Land use change detection using GIS and RS techniques casestudy: The South east of Zayanderood Basin, Esfahan, Iran

Paper Details

Research Paper 01/06/2016
Views (269) Download (19)
current_issue_feature_image
publication_file

Land use change detection using GIS and RS techniques casestudy: The South east of Zayanderood Basin, Esfahan, Iran

Vali Abbas Ali, Erahimi Khusfi zohre, Khosroshahi Mohammah, Ghazavi Reza
J. Bio. Env. Sci.8( 6), 87-100, June 2016.
Certificate: JBES 2016 [Generate Certificate]

Abstract

Satellite images and geographic information system (GIS) are important data resources for the dynamic analysis of landscape transformations. The application of these data made possible to monitor the changes in different land uses in less time, at low cost and with better accuracy. In this study, Land use/ Land cover changes was investigated using of Remote Sensing and GIS in the south east of Zayanderood watershed. Multispectral satellite data acquired from images of Landsat satellite for the years 1998and 2013 was used. Processing operations was performed using ENVI4.7 software. Supervised classification-maximum likelihood algorithmwas appliedto detectland cover/land use changes observed in the study area. Studywatershed wasclassified into eight major land use classes viz., Vegetation, Agriculture, Gavkhouni Wetland, Settlement area, Sand dune, Salt land, Bare land and Poor pastureland. The results indicate that over 15 years, agriculture, poor pastures, vegetation and Gavkhouni wetland have been decreased by 1.84% (326.42 km2), 1.11% (319.88 km2), 0.21%(36.4km2) and 0.14% (25.14 km2) while Settlement area, salt land, sand dune and bare land have been increased by 2.07% (366.2 km2), 0.97% (171.6 km2), 0.56%(98.4km2) and 0.4%(71.57km2), respectively. These land cover/use variations lead to serious danger for watershed resources. Therefore, an appropriate watershed management plans and conservation strategiesare required in order to protect these valuable resources or else they will soon be diminished and no longer be able to perform their function in socioeconomic development of the area.

VIEWS 4

Ahmad  S,  Avtar R,  Mahendra S, Akhilesh S. 2016. Delhi , s land cover change in post transit era. Cities 50, 111-118.

Ahmad F. 2012. Detection of change in vegetation cover using multi-spectral and multi-temporal information for District Sargodha, Pakistan. Sociedade and Natureza 24(3), 557–572.

Ahmed MA , Walid AA. 2014. Integration Remote Sensing and GIS Techniques to Evaluate Land Use-Land Cover of Baghdad Region and Nearby Areas. Iraqi Journal of Science 55(1), 184-192.

Alavi N. 2012. Land Use And Land Cover Change Detection In Isfahan, Iran Using Remote Sensing Techniques. Master’s thesis, University of Ottawa, Canada, 134 p.

Amin A, Amin A, Singh SK. 2012. Study of urban land use dynamics in Srinagar city using geospatial approach. Bulletin of Environmental and Scientific Research 1(2), 18–24.

Anderson JR.1971. Land use classification schemes used in selected recent geographic applications of remote sensing: Photogramm Eng 37(4), 379-387.

Butt A, Shabbir R, Ahmad S , Aziz N. 2015. Land use change mapping and analysis using Remote Sensing and GIS: A case study of Simly watershed, Islamabad, Pakistan. The Egyptian Journal of Remote Sensing and Space Sciences 18(2), 251-259.

Carlson TN, Azofeifa SGA. 1999. Satellite Remote Sensing of land Use changes in and around San Jose´, Costa Rica. Remote Sensing of Environment 70, 247– 256.

Cetin M. 2009. A satellite based assessment of the impact of urban expansion around a lagoon. International journal environmental science technology 6(4), 579-590.

Chavez PS, Guptil SC, Bowell JA. 1984. Image processing techniques for thematic mapper data. Proceedings, ASPRS-ACSM Technical Papers 2, 728-742.

Chavez Jr PS. 1988. An improved dark-object subtraction technique for atmospheric scattering correction for multispectral data. Remote Sensing of Environment 24, 459-479.

Chavez PS, Berlin GL, Sowers LB. 1982. Statistical method for selecting Landsat MSS ratios. Journal of Applied Photographic Engineering 8, 23-30.

