Investigating and Predicting the Extension of Dunes Using Land Change Modeler (LCM) in the North West of Yazd, Iran

Document Type : Research Paper

Authors

1 Faculty of Natural Resources and Desert Studies, Yazd University, Yazd, Iran

2 Department of Watershed MGT, Maybod Branch, Islamic Azad University, Maybod, Iran

3 Department of Remote Sensing and GIS, Yazd Branch, Islamic Azad University, Yazd, Iran

Abstract

In the present study, in order to calculate the movement of sand dunes in the period between 2001 and 2010, the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) images were used. The training samples were obtained from the field, and the images of the years 2001 and 2010 were classified using maximum likelihood algorithm and decision making tree. The study area was classified into four classes, including vegetated areas, urban areas, sand dunes, and bare lands. Accuracy of the created land cover maps was assessed using five hundred ground control points, Google Earth, and Landsat 7 satellite images. Based on the results, the overall accuracy and kappa coefficient for the maps of 2001 and 2010 were estimated 96%, 0.94 and 98%, 0.98, respectively. In the next step, the resulted land cover maps were used as input for Land Change Modeler (LCM) and Markov calculation. Statistical outputs and change map of this model show the extensive changes in the dunes during the study period. In addition, the area of sand dunes increased from 12,103 to 14,355 hectares. However, 6 hectares of vegetated areas around the Ashkezar and Zarch cities in the North West of Yazd changed to sand dunes. The highest probability of change in the dunes is the change of dunes to bare lands and the lowest probability is the change of dunes to vegetation lands. These results show the movement and change of the dunes in this arid zone.

Keywords


Arkhy, S., 2014. Prediction of the land use changes using the LCM model in GIS environment Case study: Sarableh region. Journal of the protection and conservation of forests and Rangelands, 12; 1-19.
Azizpoor, M., K. Hosseinzadeh, N. Esmaeilpoor, 2009. Investigation of relationship between rapid horizontal growth of Yazd and population movements. Journal of Geography and Planning, 2; 105–124.
Brown, G., L. Brabyn, 2012. An analysis of the relationships between multiple values and physical landscapes at a regional scale using public participation GIS and landscape character. Landsc Urban Plan, 107; 317-331.
Ekhtesasi, M.R., 1996. Source detecting of sand dunes in the Yazd-ardakan plain of Forests and Rangelands. Research Institute, 1; 20-22.
Feranec, J., G. Jaffrain, T. Soukup, G. Hazeu, 2010. Determining changes and flows in European landscapes 1990–2000 using CORINE land cover data. Applied Geography, 30; 19–35.
GholamAlifard, M., S. Joorabian SHOUSHTARI, H. Hosseini Kahnuj, M. Mirzaei, 2012. Modeling of land use changes in coastal areas of Mazandaran province using the LCM model in GIS. Environment Ecology, 38; 124-109.
GholamAlifard, M., M. Taheri, 2013. Modeling of the changes in land cover of Tabriz province using artificial neural networks and Markov chains. Natural Geography Research, 45; 97-121.
Haase, D., U. Walz, M. Neubert, M. Rosenberg, 2007. Change to Central European landscapes: analyzing historical maps to approach current environmental issues. Land Use Policy, 24; 248-263.
Ismail, M., K. Josoff, 2008. Satellite Data Classification Accuracy Assessment Based from Referenced Dataset. International Journal of Enviromental, Ecological and Geophysical Engineering, 2; 7.
Idrisi 17, 2012. Guide to GIS and Image processing, 1; 17p.
Imani, R., M. Abdullahi, A. Vali, 2013. Investigation of the morphological changes of the sand dunes using remote sensing techniques. Geo-morphological studies, second year, No.3; 129-140.
Jebali, A., R. Jafari, S.J. Khajadin, 2014.MonitoringSand dunes of international GavKhoni wet land using satellite images. Remote sensing and GISIran, 19; 1-10.
Kafi, K.M., H.Z.M. Shafri, A.B.M. Shariff, 2014. An analysis of LULC change detection using remotely sensed data A Case study of Bauchi City. IOP Conf Series Earth and Environmental Science, 20; 1-10.
Khoi, D.D., Y. Murayama, 2010. Forecasting Areas Vulnerable toForest Conversion in the Tam DaoNational Park Region Vietnam. Remote Sensing, 5; 1249–1272.
Kotha, M., P.D. Kunte, 2013, Land cover change in Goa-An Integrated RS_GIS Approach. International Journal of Geo-informatics, 9; 37-43.
Losifescu-Enescu, I., M. Hugentobler, L. Hurni, 2010. Web cartography with open standards: a solution to cartographic challenges of environmental management Environ Model Softw, 25; 988-999.
Mas, J., M. Kolb, M. Paegelow, M. Olmedo, T. Houet, 2014. Modeling Land use/cover change: a comparison of conceptual approaches and software. Environmental Modeling and Software, 51; 94-111.
Meyer, W.B., 1999. Past and Present Land-use and Land-cover in the U.S.A. Consequences; 24-33.
Omidvar, k., 2010. An analysis of extreme winds and storms Yazd. Journal of Humanities Teacher, 1; 89.
Peter, Y., B. Gadiga, A. Mshelia, 2015. Land use/land cover change detection of Mubi Metropolis Adamawa State Nigeria. Sky Journal of Soil Science and Environmental Management, 4; 70-78.
Picuno, P., A. Tortora, R.L. Capobianco, 2011. Analysis of plasticulture landscapes in southern Italy through remote sensing and solid modeling techniques. Landscape Urban Plan, 100; 45-56.
Reynolds, J.F., S. Stafford, 2002. Do humans cause deserts? Global desertification. Dahlem University Press; 1–22.
Schulz, J., L. Cayuela, C. Echeverria, J. Salas, 2010. Applied Geography, 30, 436-447.
Tortora, A., D. Statuto, P. Picuno, 2015. Rural landscape planning through spatial modeling and image processing of historical maps. Land Use Policy, 42; 81p.
Vaclavic, T., 2008. Mapping land use –land cover change in the Olomouc region. URISA Journal, 20; 45-51.
Vafaee, S., A. Darvish sefat, M. Pirbavar, 2012. Monitoring and prediction of the land use spatial changes using the LCM model (Case study: Marivan region). Iranian Journal of the forest, the fifth year; 323- 336.
Warner, T., A. Almutairi, 2010. Change Detection Accuracy and Image Properties: A Study Using Simulated Data. Remote Sensing, 2; 1508p.
Wilkie, D.S., J.T. Finn, 1996. Remote Sensing Imagery for Natural Resources Monitoring. Columbia University Press New York; 295