Research Article
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Year 2025, Volume: 11 Issue: 1, 48 - 57, 17.06.2025
https://doi.org/10.33904/ejfe.1495749

Abstract

Project Number

2565

References

  • Andualem, T.G., Peters, S., Hewa, G.A., Boland, J., Myers, B.R. 2023. Spatiotemporal trends of urban-induced land use and land cover change and implications on catchment surface imperviousness. Applied Water Science, 13(12): 223. https://doi.org/ 10.1007/s13201-023-02029-7
  • Berberoglu, S., Akin, A. 2009. Assessing different remote sensing techniques to detect land use/cover changes in the eastern Mediterranean. International Journal of Applied Earth Observation and Geoinformation, 11(1): 46–53. https://doi.org/ https://doi.org/10.1016/j.jag.2008.06.002
  • Bhattacharjee, S., Islam, M.T., Kabir, M.E., Kabir, M.M. 2021. Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques. Earth Systems and Environment, 5(2): 319–340. https:// doi.org/10.1007/s41748-021-00228-3
  • Brown, D.G., Johnson, K. M., Loveland, T.R., Theobald, D.M. 2005. Rural land-use trends in the conterminous united states, 1950–2000. Ecological Applications, 15(6): 1851–1863.
  • CCRS. 2009. Fundamentals of Remote Sensing. Canada Center for Remote Sensing. 258 p.
  • Chungtai, A.H., Abbasi, H., Karaş, İ.R. 2021. A review on change detection method and accuracy assessment for land use land cover. Remote Sensing Applications Society and Environment, 22(2): 100482.
  • Çoban, H.O. 2006. Uydu Verileri ile Orman Alanlarındaki Zamansal Değişimlerin Belirlenmesi [Doctoral Thesis]. Istanbul Üniversity. Istanbul.
  • Das, S., Angadi, D.P. 2022. Land use land cover change detection and monitoring of urban growth using remote sensing and GIS techniques: a micro-level study. GeoJournal, 87(3): 2101–2123. https://doi.org/10.1007/s10708-020-10359-1
  • Deering, D.W., Rouse, J.W., Haas, R.H., Schell, J.A. 1975. Measuring “forage production” of grazing units from Landsat MSS data. 10th International Symposium on Remote Sensing of Environment, 1169–1178.
  • ESRI. 2024. World Imagery. Retrieved July 10, 2024, from https://www.arcgis.com/home/item.html?id= 10df2279f9684e4a9f6a7f08febac2a9%3FWT.mc_id%3DEmailCampaign15361
  • Huete, A.R. 1988. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3): 295–309. https://doi.org/10.1016/0034-4257(88)90106-X
  • Jensen, J.R. 1996. Introductory Digital Image Processing: A Remote Sensing Perspective (2nd Edition). Prentice Hall.
  • Jordan, C.F. 1969. Derivation of Leaf-Area Index from Quality of Light on the Forest Floor. Ecology, 50(4): 663–666.
  • Koç, A., Selik, C. 2004. Belgrad ormanında arazi kullanımının uzaktan algılama yöntemleri ile belirlenmesi. Journal of the Faculty of Forestry Istanbul University, 46(1): 137–146. https:// doi.org/10.17099/jffiu.56773
  • Lu, D., Mausel, P., Brondízio, E., Moran, E. 2004. Change detection techniques. International Journal of Remote Sensing, 25(12): 2365–2401. https:// doi.org/10.1080/0143116031000139863
  • Mas, J. 1999. Monitoring land-cover changes: A comparison of change detection techniques. International Journal of Remote Sensing (IJRS), 20:139–152. https://doi.org/10.1080/01431169921 3659
  • Mevzuat Bilgi Sistemi. 2024. Orman Amenajman Yönetmeliği. Retrieved July 10, 2024, from https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=11952&MevzuatTur=7&MevzuatTertip=5
  • Qi, J., Chehbouni, A., Huete, A.R., Kerr, Y.H., Sorooshian, S. 1994. A modified soil adjusted vegetation index. Remote Sensing of Environment, 48(2): 119–126. https://doi.org/10.1016/0034-4257(94)90134-1
  • Richards, J.A. 2013. Remote sensing digital image analysis: An introduction. In Remote Sensing Digital Image Analysis: An Introduction (5th ed, Vol. 9783642300622). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-30062-2
  • Rondeaux, G., Steven, M., Baret, F. 1996. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, 55(2), 95–107. https://doi.org/10.1016/ 0034-4257(95)00186-7
  • Roujean, J.L., Breon, F.M. 1995. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements. Remote Sensing of Environment, 51(3): 375–384. https://doi.org/10.1016/0034-4257(94)00114-3
  • Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W. 1974. Monitoring Vegetation Systems in The Great Plains with ERTS. Goddard Space Flight Center 3d Earth Resources Technology Satellite-1 Symposium, 309–317.
  • Roy, D.P., Wulder, M.A., Loveland, T.R., Allen, R.G., Anderson, M.C., Helder, D., Irons, J.R., Johnson, D.M., Kennedy, R., Scambos, T.A., Schaaf, C.B., Schott, J.R., Sheng, Y., Vermote, E.F., Belward, A.S., Bindschadler, R., Cohen, W.B., Gao, F., … Zhu, Z. 2014. Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment, 145: 154–172. https://doi.org/10.1016/ j.rse.2014.02.001
  • Sunar, F. 1998. An analysis of changes in a multi-date data set: A case study in the Ikitelli area, Istanbul, Turkey. International Journal of Remote Sensing, 19(2): 225–235. https://doi.org/10.1080/0143116982 16215
  • Tewabe, D., Fentahun, T. 2020. Assessing land use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia. Cogent Environmental Science, 6(1): 1778998.
  • Thien, B.B., Phuong, V.T. 2023. Detection of Land Use and Land Cover Change Using Remote Sensing and GIS in Ba Ria-Vung Tau Province, Vietnam. Geography and Natural Resources, 44(4): 383–393. https://doi.org/10.1134/S1875372823040133
  • Tucker, C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2): 127–150. https:// doi.org/10.1016/0034-4257(79)90013-0
  • USGS. 2024. What are the band designations for the Landsat satellites? Retrieved July 10, 2024, from https://www.usgs.gov/faqs/what-are-band-designa tions-landsat-satellites
  • Yener, H., Koç, A. 2006. Monitoring changes in forest and other land use forms in Istanbul. Journal of Environmental Biology, 27(1): 77–83.
  • Yong, P., Sun, G., Zengyuan, L., Xuejian, C., Yanfang, D., Zhang, Z. 2003. Land cover change monitoring after forest fire in northeast China. 2003 IEEE International Geoscience and Remote Sensing Symposium Proceedings, 3383–3385.