Congalton RG, Green K. 1999. Assessing the accuracy of remotely sensed data: (Second edition). Principles and practices. CRC Press Taylor and Francis Group, International Standard Book Number-13: 978-1-4200-5512-2, Lewis Publishers 201 p.

Dadras M, Helmi Zm, Shafri, Noordin A. 2015. Spatio-temporal analysis of urban growth from remote sensing data in Bandar Abbas city, Iran. The Egyptian Journal of Remote Sensing and Space Sciences 18, 35-52.

Demers MN. 2005. Fundamentals of Geographic Information Systems, John Wiley and Sons, Inc., Newyork, USA.455 p.

Dutra LV, Huber RI. 1999. Feature Extraction and Selection for ERS-1/2 in SAR Classification. International Journal of Remote Sensing 20( 5), 993-1016.

Egorova AV, Hansenb MC, Roya DP, Kommareddy A, Potapov PV. 2015. Image interpretation-guided supervised classification using nested segmentation. Remote Sensing of Environment 165,135-147.

Fisher RA. 1936. The use of multiple measurements in taxonomic problems. Annals of Eugenics 7(2), 179–188.

Gambarova YM, Gambarov AY, Rustamov RB, Zeynalova MH. 2010. Remote Sensing and GIS as an Advance Space Technologies for Rare Vegetation Monitoring in Gobustan State National Park, Azerbaijan. Journal of Geographic Information System 2, 93-99.

Gao BC. 1996. NDWI – A normalized difference water index for remote sensing of vegetation liquid water water from space. Remote Sensing of Environment 58, 257-266.

Jebali A, Jafari R, Khajedin SJ. 2013. Monitoring Sand Dunes Change of Gavkhouni International Wetland Using Sattelite Imagery. Iranian Remote Sensing and GIS 5(3), 34-48.

Janssen LLF, vander Wel FJM. 1994. Accuracy Assessment of Satellite Derived Land-Cover Data: A Review. Photogrammetric Engineering and Remote Sensin 60(4), 419-426.

Jensen JR. 1983. Urban/suburban land use analysis. Manual Remote Sensing 2, 1571-1666.

Jensen JR. 1996. Introductory Digital Image Processing: A Remote Sensing Perspective Journal of Remote Sensing 10, 989-1003.

Jensen JR. 2007. Introductory Digital Image Processing: A Remote Sensing Perspective. Prentice Hall.

Liao CH, Chang CL, Su CY, Chiueh PT. 2013. Correlation between land-use change and greenhouse gas emissions in urban areas. International Journal of Environmental Science and Technology 10, 1275-1286.

Lillesand TM , Kiefer RW. 1994. Remote sensing and interpretation. Jhon Wiley and sons Inc., New York, 750 p.

Liu CH , Xiao-xiao MA. 2011. Analysis to driving forces of land use change in Lu,an mining area. Transactions of Nonferrous Metals Society of China 21, 727-732

Maleky M , Saeedi Razavi B. 2013. Evaluation of Development and Changes in Land Use using Different Satellite Image Processing and Remote Sensing Techniques (Case Study: Kermanshah, Iran). Research Journal of Environmental and Earth Sciences 5(10), 567-576.

Mas JFO, Velazquez A, Az-Gallegos D, Mayorga-Saucedo JR, Alcantara R, Boccob C, Castro R, Fernandez T, Perez-Vega A. 2004. Assessing land use/cover changes: a nationwide multidate spatial database for Mexico, International Journal of Applied Earth Observation and Geoinformation 5, 249-261.

Meyer WB, Turner BL. 1994. Changes in Land Use and Land Cover: A Global Perspective. Cambridge, Cambridge University Press, 537 p.

Mohd HI, Kamaruzaman J. 2008. Satellite Data Classi-fication Accuracy Assessment Based from Reference Dataset. International Journal of Computer and Infor-mation Science and Engineering 2(2), 96-102.

Mousavi SA, Shahriari AR, Fakhire A, Ranjbar F, Abolfazl Rahdari V. 2014. Assessment of changes trend of land cover with use of remote sensing data in Hamoon wetland. Journal of Biodiversity and Environmental Sciences (JBES) 4(5), 146-156.

