Investigation of Land Use Changes in North of Iran Using Remote Sensing and Geographical Information System (1986-2015)
Keywords:
Land use, Deforestation, Remote Sensing, Classification, Neka.Abstract
Deforestation in Iran has been more rapid in the past 50 years than at any time in Iran’s history, and Neka basin located in the north of Iran has been subjected to severe deforestation problems. Detection of ecosystem changes may help decision makers and planners to understand the factors in land use and land cover changes in order to take effective and useful measures. Using remote sensing and GIS technologies are used as efficient tools for monitoring and evaluation land use change. In recent years, a considerable land use changes have occurred in in the Neka basin. This paper presents ?ndings of an evaluation study that focused on the changes in land use changes in a great basin of Neka. The study was based on a spatial analysis of historical Landsat images (1986–2015) and several ?eld measurements and observations. First, geometric correction and contrast stretch are applied. In order to detect and evaluate land use changes, image differencing, vegetation change analysis, principal component analysis and classification comparison have been applied. Finally, the results of land cover classification for three different times are compared to reveal land use changes. Relatively, agriculture, range and urban developed areas increased, respectively 84.70, 31.88 and 54.52 % from 1986 to 2015, while forest decreased 44.35%. With the greatest decrease occurring from 1991 to 1999. The overly analysis of the four land cover maps revealed that there is an imbalance in the spatial distribution of deforestation areas. The west and central part of the study area has mostly changed and deforestrated.
From 1986 to 2015, forest, which covered 1245.53 km2 (47.79%) of the total area in 1986 had decreased to 693.60 (25.60.7%) in 2015. However, the rangelands increased from 1120.42 ha in 1986 to 1477.69 km2 in 20015.
References
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[2] Ahmadi, S., Khosravi, H., Dehghan, P., Evolution of land use changes using Remote Sensing (Case Study: Hiv Basin, Taleghan), International Journal of Forest, Soil and Erosion (IJFSE), 2016. 6 (2): 49-55
[3] Antwi, E. K., Boakye-Danquah, J., Asabere, S. B., Takeuchi, K., Wiegleb, G. Landover transformation in two post-mining landscapes subjected to different ages of reclamation since dumping of spoils. Springer plus, 2014. 3(1):702-713.
[4] Barsimantov, J., Navia Antezana, J. Forest cover change and land tenure change in Mexico’s avocado region: Is community forestry related to reduce deforestation for high value crops? ApplGeogr, 2012. 32(2):844–853.
[5] Bhatta, B., Saraswati, S., Bandyopadhyay, D. Quantifying the degree-of-freedom, degree-of-sprawl and degree-of-goodness of urban growth from remote sensing data. ApplGeogr, 2010. 30: 96–111.
[6] Bhattarai, K., Conway, D., and Yousef, M. Determinants of deforestation in Nepal’s central development region. Journal of Environmental Management, 2009. 91 (2): 471–488.
[7] Bhattarai, N., Quackenbush, L. J., Dougherty, M., & Marzen, L. J. A simple Landsat – MODIS fusion approach for monitoring seasonal evapotranspiration at 30 m spatial resolution. International Journal of Remote Sensing, 2015. 36(1): 115 – 143.
[8] Chen, H., Liang, X., Li, R. Based on a multi-agent system for multi-scale simulation and application of household’s LUCC: a case study for Mengchavillage, Mizhicounty, Shaanxi province. Springer plus, 2013. 2(1): 12-23.
[9] Chen, H., Chang, N., Yu, R., & Huang, Y. Urban land use and land cover classification using the neural-fuzzy inference approach with Formosat-2 data. Journal of Applied Remote Sensing, 2009. 3(1): 1-18. doi:10.1117/1.3265995.
[10] Crabtree, R., Potter, C., Mullen, R., Sheldon, J., Huang, S., Harmsen, J., & Jean, C. A modeling and spatio-temporal analysis framework for monitoring environmental change using NPP as an ecosystem indicator. Remote Sensing of Environment, 2009. 113(7); 1486-1496.
[11] DEI. Department of environment Iran. Initial National Communication to UNFCCC, 2003.
[12] Dennison, P. E., Nagler, P. L., Hultine, K. R., Glenn, E. P., & Ehleringer, J. R. Remote monitoring of tamarisk defoliation and evapotranspiration following salt cedar leaf beetle attack. Remote Sensing of Environment, 2009. 113(7): 1462-1472.
[13] Emadodin, I (2008). Human-induced soil degradation in Iran. Ecosystem services workshop, Salzau Castle, 13 – 15 May, Kiel, Northern Germany.
[14] Esandari, H., Borji, M., Khosravi, H., Nakhaee Nejadfar, S., Eskandari, H., Change Detection of of Bakhtegan and Tashk Basin during 2001-2013, International Journal of Forest, Soil and Erosion (IJFSE), 2016. 6 (2): 67-71
[15] Eskandari, H., Borji, M., Khosravi, H., Mesbahzadeh, T., Deserti?cation of forest, range and desert in Tehran province, affected by climate change, Solid Earth, 2016. 7 (3): 905-915
[16] Fonji, S.F., Taff, G. N. Using satellite data to monitor land-use land-cover change in North-eastern Latvia. Springer plus, 2014. 3(1): 61.
[17] Jahani Shakib, F., Malek Mohammadi, B., Yavari, A., Sharifi,Y. Assessment of Wetland Landscape Changes In Land Use And Climate Change, With A Focus On Environmental Impacts. Ecology, 2014. 40 (3), 631-643.
