International Journal of Environment and Geoinformatics

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DOI :10.30897/ijegeo.1150436   IUP :10.30897/ijegeo.1150436    Full Text (PDF)

Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map

Abdulazeez Onotu Aliyu, Ebenezer Ayobami Akomolafe, Adamu Bala, Terwase Tosin Youngu, Hassan Musa, Swafiyudeen Bawa

Several remotely sensed images of various resolutions readily exist. Consequently, different classification algorithms also exist, and are broadly categorized as pixel-based and object-based classification methods. Most times, researchers utilize these coarse resolution images to extract land use and land cover (LULC) of an area. This is usually difficult if distinct land uses are to be derived those is not mutually exclusive and overlap with each other due to proximity and contiguity of the pixels, thus, resulting into “salt and pepper” appearance. In the same vein, object-oriented classification is unsuitable for coarse resolution images. Based on the foregoing, this study provided an integrated method of deriving land use from a coarse satellite image. This was to produce a nonraucous and distinct LULC classes that has the appearance of the object-based image classification technique. Location coordinates of the land uses were acquired with a handheld Global Positioning System (GPS) instrument as primary data. The study classified the image quantitatively (pixel-based) into built-up, water, riparian, cultivated, and uncultivated land cover classes with no mixed pixels, and then qualitatively into educational, commercial, health, residential, and security land use classes that were conflicting due to spectral similarity because they belong to the same built-up pixel group. The total accuracy and kappa coefficient of the pixel-based land cover classification were 92.5 and 94% respectively. The results showed that residential land use occupied an area of 5500.01ha, followed by educational (2800.69ha); security (411.27ha); health (133.88ha); and commercial (109.01ha) respectively. The produced LULC map has a crisp-appearance and distinct classes. The approach would exceedingly overcome the “salt and pepper” effect that has bedevilled the scientific community of remote sensing applications. The output of integrated method can be a vector or raster model depending on the purpose for which it is created.

Keywords: Land use, Land cover, pixel-based classification, integrated method, spectral similarity

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APA

Aliyu, A.O., Akomolafe, E.A., Bala, A., Youngu, T.T., Musa, H., & Bawa, S. (2023). Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map. International Journal of Environment and Geoinformatics, 10(2), 135-144. https://doi.org/10.30897/ijegeo.1150436


AMA

Aliyu A O, Akomolafe E A, Bala A, Youngu T T, Musa H, Bawa S. Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map. International Journal of Environment and Geoinformatics. 2023;10(2):135-144. https://doi.org/10.30897/ijegeo.1150436


ABNT

Aliyu, A.O.; Akomolafe, E.A.; Bala, A.; Youngu, T.T.; Musa, H.; Bawa, S. Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map. International Journal of Environment and Geoinformatics, [Publisher Location], v. 10, n. 2, p. 135-144, 2023.


Chicago: Author-Date Style

Aliyu, Abdulazeez Onotu, and Ebenezer Ayobami Akomolafe and Adamu Bala and Terwase Tosin Youngu and Hassan Musa and Swafiyudeen Bawa. 2023. “Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map.” International Journal of Environment and Geoinformatics 10, no. 2: 135-144. https://doi.org/10.30897/ijegeo.1150436


Chicago: Humanities Style

Aliyu, Abdulazeez Onotu, and Ebenezer Ayobami Akomolafe and Adamu Bala and Terwase Tosin Youngu and Hassan Musa and Swafiyudeen Bawa. “Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map.” International Journal of Environment and Geoinformatics 10, no. 2 (Jun. 2025): 135-144. https://doi.org/10.30897/ijegeo.1150436


Harvard: Australian Style

Aliyu, AO & Akomolafe, EA & Bala, A & Youngu, TT & Musa, H & Bawa, S 2023, 'Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map', International Journal of Environment and Geoinformatics, vol. 10, no. 2, pp. 135-144, viewed 6 Jun. 2025, https://doi.org/10.30897/ijegeo.1150436


Harvard: Author-Date Style

Aliyu, A.O. and Akomolafe, E.A. and Bala, A. and Youngu, T.T. and Musa, H. and Bawa, S. (2023) ‘Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map’, International Journal of Environment and Geoinformatics, 10(2), pp. 135-144. https://doi.org/10.30897/ijegeo.1150436 (6 Jun. 2025).


MLA

Aliyu, Abdulazeez Onotu, and Ebenezer Ayobami Akomolafe and Adamu Bala and Terwase Tosin Youngu and Hassan Musa and Swafiyudeen Bawa. “Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map.” International Journal of Environment and Geoinformatics, vol. 10, no. 2, 2023, pp. 135-144. [Database Container], https://doi.org/10.30897/ijegeo.1150436


Vancouver

Aliyu AO, Akomolafe EA, Bala A, Youngu TT, Musa H, Bawa S. Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map. International Journal of Environment and Geoinformatics [Internet]. 6 Jun. 2025 [cited 6 Jun. 2025];10(2):135-144. Available from: https://doi.org/10.30897/ijegeo.1150436 doi: 10.30897/ijegeo.1150436


ISNAD

Aliyu, AbdulazeezOnotu - Akomolafe, EbenezerAyobami - Bala, Adamu - Youngu, TerwaseTosin - Musa, Hassan - Bawa, Swafiyudeen. “Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map”. International Journal of Environment and Geoinformatics 10/2 (Jun. 2025): 135-144. https://doi.org/10.30897/ijegeo.1150436



TIMELINE


Submitted28.07.2022
Accepted20.05.2023
Published Online15.06.2023

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