This paper is published in Volume-4, Issue-5, 2018
Area
Geography
Author
Modibbo Babagana-Kyari
Co-authors
Yusuf Maina-Bukar
Org/Univ
Yobe State University, Yobe State, Nigeria, Nigeria
Pub. Date
28 September, 2018
Paper ID
V4I5-1249
Publisher
Keywords
GIS, Image differencing, Land cover, Multispectral, NDVI, Satellite imageries

Citationsacebook

IEEE
Modibbo Babagana-Kyari, Yusuf Maina-Bukar. Detecting tree cover loss in Damaturu town using multi-temporal landsat imagery, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Modibbo Babagana-Kyari, Yusuf Maina-Bukar (2018). Detecting tree cover loss in Damaturu town using multi-temporal landsat imagery. International Journal of Advance Research, Ideas and Innovations in Technology, 4(5) www.IJARIIT.com.

MLA
Modibbo Babagana-Kyari, Yusuf Maina-Bukar. "Detecting tree cover loss in Damaturu town using multi-temporal landsat imagery." International Journal of Advance Research, Ideas and Innovations in Technology 4.5 (2018). www.IJARIIT.com.

Abstract

Damaturu, the administrative headquarters of Yobe State, Nigeria has been experiencing a rapid developmental change in its physical landscape due to the monumental impact of urbanization in the last two to three decades, and this development has been occurring progressively at the detriment of the urban trees. No attempt has been made singularly to investigate the extent of this negative development as it keeps on progressing at an alarming rate. Thus, this study aimed at detecting and mapping the changes occurred in the last three decades, so as to the find out the extent of the change. For this purpose, the Landsat Thematic Mapper (TM) of 1986, and Landsat Eight/8 (OLI) scene of 2016 was acquired and used. Normalized Difference Vegetation Index (NDVI) and change detection technique of image differencing was employed to detect the changes. The threshold parameter of 45% and 48% were used respectively for the increased (gain) and decreased (loss) option to obtain the image differencing (Highlight change map) result in ERDAS Imagine software version 15. Findings revealed that there are a significant tree cover canopies gain and loss amounting to an area cover of 2,193.75 and 1150.38 Hectares of land respectively. People’s quest of land for shelter, administrative status of the town, as well as lack of strong environmental bye-laws were identified as the main drivers of the observed changes. Overall, the study provides the valuable information required for sustainable urban development. This study also demonstrates the usefulness of medium resolution Landsat imageries and change detection techniques in observing environmental changes at a local level.
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