An Integrative Modelling Approach to Analyse Landscape Dynamics Through Intensity Analysis and Cellular Automata-Markov Chain Model

• Authors: Mohammad Hasani , Abdolrassoul Salmanmahiny , Alireza Mikaeili Tabrizi
• Languages of publication: EN

Abstracts

EN

The goal of this study is offer a deep understanding of the landscape dynamics in the Gorgan Township, the Golestan Province, Iran. Landsat satellite imagery of two different time thresholds, i.e. the years 1992 and 2011, was acquired from the US Geological Survey database and the changes were quantified for the Gorgan area covering a 19-year time span. Furthermore, an integrated Cellular Automata-Markov Chain (CA-MC) model was applied to predict future changes up to the year 2030. We used the intensity analysis method to compare the historical dynamics of different land categories at multiple levels. The results indicated that during the 19 years, the built-up and forest areas increased by 2.33% and 0.27%, respectively, while agriculture and remnant vegetation decreased by 2.43% and 0.24%, respectively. The CA-MC model illustrated that in the following 19 years, the built-up areas could increase by 2.45%. An intensity analysis revealed that forest gains and losses were dormant while remnant vegetation gains and losses were active. The built-up area’s gains and water bodies’ losses were active and stationary during both time intervals. The transitions from water bodies and remnant vegetation to agriculture were regularly targeting and stationary, while the transition from forest to agriculture was regularly avoiding and stationary. Our findings also indicated a heavy systematic transition from agriculture to built-up areas. Regarding the increasing population growth and urbanisation in the region, the outcomes of this study can help make informed decisions for the management and protection of natural resources in the study area.

Keywords

EN

landscape dynamics; satellite imagery; Cellular Automata-Markov Chain; Intensity Analysis; Iran

• Publisher: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
• Journal: European Spatial Research and Policy
• Year: 2020
• Volume: 27
• Issue: 1
• Pages: 243-261

Dates

published

2020-06-30

Contributors

author

Mohammad Hasani

• Gorgan University of Agricultural Sciences and Natural Resources, College of the Environmental Sciences, Basij square, Gorgan, Golestan Provice, Iran

• https://orcid.org/0000-0002-8731-1666

author

Abdolrassoul Salmanmahiny

• Gorgan University of Agricultural Sciences and Natural Resources, College of the Environmental Sciences, Basij square, Gorgan, Golestan Provice, Iran

• https://orcid.org/0000-0002-5188-7356

author

Alireza Mikaeili Tabrizi

• Gorgan University of Agricultural Sciences and Natural Resources, College of the Environmental Sciences, Basij square, Gorgan, Golestan Provice, Iran

