 Introduction: Rapid urbanization and urban growth, particularly in the developing worlds, is continuing to be one of the crucial issues of global change in affecting the physical dimensions of cities.  Case description with Methodology: This study proposes a technique to extract urban built-up land features from, Multi Spectral Scanner System (MSS-1977), Landsat Thematic Mapper (1998, 2003, and 2014) and Hyperion EO-1imagery of part of Delhi NCT in India as examples. The study selected two indices, Normalized Difference Built-up Index (NDBI), Normalized and Normalized Different Vegetation Index (NDVI) to represent three major urban land-use classes, built-up land and vegetation, respectively. The relationship between land use/land cover (LU/ LC) change and population shift and their effects on the spatiotemporal patterns of urban area were quantitatively examined using an integrated approach of remote sensing, geographical information systems (GIS). Consequently, the seven bands of an original Landsat image were reduced into three thematic-oriented bands derived from above indices. The three new bands were then combined to compose a new image. As a result, the spectral signatures of the three urban land-use classes are more distinguishable in the new composite image than in the original seven-band image as the spectral clusters of the classes are well separated. Therefore, the technique is effective and reliable. In addition, the advantages of over NDVI and over NDBI in the urban study are also discussed in this paper. Furthermore, in combination with the detection of LU/ LC change, an analysis of the spatially differential growth rates for developed land area and population size revealed an urban e suburban gradient pattern of population shifting, as evidenced by a sharp increase in developed land area within the middle sub-zones at the urban fringe and the exurban sub-zones beyond the outer traffic ring. As the result, changes in LU/ LC and population shifts resulted in significant variation in the spatiotemporal patterns of the urban area due to the loss of water bodies and vegetated surfaces.  Discussion and Evaluation: Results indicate that the built-up area in the study area has increased by 290%; from 165.52 km 2 in 1977 to 645.3799 km 2 in 2014. The results of the multi-temporal change detection show that the highest urban growth rates, 216% occurred between 2003 and 2014. In contrast, the growth rates were 10% during 1977-1998 and 12% during the period 1998-2003. This massive growth was mainly resulted from the transformation of agricultural and barren land of the outskirt of core city. Peri-urban areas are often characterized by valuable natural environment and resource bases to provide essential ecosystem functions for urban residents. Observing land cover change over time can reveal the effects and impacts of urbanization in peri-urban areas. Existing built-up areas have a greater influence on urban expansion outside urban planned districts than in urban planned districts.  Conclusion: It is sugg...

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Brick-making industry, top-soil removal, replacement cost approaches and crop yield loss.

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