International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Download
Citation
Volume XLII-4/W16
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 261–266, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-261-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 261–266, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-261-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  01 Oct 2019

01 Oct 2019

WATER LEVEL FLUCTUATION ASSESSMENT OF LAKE CHAD FOR ENVIRONMENTAL SUSTAINABILITY USING REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEM TECHNIQUE

A. Hussaini1,2, M. R. Mahmud1, K. K. W. Tang1, and A. G. Abubakar1 A. Hussaini et al.
  • 1Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
  • 2Department of Geography, Aminu Saleh College of Education Azare PMB 044, Bauchi State, Nigeria

Keywords: Remote Sensing, GIS, Lake Chad, Landsat and Water Level

Abstract. Surface water is a significant constituent of the water cycle, and is paramount for human survival, social and economic development as well as environmental sustainability. Water level shrinkage and global warming are the main phenomena that becoming worldwide environmental problems. Lake Chad has been in a critical situation in recent years due to a continuous decline in surface water and drought, over abstraction of water and climate change caused a significant change of a land cover patterns. The present study aimed to highlight the change pattern of water level in the lake over the past three decades, and the satellite images of the Lake Chad from Landsat-TM, ETM+ and OLI were analyzed to investigate the change of land cover pattern during three periods: the 1985, 2000 and 2015. Supervised classification was performed for land cover change analysis. Then the overall accuracies of the classification of Landsat-TM is 93.80, Landsat-ETM+ is 90.80 and Landsat-OLI is 86.20 respectively. The result shows that there are continuous decline of water bodies, barren land and shrub, with rapid increment of farmland and gallery forest.