Monitoring of Land Cover Changes between 1990 and 2014 Over Cyprus Using Multi-Temporal Landsat Imagery

Year 2025, Volume: 11 Issue: 1, 48 - 57, 17.06.2025
https://doi.org/10.33904/ejfe.1495749

Abstract

Determining changes in forest resources and land cover/land use is crucial for sustainable forest planning. This study aims to determine changes in land cover classes, including forest areas, agricultural areas, settlement areas, other non-forest areas, and water bodies in the study area located in Cyprus between 1990 and 2014. The study utilized digital management plans, a high-resolution base map, and Landsat satellite images for the relevant years. Necessary preprocessing steps were applied to prepare the satellite data for classification. Initially, unsupervised classification was conducted on the images to determine the number of distinguishable sub-information classes. Subsequently, supervised classification was performed using the maximum likelihood algorithm with the provision of training areas. The sub classes generated based on the supervised classification were consolidated into five main classes. After the classification process, the accuracy of the classification for each image was determined. Accordingly, the overall classification accuracy of the map from the 1990 Landsat 5 TM satellite image was 92%, with 0.90 Kappa Statistics. The overall classification accuracy of the map from 2014 Landsat 8 OLI satellite image was 89.20%, with 0.87 Kappa statistics. Then, land cover change analysis was conducted to compare a twenty-four-year period within the study area.