[18] Jensen, J. R. Digital change detection. Introductory digital image processing: A remote sensing perspective. New Jersey’ Prentice-Hall. 2004. pp. 467–494
[19] Jones, D.A., Hansen, A.J., Bly, K., Doherty, K., Verschuyl, J.P., Paugh, J.I., Carle, R., Story, S.J. Monitoring land use and cover around parks: A conceptual approach. Remote Sensing of Environment, 2009. 113: 1346-1356.
[20] Karteris, M. A. The utility of digital thematic mapper data for natural resources classification, International Journal of Remote Sensing, 1990. 11 (9): 1589-1598.
[21] Kelarestaghi, A., H. Ahmadi, Jafari, M. Evaluation and comparison of the potential of the ETM+ and ASTER imagery for forest land use mapping, case study Farm Drainage Basin. International Conference Map Asia, Bangkok, Thailand. 2006.
[22] Klosterman, R. E. Modelling Land-use Change: Progress and Applications (GeoJournal Volume 90). Appl Spatial Anal Policy 1(2):151–152, Eric Koomen, John Stillwell, Aldrik Bakema, and Henk J. Scholten, eds. 2008.
[23] Lambin, E. F., Geist, H., & Rindfuss, R. R. Introduction: local processes with global impacts. In Land-use and land-cover change. Springer Berlin Heidelberg, 2006. pp. 1-8.
[24] Michaelis, A. Wirtschaftliche Enttwicklungsprobleme des Mittleren Ostens. Kiel, seite78, 1960.
[25] Mirkatouli, J. Hosseini, A. Neshat, A. Analysis of land use and land cover spatial pattern based on Markov chains modelling, city territory and architecture. 2015.
[26] Mozaffari, G. A., Narangi, F. Evaluation of precipitation on Lake water level changes using sensing data Dvr.nshryh Akvbyvlvzhy wetlands, spring, 2014. 6(19): 73-82
[27] Ozesmi, S. L., Bauer, M. E. Satellite remote sensing of wetlands. Wetlands ecology and management, 2002. 10(5): 381-402.
[28] Panta, M., Kim, K., and Joshi, C. Temporal mapping of deforestation and forest degradation in Nepal: applications to forest conservation. Forest Ecology and Management, 2008. 256 (9): 1587–1595.
[29] Pelorosso, R., Leone, A., Boccia, L. Land cover and land use change in theItalian central Apennines: A comparison of assessment methods. ApplGeogr, 2009. 29(1): 35–48.
[30] Ressl, R., Lopez, G., Cruz, I., Colditz, R. R., Schmidt, M., Ressl, S., Jiménez, R. Operational active fire mapping and burnt area identification applicable to Mexican nature protection areas using MODIS-DB data. Remote Sensing of Environment, 2009. 113: 1113–1126.
[31] Sakizadeh, M. Assessment the performance of classification methods in water quality studies, a case study in Karaj River. Environmental Monitoring and Assessment, 2015. 187(9): 573-582.
[32] Shaw, S. B., Marrs, J., Bhattarai, N., Quackenbush, L. Longitudinal study of the impacts of land cover change on hydrologic response in four mesoscale watersheds in New York State, USA. Journal of Hydrology, 2014. 519: 12 – 22.
[33] Soffianian, A., Madanian, M. Monitoring land cover changes in Isfahan Province, Iran using Landsat satellite data. Environmental Monitoring and Assessment, 2015. 187(8): 1 – 15.
[34] Tan, R., Liu, Y., Zhou, K., Jiao, L., Tang, W. A game-theory based agent-cellular model for use in urban growth simulation: A case study of the rapidly urbanizing Wuhan area of central China. ComputEnvir urban Syst, 2015. 49:15–29.
[35] Vitousek, P. M., Mooney, H. A., Lubchenco, J., Melillo, J. M. Human domination of earth’s ecosystems, Science, 1997. 277(5325): 494-499.
[36] Wang, Y., Mitchell, B. R., Nugranad-Marzilli, J., Bonynge, G., Zhou, Y., Shriver, G. Remote sensing of land-cover change and landscape context of the National Parks: A case study of the Northeast Temperate Network,” Remote Sensing of Environment, 2009. 113: 1453-1461
[37] Wang, Z., Jiao, J. Y., Lei, B., Su, Y. An approach for detecting five typical vegetation types on the Chinese Loess Plateau using Landsat TM data. Environmental Monitoring and Assessment, 2015. 187(9): 1 – 16
[38] Yang, X. Satellite monitoring of urban spatial growth in the Atlanta metropolitan area. Photogrammetric Engineering and Remote Sensing, 2002. 68(7):725–734.
[39] Yanli, Y. Jabbar, M.T. Zhou, J. X. Study of environmental change detection using remote sensing and GIS application: A case study of northern Shaanxi province, China, Polish Journal Environment Studies, 2012. 21(3), 783-790.
[40] Zebardast, L., Jafari, H., Use of Remote Sensing in Monitoring the Trend of Changes of Anzali Wetland in Iran and Proposing Environmental Management Solution, Journal of environmental studies, 2011. 37(57): 1-8.
[41] Zhang, X., Kang, T., Wang, H., Sun, Y. Analysis on spatial structure of landuse change based on remote sensing and geographical information system. Int JAppl Earth ObsGeoinf, 2010. 12:S145–S150.
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Published
2016-09-17
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Ghodsi, M., Moghimi, E., Yamani, M., Jafarbigloo, M., & Hosseini, S. M. (2016). Investigation of Land Use Changes in North of Iran Using Remote Sensing and Geographical Information System (1986-2015). American Scientific Research Journal for Engineering, Technology, and Sciences, 25(1), 11–22. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/2062
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