References

• ABD EL-KAWY, O.R., RØD, J.K., ISMAIL, H.A. and SULIMAN, A.S., (2011) ‘Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data’, Appl Geogr, 31, pp. 483–494. https://doi.org/10.1016/j.apgeog.2010.10.012
• ALDWAIK, S.Z. and PONTIUS, R.G.Jr., (2012), ‘Intensity analysis to unify measurements of size and stationarity of land changes by interval, category, and transition’, Landscape and Urban Planning, 106, pp. 103–114. https://doi.org/10.1016/j.landurbplan.2012.02.010
• ALDWAIK, S.Z. and PONTIUS, R.G.Jr. (2013), ’Map errors that could account for deviations from a uniform intensity of land change’, International Journal of Geographical Information Science, 27 (9), pp. 1717–1379. https://doi.org/10.1080/13658816.2013.787618
• BHAGAWAT, R. (2011), ‘Application of remote sensing and GIS, land use/land cover change in Kathmandu metropolitan city’, Nepal J. Theor. Appl. Inform. Technol, 23 (2), pp. 80–86.
• CHANDER, G., MARKHAM, B.L. and HELDER, D.L. (2009), ‘Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors’, Rem. Sen. Envi, 113 (5), pp. 893–903. https://doi.org/10.1016/j.rse.2009.01.007
• CLARK, W. (1965), ‘Markov chain analysis in geography: an application to the movement of rental housing areas’, Ann. Assoc. Am. Geogr., 55 (2), pp. 351–359. https://doi.org/10.1111/j.1467-8306.1965.tb00523.x
• EL BASTAWESY, M. (2014), ‘Hydrological Scenarios of the Renaissance Dam in Ethiopia and Its Hydro-Environmental Impact on the Nile Downstream’, J. Hydro. Engin., http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0001112
• ENARUVBE, G. and PONTIUS, R.G.Jr. (2015), ‘Influence of classification errors on Intensity Analysis of land changes in southern Nigeria’, International Journal of Remote Sensing, 31 (1), pp. 244–261. https://doi.org/10.1080/01431161.2014.994721
• GONG, W., YUAN, L., FAN, W. and STOTT, P., (2015), ‘Analysis and simulation of land use spatial pattern in Harbin prefecture based on trajectories and cellular automata Markov modelling’, International Journal of Applied Earth Observation and Geoinformation, 34 (3), pp. 207–216. https://doi.org/10.1016/j.jag.2014.07.005
• GUAN, D., LI, H., INOHAE, T., SU, W., NAGAIE, T. and HOKAO, K. (2011), ‘Modeling urban’, Ecological Modelling, 222, pp. 3761–3772. https://doi.org/10.1016/j.ecolmodel.2011.09.009
• HALMY, M.W.A., GESSLER P.E., HICKE, J.A. and SALEM, B.B. (2015), ‘Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA’, Applied Geography, 63, pp. 101–112. https://doi.org/10.1016/j.apgeog.2015.06.015
• HASANI, M., SAKIEH, Y., DEZHKAM, S., ARDAKANI, T. and SALMANMAHINY, A. (2017), ‘Environmental monitoring and assessment of landscape dynamics in southern coast of the Caspian Sea through intensity analysis and imprecise land-use data’, Environ Monit Assess. https://doi.org/10.1007/s10661-017-5883-9
• 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, 4, pp. 117–124. https://doi.org/10.1016/j.ijsbe.2015.02.005
• KAMUSOKO, C., ANIYA, M., ADI, B. and MANJORO, M. (2009), ‘Rural sustainability under threat in Zimbabwe – simulation of futurs land use/cover changes in the Bindura district based on the Markov-cellular automata model’, Applied Geography, 29, pp. 435–447. https://doi.org/10.1016/j.apgeog.2008.10.002
• LIU, J.Y. and DENG, X.Z. (2010), ‘Progress of the research methodologies on the temporal and spatial process of LUCC’, Chin. Sci. Bull., 55, pp. 1354–1362. https://doi.org/10.1007/s11434-009-0733-y
• LIU, Y., NISHIYAMA, S. and YANO, T. (2004), ‘Analysis of four change detection algorithms in bi-temporal space with a case study’, International Journal of Remote Sensing, 25 (11), pp. 2121–2139. https://doi.org/10.1080/01431160310001606647
• LO, C.P. and CHOI, J. (2004), ‘A hybrid approach to urban land use/cover mapping using Landsat 7 enhanced thematic mapper plus (ETM+) images’, Inter. J. Rem. Sen., 25 (14), pp. 2687–2700. https://doi.org/10.1080/01431160310001618428
• MULLER, M.R. and MIDDLETON, J. (1994), ‘A Markov model of land-use change dynamics in the Niagara Region, Ontario, Canada’, Landscape Ecology, 9, pp. 151–157.
• NAHUELHUAL, L., CARMONA, A., LARA, A., ECHEVERRA, C. and GONZلLEZ, M.E. (2012), ‘Landcover change to forest plantations: proximate causes and implications for the landscape in south-central Chile’, Landscape and Urban Planning, 107 (1), pp. 12–20. https://doi.org/10.1016/j.landurbplan.2012.04.006
• NITSCH, H., OSTERBURG, B., ROGGENDORF, W. and LAGGNER, B. (2012), ‘Cross compliance and the protection of grassland – illustrative analyses of land use transitions between permanent grassland and arable land in German regions’, Land Use Policy, 29, pp. 440–448. https://doi.org/10.1016/j.landusepol.2011.09.001
• OTUKEI, J.R. and BLASCHKE, T. (2010), ‘Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms’, International Journal of Applied Earth Observation and Geoinformation, 12, pp. S27–S31. https://doi.org/10.1016/j.jag.2009.11.002