Supporting Institution

Scientific Research Projects Coordination Unit of Istanbul University - Cerrahpasa

Project Number

2565

Thanks

I would like to express my gratitude to the Scientific Research Projects Unit of Istanbul University – Cerrahpaşa for providing financial support for my work (Project number: 2565). Additionally, I extend my thanks to the Directorate of the Forestry Department of the Turkish Republic of Northern Cyprus for their contributions to the development of forest management plans.

References

  • Andualem, T.G., Peters, S., Hewa, G.A., Boland, J., Myers, B.R. 2023. Spatiotemporal trends of urban-induced land use and land cover change and implications on catchment surface imperviousness. Applied Water Science, 13(12): 223. https://doi.org/ 10.1007/s13201-023-02029-7
  • Berberoglu, S., Akin, A. 2009. Assessing different remote sensing techniques to detect land use/cover changes in the eastern Mediterranean. International Journal of Applied Earth Observation and Geoinformation, 11(1): 46–53. https://doi.org/ https://doi.org/10.1016/j.jag.2008.06.002
  • Bhattacharjee, S., Islam, M.T., Kabir, M.E., Kabir, M.M. 2021. Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques. Earth Systems and Environment, 5(2): 319–340. https:// doi.org/10.1007/s41748-021-00228-3
  • Brown, D.G., Johnson, K. M., Loveland, T.R., Theobald, D.M. 2005. Rural land-use trends in the conterminous united states, 1950–2000. Ecological Applications, 15(6): 1851–1863.
  • CCRS. 2009. Fundamentals of Remote Sensing. Canada Center for Remote Sensing. 258 p.
  • Chungtai, A.H., Abbasi, H., Karaş, İ.R. 2021. A review on change detection method and accuracy assessment for land use land cover. Remote Sensing Applications Society and Environment, 22(2): 100482.
  • Çoban, H.O. 2006. Uydu Verileri ile Orman Alanlarındaki Zamansal Değişimlerin Belirlenmesi [Doctoral Thesis]. Istanbul Üniversity. Istanbul.
  • Das, S., Angadi, D.P. 2022. Land use land cover change detection and monitoring of urban growth using remote sensing and GIS techniques: a micro-level study. GeoJournal, 87(3): 2101–2123. https://doi.org/10.1007/s10708-020-10359-1
  • Deering, D.W., Rouse, J.W., Haas, R.H., Schell, J.A. 1975. Measuring “forage production” of grazing units from Landsat MSS data. 10th International Symposium on Remote Sensing of Environment, 1169–1178.
  • ESRI. 2024. World Imagery. Retrieved July 10, 2024, from https://www.arcgis.com/home/item.html?id= 10df2279f9684e4a9f6a7f08febac2a9%3FWT.mc_id%3DEmailCampaign15361
  • Huete, A.R. 1988. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3): 295–309. https://doi.org/10.1016/0034-4257(88)90106-X
  • Jensen, J.R. 1996. Introductory Digital Image Processing: A Remote Sensing Perspective (2nd Edition). Prentice Hall.
  • Jordan, C.F. 1969. Derivation of Leaf-Area Index from Quality of Light on the Forest Floor. Ecology, 50(4): 663–666.
  • Koç, A., Selik, C. 2004. Belgrad ormanında arazi kullanımının uzaktan algılama yöntemleri ile belirlenmesi. Journal of the Faculty of Forestry Istanbul University, 46(1): 137–146. https:// doi.org/10.17099/jffiu.56773
  • Lu, D., Mausel, P., Brondízio, E., Moran, E. 2004. Change detection techniques. International Journal of Remote Sensing, 25(12): 2365–2401. https:// doi.org/10.1080/0143116031000139863
  • Mas, J. 1999. Monitoring land-cover changes: A comparison of change detection techniques. International Journal of Remote Sensing (IJRS), 20:139–152. https://doi.org/10.1080/01431169921 3659
  • Mevzuat Bilgi Sistemi. 2024. Orman Amenajman Yönetmeliği. Retrieved July 10, 2024, from https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=11952&MevzuatTur=7&MevzuatTertip=5
