  • Liu, J., H. Tian, M. Liu, D. Zhuang, J. M. Melillo, and Z. Zhang. 2005. “China’s Changing Landscape during the 1990s: Large‐Scale Land Transformations Estimated with Satellite Data.” Geophysical Research Letters 32 (2). doi:10.1029/2004GL021649.
  • Lu, D., E. Moran, and S. Hetrick. 2011. “Detection of Impervious Surface Change with Multitemporal Landsat Images in an Urban–Rural Frontier.” ISPRS Journal of Photogrammetry and Remote Sensing 66 (3): 298–306. doi:10.1016/j.isprsjprs.2010.10.010.
  • Mas, J. F. 2004. “Mapping Land Use/Cover in a Tropical Coastal Area Using Satellite Sensor Data, GIS and Artificial Neural Networks.” Estuarine, Coastal and Shelf Science 59 (2): 219–230. doi:10.1016/j.ecss.2003.08.011.
  • NCRPB (National Capital Region Planning Board). 2008. A Study on Counter-Magnet Areas to Delhi and National Capital Region. Ministry of Urban Development, Government of India, New Delhi.
  • NCRPB (National Capital Region Planning Board). 2015. Annual Report 2014-15. Ministry of Urban Development, Government of India, New Delhi.
  • Parece, T. E., and J. B. Campbell. 2013. “Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography.” Remote Sensing 5 (10): 4942–4960. doi:10.3390/rs5104942.
  • Pereira, J. M. 1999. “A Comparative Evaluation of NOAA/AVHRR Vegetation Indexes for Burned Surface Detection and Mapping.” IEEE Transactions on Geoscience and Remote Sensing 37 (1): 217–226. doi:10.1109/36.739156.
  • Slonecker, E. T., D. B. Jennings, and D. Garofalo. 2001. “Remote Sensing of Impervious Surfaces: A Review.” Remote Sensing Reviews 20 (3): 227–255. doi:10.1080/02757250109532436.
  • Squires, G. 2012. Urban and Environmental Economics: An Introduction. Abingdon: Routledge.
  • Stathakis, D., K. Perakis, and I. Savin. 2012. “Efficient Segmentation of Urban Areas by the VIBI.” International Journal of Remote Sensing 33 (20): 6361–6377. doi:10.1080/01431161.2012.687842.
  • Thompson, M. 1996. “A Standard Land-Cover Classification Scheme for Remote-Sensing Applications in South Africa.” South African Journal of Science 92 (1): 34–42.
  • Torbick, N., and M. Corbiere. 2015. “Mapping Urban Sprawl and Impervious Surfaces in the Northeast United States for the past Four Decades.” Giscience & Remote Sensing 52 (6): 746–764. doi:10.1080/15481603.2015.1076561.
  • Weng, Q. 2012. “Remote Sensing of Impervious Surfaces in the Urban Areas: Requirements, Methods, and Trends.” Remote Sensing of Environment 117: 34–49. doi:10.1016/j.rse.2011.02.030.
  • Xiao, J., Y. Shen, J. Ge, R. Tateishi, C. Tang, Y. Liang, and Z. Huang. 2006. “Evaluating Urban Expansion and Land Use Change in Shijiazhuang, China, by Using GIS and Remote Sensing.” Landscape and Urban Planning 75 (1): 69–80. doi:10.1016/j.landurbplan.2004.12.005.
  • Xu, H. 2006. “Modification Of Normalised Difference Water Index (Ndwi) To Enhance Open Water Features In Remotely Sensed Imagery.” International Journal Of Remote Sensing 27 (14): 3025-3033. doi:10.1080/01431160600589179.
  • Xu, H. 2007. “Extraction of Urban Built-Up Land Features from Landsat Imagery Using a Thematic Oriented Index Combination Technique.” Photogrammetric Engineering & Remote Sensing 73 (12): 1381–1391. doi:10.14358/PERS.73.12.1381.
  • Xu, H. 2008. “A New Index for Delineating Built-Up Land Features in Satellite Imagery.” International Journal of Remote Sensing 29 (14): 4269–4276. doi:10.1080/01431160802039957.
  • Xu, H. 2010. “Analysis of Impervious Surface and Its Impact on Urban Heat Environment Using the Normalized Difference Impervious Surface Index (NDISI).” Photogrammetric Engineering & Remote Sensing 76 (5): 557–565. doi:10.14358/PERS.76.5.557.
  • Yuan, F., C. Wu, and M. E. Bauer. 2008. “Comparison of Spectral Analysis Techniques for Impervious Surface Estimation Using Landsat Imagery.” Photogrammetric Engineering & Remote Sensing 74 (8): 1045–1055. doi:10.14358/PERS.74.8.1045.
  • Zha, Y., J. Gao, and S. Ni. 2003. “Use of Normalized Difference Built-Up Index in Automatically Mapping Urban Areas from TM Imagery.” International Journal of Remote Sensing 24 (3): 583–594. doi:10.1080/01431160304987.
  • Zhang, J., L. Zhengjun, and S. Xiaoxia. 2009. “Changing Landscape in the Three Gorges Reservoir Area of Yangtze River from 1977 to 2005: Land Use/Land Cover, Vegetation Cover Changes Estimated Using Multi-Source Satellite Data.” International Journal of Applied Earth Observation and Geoinformation 11 (6): 403–412. doi:10.1016/j.jag.2009.07.004.
  • Zhou, Y., G. Yang, S. Wang, L. Wang, F. Wang, and X. Liu. 2014. “A New Index for Mapping Built-Up and Bare Land Areas from Landsat-8 OLI Data.” Remote Sensing Letters 5 (10): 862–871. doi:10.1080/2150704X.2014.973996.
  • Zhu, G., and D. G. Blumberg. 2002. “Classification Using ASTER Data and SVM Algorithms;: The Case Study of Beer Sheva, Israel.” Remote Sensing of Environment 80 (2): 233–240. doi:10.1016/S0034-4257(01)00305-4.

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