Evaluation of change detection and future condition of meadow-land ecosystem of Shahrekord using Landsat data

Document Type : Research Paper


1 Dep. range and watershed Management of shahrekord University

2 shahre kord


Wetland meadows as a natural ecosystems plays an important role on sustainability of nature, although are enormously under drainage and changing in the recent years. Shahrekord meadow, which is located adjacent to the city, considered as a natural heritage due to its contribution to tourist visiting, balancing weather in addition to supplying forage for animals. However, this meadow is declining due to anthropogenic effects that this article aims at studying and evaluation of its change and prediction of future condition using Landsat TM5, ETM+7 and OLI/TIRS. To do so, first of all the images of 1987, 1994, 2001, 2010 and 2016 were gathered, then radiometric and geometrically were evaluated. After that, landuse/landcover of the study area was depicted using a maximum likelihood method in TerrSet (Ver. 18.31). Afterward, change detection of the study area was done using a cross-tabulation method and the future condition was predicted using a CA-Markov model. Results indicated that a significant change was occurred in this study area whereas in 1987 whole of the study area was covered by meadowland but land cover changes altered this valuable ecosystem to constructed area (3.33%), arable land (25.02%) and airport (19.65%) in 2016. Results of change prediction also depicted that 5.08% of the study area will be converted to other land cover in 2026. Therefore, we recommend that land use and land cover of this valuable ecosystem should be conserved due to the function and services that this meadowland offered.


[1] Amir Khosravi Dehkordi Ami; Marbazi Najaf Abadi Rassoul; Samadi Boroujien Hossein; Ghasemi Dastjerdi Ahmad Reza (2018) Monitoring and prediction of groundwater droughts in Shahrekord plain using GRI and Markov chain model. Hydrogeology Journal of Tabriz University. 24th of January, 2018
[2] Ahmad, Mobin (2017) Satellite Image Based Study for Land Use Land Cover Changed due to Mining Activity during (1987 to 2011) at Dhanbad District of Jharkhand. International Journal for Scientific & Development, 4 (12):962-965.
[3] Al-Hamdan, M. Z., et al. (2017). "Evaluating land cover changes in Eastern and Southern Africa from 2000 to 2010 using validated Landsat and MODIS data." International Journal of Applied Earth Observation and Geoinformation. 62: 8-26.
[4] Bauni, V., et al. (2015). "Ecosystem loss assessment following hydroelectric dam flooding: The case of Yacyretá, Argentina." Remote Sensing Applications: Society and Environment 1: 50-60.
[5] Calderon-Aguilera, L. E., et al. (2012). "An assessment of natural and human disturbance effects on Mexican ecosystems: current trends and research gaps." Biodiversity and Conservation 21(3): 589-617.            
[6] Fan, C., et al. (2017). "Time series evaluation of landscape dynamics using annual Landsat imagery and spatial statistical modeling: Evidence from the Phoenix metropolitan region." International Journal of Applied Earth Observation and Geoinformation 58: 12-25.
[7] Guan, D., Li, H., Inohae, T., et al. (2011). Modeling urban land use change by the integration of cellular automaton and Markov model. Ecological Modelling, 222, 3761–3772.
[8] Hu, X. L., Xu, L., Zhang, S. S. )2013(. Land use pattern of Dalian City, Liaoning Province of Northeast China based on CA-Markov model and multi-objective optimization. Chinese Journal of Applied Ecology, 24(6), 1652–1660.
[9] Maxwell, S.K. Schmidt, G.L. Storey, J.C. (2007). A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images. International Journal of Remote Sensing.28. (23): 5339-5356.
[10] Naboureh, A., et al. (2017). "An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain." Arabian Journal of Geosciences 10(12): 259.
[11] Pringle, M.J. Schmidt, M. Muir, J.S. (2009). Geostatistical interpolation of SLC-off Landsat ETM+ images. ISPRS Journal of Photogrammetry and Remote Sensing. 64 (Issue 6): 654-664.
[12] Roy, D.P. Kline, J. JuScaramuzza, K, P.L, Kovalskyy. Hansen, V. M. Loveland, T.R. Vermote, E. Zhang, C. (2010). Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States. Remote Sensing of Environment. 114(1): 35-49.
[13] Sánchez-Reyes, U. J., et al. (2017). "Assessment of Land Use-Cover Changes and Successional Stages of Vegetation in the Natural Protected Area Altas Cumbres, Northeastern Mexico, Using Landsat Satellite Imagery." Remote Sensing 9(7).
[14] Schneibel, A., et al. (2017). "Assessment of spatio-temporal changes of smallholder cultivation patterns in the Angolan Miombo belt using segmentation of Landsat time series." Remote Sensing of Environment 195: 118-129.
[15] Zhang, C. Li, W. Travis, D. (2007). Gaps-fill of SLC-off Landsat ETM+ satellite image using ageostatistical approach. International Journal of Remote Sensing. 28(22): 5103-5122.
Volume 71, Issue 2
September 2018
Pages 473-484
  • Receive Date: 11 October 2017
  • Revise Date: 31 May 2018
  • Accept Date: 31 May 2018
  • First Publish Date: 23 August 2018