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Zhang, Z., Wang, X., Zhao, X., Liu, B., Yi, L., Zuo, L., Wen, Q., Liu, F., Xu, J. and Hu, S. (2014) A 2010 Update of National Land Use/Cover Database of China at 1:100000 Scale Using Medium Spatial Resolution Satellite Images. Remote Sensing of Environment, 149, 142-154.
http://dx.doi.org/10.1016/j.rse.2014.04.004

has been cited by the following article:

• TITLE: Land Use and Land Cover Change Detection in the Saudi Arabian Desert Cities of Makkah and Al-Taif Using Satellite Data

  AUTHORS: Abdullah F. Alqurashi, Lalit Kumar

  KEYWORDS: Land Use/Cover Patterns, Landsat Imagery, Makkah, Al-Taif, Urban Growth, Image Classification, Change Detection

  JOURNAL NAME: Advances in Remote Sensing, Vol.3 No.3, September 17, 2014

  ABSTRACT: Land use/land cover (LULC) changes have become a central issue in current global change and sustainability research. Saudi Arabia has undergone significant change in land use and land cover since the government embarked on a course of intense national development 30 years ago, as a result of huge national oil revenues. This study evaluates LULC change in Makkah and Al-Taif, Saudi Arabia from 1986 to 2013 using Landsat images. Maximum likelihood and object-oriented classification were used to develop LULC maps. The change detection was executed using post-classification comparison and GIS. The results indicated that urban areas have increased over the period by approximately 174% in Makkah and 113% in Al-Taif. Analysis of vegetation cover over the study area showed a variable distribution from year to year due to changing average precipitation in this environment. Object-based classification provided slightly greater accuracy than maximum likelihood classification. Information provided by satellite remote sensing can play an important role in quantifying and understanding the relationship between population growth and LULC changes, which can assist future planning and potential environmental impacts of expanding urban areas.