Na XD, Zang SY, Zhang NN, Cui J. 2015. Impact of land use and land cover dynamics on Zhalong wetlandreserve ecosystem, Heilongjiang Province, China. International journal environmental science technology 12, 445–454.

Owojori A, Xie H. 2005. Landsat image-based LULC changes of San Antonio, Texas using advanced atmospheric correction andobject-oriented image analysis approaches. Paper Presented at the 5th International Symposium on Remote Sensing of Urban Areas, Tempe, AZ.

Ozesmi SL, Bauer M. 2002. Satellite remote sensing of wetlands. Wetlands Ecology and Management 10, 381–402.

Raul Romo-Leon J, Willem JD, Alejandro CV. 2014. Using remote sensing tools to assess land use transition in unsustainable arid agro-ecosystems. Journal of Arid Environments 106, 27-35.

Rawat JS, Kumar M. 2015. Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Sciences 18, 77–84.

Roostayee SH, Ahadnezhad Rooshti M , Farrokhe M. 2015. Spatial Evaluation on land use changes using satellite imagery (Case Study : Urmia). Journal of Geography and Planning, 18(50), 189-206.

Rouse JW, Haas RH, Schell JA, Deering DW.1973. Monitoring vegetation systems in the Great Plains with ERTS. Third ERTS Symposium, NASA , 309–317 p.

Saadat H, Adamowski J, Bonnel R, Sharifi F, Namdar M,  Ale-Ebrahim  S. 2011.  Land use and land coverclassification over a large area in Iran based on single date analysis of satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing 66(5), 608-619.

Sabet S, Ibrahim M, Latif AB , Pavlos K. 2011. Three decades of urban growth in the city of Shiraz, Iran: A remote sensing and geographic information systems application. Cities 28(4), 320-329.

Sader SA, Hayes DJ,Hepinstall JA, Coan M, Soza C. 2001. Forest change monitoring of a remote biosphere reserve. International Journal of Remote Sensing 22(10), 1937−1950.

Seif A, Mokarram M. 2012. Change detection of Gil Playa in the Northeast of Fars Province. Iran American Journal of Scientific Research 73, 122–130

Senseman GM, Bagley CF, Tweddale Scotee A. 1995. Accuracy assessment of the discrete classification of remotely-sensed digital data for landcover mapping. USACERL Technical Report. EN-95/04.31P.

Serra P, Pons X, Sauri D. 2003. Post – Classification change detection with data from different sensors: some accuracy considerations. International Journal of Remote Sensing 24(16), 3311-3340.

Singh A. 1989. Digital change detection techniques using remotely sensed data. InternationalJournal of Remote Sensing, 10(6), 989-1003.

Solaimani K, Modallaldoust S, Lotfi S. 2009. Investigation of land use changes on soil erosion process using geographical information system. International journal environmental science technology 6(3), 415-424.

Suffianian A, Madanian M. 2015. Monitoring land cover changes in Isfahan Province, Iran using Landsat satellite data. Environmental Monitoring and Assessment 187(8), 543-560.

Tripathi NK, Rai BK, Dwivedi P. 1997. Spatial Modeling of Soil Alkalinity in GISEnvironment Using IRS data. 18th Asian conference on remote sensing, Kualalampur, A.8.1-A.8.6 p.

Tso BM, Mather PM. 1999. Crop Discrimination Using Multi-Temporal SAR Imagery .International Journal of Remote Sensing 20(12), 2443-2460.

Turner MG, Ruscher CL. 2004. Change in landscape patterns in Georgia. USA Landscape Ecology 1(4), 251–421.

Wasige JE, Goren TA, Eric S, Victor J. 2013. Monitoring basin- scale land cover changes in Kagera Basin of Lake Victoria using ancillary data and remote sensing. International Journal of Applied Earth Observation and Geoinformation 21, 32-42.

Zoran ME. 2006. The use of multi-temporal and multispectral satellite data for change detection analysis of Romanian Black Sea Coastal zone. Journal of Optoelectronics and Advanced Materials 8, 252– 256.

Zsuzsanna D, Bartholy J, Pongracz R, Barcza Z. 2005. Analysis of land-use/land-cover change in the Carpathian region based on remote sensing techniques. Physics and Chemistry of Earth 30, 109-115.