Change Detection Analysis using New Nano Satellite Imagery
M. Selim

M. Selim, Higher Institute of Engineering. At Shorouk City Egypt
Manuscript received on 18 February 2018 | Revised Manuscript received on 27 February 2018 | Manuscript published on 28 February 2018 | PP: 4-10 | Volume-7 Issue-3, February 2018 | Retrieval Number: C5276027318/18©BEIESP
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Abstract: Mapping Land use /Land cover (LULC), changes studies have become interesting over the past decades through using remote sensing. It is essential for a wide range of applications, including landslide, erosion, urban growth, agricultural expansion, land planning, global warming etc. In this study, LULC changes in a new Capital, North-East Cairo are investigated by using remote sensing images acquired by (Nano satellite / Planet Labs). For this purpose, firstly supervised classification technique is applied to Planet Labs images acquired in 21December, 2016 and 14 July, 2017. Image classification of four reflective bands of the two images is carried out by using maximum likelihood method with the aid of ground truth data obtained from topographic maps cover the studying area (25x21km). The second part concern is detecting land use land cover changes by using change detection comparison (Image Differencing Method). In the third part of the study, land cover changes are analyzed according to the different features by using ERDAS functions. The results indicate that land cover changes have occurred in the urban area were increased approximately by 1,847,790 sq. m and roads area by 245,385 sq. m while a decrease in bare soil areas by -2,093,175 sq. m. This occurred due to the rapid construction operation. It can be seen that the LULC changes were occurred by the rate of 1,395,450 sq. m. per year in the development area East side of the new Capital.
Keywords: Remote Sensing, Land Use / Land Cover (LULC), Change Detection, Supervised Classification.

Scope of the Article: Classification