- Tytuł:
- Examining Landuse Pattern of Akinyele Local Government Area of Oyo State Using Remote Sensing and GIS Techniques
- Autorzy:
-
Amusa, I. A.
Akinpelu, A. A.
Oludiji, S. M.
Oyebanji, S. T. - Powiązania:
- https://bibliotekanauki.pl/articles/1839383.pdf
- Data publikacji:
- 2021
- Wydawca:
- Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
- Tematy:
-
Remote Sensing
resolution
Kappa Index
Confusion matrix and classification
Geographic Information Systems
GIS - Opis:
- The study looked at the application of Remote Sensing and Geographic Information Systems in the landuse pattern in Akinyele Local Government Area of Oyo state; this is with the aim of classifying the area into the four basic classes observed in the study area. Landsat8 imagery with 30m by 30m resolution within path 191 and row 55 was downloaded, administrative boundary of the local government was used to clip the image using ArcGIS software and bands’ combination was done. Bands 7, 5 and 4 were combined to produce the composite image that gives natural colours for easy identification of features using supervised classification method. The study area was categorized into built up, vegetation, bare ground and water body. During the course of the study, it was gathered that the area has 56.84% vegetation, 39.61% built up, 3.32% bare ground and 0.23% water body. Confusion matrix was adopted for accuracy assessment. At the end, it was shown that the study had an overall classification accuracy of 83.67% and the Kappa Index is substantial at 0.77. Therefore, it was concluded that supervised image classification method is suitable for landuse classification and the results obtained are reliable.
- Źródło:
-
World Scientific News; 2021, 162; 16-28
2392-2192 - Pojawia się w:
- World Scientific News
- Dostawca treści:
- Biblioteka Nauki
Artykuł