Monitoring land use /land cover using multi-temporal Landsat images in Al-Jabal Al-Akhdar area in Libya between 1984 and 2003


  • Moussa Masoud Faculty of Natural Resources and Environmental Sciences, Omar Al-Mukhtar University, Libya



Rangeland, Satellite images, land cover change, Libya


This study investigated the change in land cover of Al-Jabal Al-Akhdar from 1984 to 2003 by using satellite images. Four categories of land-cover (forest, rangeland, urban area and desert) were studied to determine the change between 1984 and 2003. Supervised classifications were performed on the Landsat 5 images. The land resources database showed that the rangeland and forest recorded negative change over the years under study while it was a significant positive change in the urban areas. The most significant change was the desert expanding. Rangeland surface proportions were 43.34% in 1984 but were decreased to 28.63% in 2003. Forest surface proportions were 22.13% in 1984 but were decreased to 10.17% in 2003. This can be attributed to human activities, which includes over- grazing, indiscriminate bush burning, fire and urban areas. This is a clear indication of an increase in population and infrastructure development in the study area, regardless of use or pattern. Information from satellite remote sensing can play a useful role in understanding the nature of land use and land cover changes (LULCC), where they are occurring, and projecting possible or likely future changes.


Download data is not yet available.


Metrics Loading ...


Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20:37–46. DOI:

Congalton, G. R. (1991). A review of assessing the accuracy of classification of remote sensed data. Remote Sensing Environment, 7:35–46. DOI:

Congalton, R. G. and R. A. Mead. (1983). A quantitative method to test for consistency and correctness in photo interpretation. Photogrammetric Engineering and Remote Sensing, 49:69-74.

Frey, D., and M. Butenuth. (2009). Classification system of GIS-objects using multi-sensorial imagery for near-realtime disaster management. In: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII (3/W4), 103–108.

Hoffer, RM. (1978). Biological and Physical Considerations in Applying Computer- aided analysis techniques to Remote Sensor data. In: Remote Sensing: The quantitative approach, Ed.: P. H. Swam and S. M. Davis, McGraw- Hill, NY, USA, P: 227-289.

Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80: 185-201. DOI:

Gitas, I., M. Meliadis, T. Katagis, A. Polychronaki and I. Meliadis. (2009). Monitoring land use/cover change with the use of object based image analysis and LANDSAT imagery. 3rd EARSeL Workshop of Remote Sensing of Land Use & Land Cover. Bonn, Germany, 25-27 November.

Jensen, J. R. (1996). Introductory Digital Image Processing. A Remote Sensing Perspective. Prentice-Hall, Englewood Cliffs, New Jersey.

Jensen, R., J. Gatrell and D. Mclean. (2005). Geo-spatial technologies in urban environments. Policy, practice and pixels. Berlin: Springer.

Johnson, D. L. (1973). Jabal Al-Akhdar, Cyrenaica: A historical geography of settlement and livelihood. Research paper 48, Department of Geography, University of Chicago.

Lu, D., P. Mausel, E. Brondizio and E. Moran. (2004). Change detection techniques. International Journal of Remote Sensing, 25: 2365-2407. DOI:

Malinverni, E. S., G. Fangi and P. Salandin. (2003). Spatial Modeling in a GIS for an environmental decision support system. Workshop: Spatial Analysis and Decision Making SADM2003. ISPRS. Commission II WG 5 and 6. Hong Kong, 229-241.

Μeliadis, ΙM. (2005). Correlations of environmental parameters with the use of satellite technology and G.I.S. Forest Research, 17: 19-26.

Μeliadis, ΙM., A. Τsiontsis and T. Daskalakis. (2005). Estimation of the risk erosion in the soil of the county of Thessaloniki. Proceedings of the 12th National Forestry Conference, Forest and Water Protection of the Environment. Drama 2-5 October, pp: 433-440.

Papadopoulou, M., and M. Tsakiri-Strati. (1993). The monitoring of environmental changes with the combination of aerial photos and Satellite images. 2nd Greek Convention, Solar and Space Research. Athens. Greece.

Ramachandra, T., and U. Kumar. (2004). Geographic Resources Decision Support System for land use, land cover dynamics analysis. Proceedings of the FOSS/GRASS Users Conference. 12-14 September, Bangkok, Thailand.

Ramita, M., OA. Inakwu and A. Tiho. (2009). Improving the accuracy of land-use and land-cover classification of landsat data using post-classification enhancement. Remote Sensing, ISSN, pp: 2072-4292.

Singh, A. (1989). Digital change detection techniques using remotely-sensing data. International Journal of Remote Sensing, 10: 989-1003. DOI:

Trisurat, Y., A. Eiumnoh, S. Murai, M. Z. Husain and R. P. Shrestha. (2000). Improvements of tropical vegetation mapping using a remote sensing technique: a case study of Khao National Park, Thailand. International Journal of Remote Sensing, 21: 2031-2042. DOI:




How to Cite

Masoud, M. . (2016). Monitoring land use /land cover using multi-temporal Landsat images in Al-Jabal Al-Akhdar area in Libya between 1984 and 2003. Al-Mukhtar Journal of Sciences, 31(1), 12–23.



Research Articles


Similar Articles

You may also start an advanced similarity search for this article.