  • Qi, J., Chehbouni, A., Huete, A.R., Kerr, Y.H., Sorooshian, S. 1994. A modified soil adjusted vegetation index. Remote Sensing of Environment, 48(2): 119–126. https://doi.org/10.1016/0034-4257(94)90134-1
  • Richards, J.A. 2013. Remote sensing digital image analysis: An introduction. In Remote Sensing Digital Image Analysis: An Introduction (5th ed, Vol. 9783642300622). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-30062-2
  • Rondeaux, G., Steven, M., Baret, F. 1996. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, 55(2), 95–107. https://doi.org/10.1016/ 0034-4257(95)00186-7
  • Roujean, J.L., Breon, F.M. 1995. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements. Remote Sensing of Environment, 51(3): 375–384. https://doi.org/10.1016/0034-4257(94)00114-3
  • Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W. 1974. Monitoring Vegetation Systems in The Great Plains with ERTS. Goddard Space Flight Center 3d Earth Resources Technology Satellite-1 Symposium, 309–317.
  • Roy, D.P., Wulder, M.A., Loveland, T.R., Allen, R.G., Anderson, M.C., Helder, D., Irons, J.R., Johnson, D.M., Kennedy, R., Scambos, T.A., Schaaf, C.B., Schott, J.R., Sheng, Y., Vermote, E.F., Belward, A.S., Bindschadler, R., Cohen, W.B., Gao, F., … Zhu, Z. 2014. Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment, 145: 154–172. https://doi.org/10.1016/ j.rse.2014.02.001
  • Sunar, F. 1998. An analysis of changes in a multi-date data set: A case study in the Ikitelli area, Istanbul, Turkey. International Journal of Remote Sensing, 19(2): 225–235. https://doi.org/10.1080/0143116982 16215
  • Tewabe, D., Fentahun, T. 2020. Assessing land use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia. Cogent Environmental Science, 6(1): 1778998.
  • Thien, B.B., Phuong, V.T. 2023. Detection of Land Use and Land Cover Change Using Remote Sensing and GIS in Ba Ria-Vung Tau Province, Vietnam. Geography and Natural Resources, 44(4): 383–393. https://doi.org/10.1134/S1875372823040133
  • Tucker, C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2): 127–150. https:// doi.org/10.1016/0034-4257(79)90013-0
  • USGS. 2024. What are the band designations for the Landsat satellites? Retrieved July 10, 2024, from https://www.usgs.gov/faqs/what-are-band-designa tions-landsat-satellites
  • Yener, H., Koç, A. 2006. Monitoring changes in forest and other land use forms in Istanbul. Journal of Environmental Biology, 27(1): 77–83.
  • Yong, P., Sun, G., Zengyuan, L., Xuejian, C., Yanfang, D., Zhang, Z. 2003. Land cover change monitoring after forest fire in northeast China. 2003 IEEE International Geoscience and Remote Sensing Symposium Proceedings, 3383–3385.
There are 30 citations in total.

Details

Primary Language English
Subjects Forest Products Transport and Evaluation Information
Journal Section Research Articles
Authors

Burcu Kurtoğlu Erkmen 0000-0002-4415-2626

Hakan Yener 0000-0002-2136-4271

Project Number 2565
Early Pub Date June 12, 2025
Publication Date June 17, 2025
Submission Date June 4, 2024
Acceptance Date September 25, 2024
Published in Issue Year 2025 Volume: 11 Issue: 1

Cite

APA Kurtoğlu Erkmen, B., & Yener, H. (2025). Monitoring of Land Cover Changes between 1990 and 2014 Over Cyprus Using Multi-Temporal Landsat Imagery. European Journal of Forest Engineering, 11(1), 48-57. https://doi.org/10.33904/ejfe.1495749

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The works published in European Journal of Forest Engineering (EJFE) are licensed under a  Creative Commons Attribution-NonCommercial 4.0 International License.