Change detection of land cover in Meighan wetland using remote sensing technique

Document Type : (original research)

Authors

1 Department of Environment Sciences and Engineering, Faculty of Natural Resources, University of Jiroft, Jiroft, Iran.

2 Department of Nature Engineering, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

3 Department of Environmental Sciences, Faculty of Natural Resources, University of Tehran, Karaj, Iran

Abstract

Nowadays, monitoring the wetlands land-use change trends using satellite images is one of the most important tools for managing and conserving wetlands. The goal of this study was to investigate land cover change in Meighan wetland as a remarkable wintering wetland for water birds and waders in the middle of the country during 2008-2018 in order to evaluate the trend of the changes in this wetland and make managers prompt a proper decision for the effective management. In this study, images of the geo-referenced Landsat satellite, ETM+, OLI 8 TRIS were used and after applying necessary corrections on the images, results were analyzed in the ENVI 5.4 software. The results of the change detections indicated that the area of the wetland has decreased by 63.31% during the study period. Vegetation covers of the wetland diminished by 64%. During the study period, barren lands have increased by 11.6%. Also, the area of agricultural land in the border of the wetland has expanded by 23.15%. Besides, reviewing water birds and waders abundance in 2008 and 2018 showed that abundance of the most families of water birds and waders were higher in 2008. Taking the environmental importance of Meighan wetland into account as a place hosting large populations of water birds and waders, we recommend that management plans to survey and systematically control of this wetland should be implemented.

Keywords

Main Subjects


  1. Ballanti, L.; Byrd, K.B.; Woo, I. and Ellings, C., Remote sensing for wetland mapping and historical change detection at the Nisqually River Delta. Sustainability. Vol. 9, No. 11, pp: 1-32.
  2. Emadi, M.; Baghernejad, M.; Pakparvar, M. and Kowsar, S.A., 2010. An approach for land suitability evaluation using geostatistics, remote sensing, and geographic information system in arid and semiarid ecosystems. Environmental monitoring and assessment. Vol. 164, No. 1-4, pp: 501-511.
  3. Fichera, C.R.; Modica, G. and Pollino, M., 2012. Land Cover classification and change-detection analysis using multi-temporal remote sensed imagery and landscape metrics. European journal of remote sensing. Vol. 45, No. 1, pp: 1-18.
  4. Hegazy, I.R. and Kaloop, M.R., 2015. Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment. Vol. 4, No. 1, pp: 117-124.
  5. Islam, M.M. and Shamsuddoha, M., 2018. Coastal and marine conservation strategy for Bangladesh in the context of achieving blue growth and sustainable development goals (SDGs). Environmental science & policy. Vol. 87, pp: 45-54.
  6. Jin, S.; Yang, L.; Danielson, P.; Homer, C.; Fry, J. and Xian, G., 2013. A comprehensive change detection method for updating the National Land Cover Database to circa 2011. Remote Sensing of Environment. Vol. 132, pp:
    159-175.
  7. Kaliraj, S.; Chandrasekar, N.; Ramachandran, K.K.; Srinivas, Y. and Saravanan, S., 2017. Coastal land use and land cover change and transformations of Kanyakumari coast, India using remote sensing and GIS. The Egyptian Journal of Remote Sensing and Space Science. Vol. 20, No. 2, pp: 169-185.
  8. Keddy, P.A., 2010. Wetland ecology: principles and conservation. Cambridge University Press. 207 p.
  9. Zeng, Y.; Schaepman, M.E.; Wu, B.; Clevers, J.G. and Bregt, A.K., 2008. Scaling-based forest structural change detection using an inverted geometric-optical model in the Three Gorges region of China. Remote Sensing of Environment. Vol. 112, No. 12, pp: 4261-4271.