• OVERMARS, K.P., DE KONING, G.H.J. and VELDKAMP, A. (2003), ‘Spatial autocorrelation in multi-scale land use models’, Ecological Modelling, 164, pp. 257–270. https://doi.org/10.1016/S0304-3800(03)00070-X
• PALIWAL, M.C. and KATIYAR, S.K. (2015), ‘Accuracy Assessment of Land Cover /Land Use Mapping Using Medium Resolution Satellite Imagery’, International Journal of Scientific & Engineering Research, 6 (7), pp. 1428–1432.
• PONTIUS, G.R. and MALANSON, J. (2005), ‘Comparison of the structure and accuracy of two land change models’, International Journal of Geographical Information Science, 19, pp. 243–265. https://doi.org/10.1080/13658810410001713434
• PONTIUS JR., R.G, SHUSAS, E. and MCEACHERN, M. (2004), ‘Detecting important categorical land changes while accounting for persistence’, Agriculture, Ecosystems & Environment, 101 (2–3), pp. 251–268. https://doi.org/10.1016/j.agee.2003.09.008
• PONTIUS JR., R.G., GAO, Y., NICHOLAS, M.G., KOHYAMA, T., OSAKI, M. and HIROSE, K. (2013), ‘Design and interpretation of intensity analysis illustrated by land change in Central Kalimantan, Indonesia’, Land, 2 (3), pp. 351–369. https://doi.org/10.3390/land2030351
• PRAKASAM, C. (2010), ‘Land use and land cover change detection through remote sensing approach: A case study of Kodaikanal taluk, Tamil nadu’, International Journal of Geomatics and Geosciences, 1 (2), pp. 150–158.
• RAWAT, J.S. and KUMAR, M. (2015), ‘Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India’, Remote Sensing and Space Sciences, 18, pp. 77–84. https://doi.org/10.1016/j.ejrs.2015.02.002
• SAKIEH, Y., SALMANMAHINY, A., JAFARNEZHAD, J., MEHRI, A., KAMYAB, H. and GALDAVI, S. (2015), ‘Evaluating the strategy of decentralized urban land-use planning in a developing region’, Land Use Policy, 48, pp. 534–551. https://doi.org/10.1016/j.landusepol.2015.07.004
• SAKIEH, Y., SALMANMAHINY, A., MIRKARIMI, S.H. and SAEIDI, S. (2016), ‘Measuring the relationships between landscape aesthetics suitability and spatial patterns of urbanized lands: An informed modeling framework for developing urban growth scenarios’, Geocarto International. https://doi.org/10.1080/10106049.2016.1178817
• SALMANMAHINY, A. (2013), Golestan Province Land Use Planning Report, Gorgan University of Agriculture and Natural Resources.
• SELCUK, R., NISANCI, R., UZUN, B., YALCIN, A., INAN, H. and YOMRALIOGLU, T. (2003), ‘Monitoring land-use changes by GIS and remote sensing techniques: case study of Trabzon’, http://www.fig.net/pub/morocco/proceedings/TS18/TS18_6_reis_el_al.pdf 5.
• SONG, C., WOODCOCK, C.E., SETO, K.C., LENNEY, M.P. and MACOMBER, S.A. (2001), ‘Classification and change detection using Landsat TM data: When and how to correct atmospheric effects?’, Remote Sensing of Environment, 75, pp. 230–244. https://doi.org/10.1016/S0034-4257(00)00169-3
• SRIVASTAVA, P.K., HAN, D., RICO-RAMIREZ, M.A., BRAY, M. and ISLAM, T. (2012), ‘Selection of classification techniques for land use/land cover change investigation’, Advances in Space Research, 50, pp. 1250–1265. https://doi.org/10.1016/j.asr.2012.06.032
• TEIXEIRA, Z., MARQUES, J.C. and PONTIUS Jr., R.G. (2016), ‘Evidence for deviations from uniform changes in a Portuguese watershed illustrated by CORINE maps: an intensity analysis approach’, Ecological Indicators, 66, pp. 382–390. https://doi.org/10.1016/j.ecolind.2016.01.018
• VERBURG, P.H. and VELDKAMP, A. (2005), ‘Introduction to the Special Issue on Spatial modeling to explore land use dynamics’, International Journal of Geographical Information Science, 19 (2), pp. 99–102. https://doi.org/10.1080/13658810410001713362
• VERBURG, P.H., KOK, K., PONTIUS, R.G. and VELDKAMP, A., (2006), ‘Modeling Land-Use and Land-Cover Change’, [in:] LAMBIN E.F. and GEIST H. (eds.) Land-Use and Land-Cover Change, Global Change – The IGBP Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32202-7_5
• WARWADE, P., HARDAHA, M.K., CHANDNIHA, S.K. and KUMAR, D. (2013), ‘Land use land cover change detection of Patani micro- watershed of Madhya Pradesh using remote sensing data’, Academicjournals, 8 (40), pp. 1983–1990.
• WENG, Q. (2001), ‘A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, southern China’, Inter. J. Rem. Sens., 22 (10), pp. 1999–2014. https://doi.org/10.1080/01431160152043676
• YUAN, F., SAWAYA, K.E., LOEFFELHOLZ, B.C. and BAUER, M.E. (2005), ‘Land cover classification and change analysis of the twin cities (Minnesota) metropolitan area by multitemporal Landsat remote sensing’, Rem. Sens. Envi., 98, pp. 317–328. https://doi.org/10.1016/j.rse.2005.08.006
• ZHOU, P., HUANG, J., PONTIUS, R.G. and HONG, H., (2014), ‘Land Classification and Change Intensity Analysis in a Coastal Watershed of Southeast China’, Sensors, 14, pp. 11640–11658. https://doi.org/10.3390/s140711640

Identifiers

DOI

10.18778/1231-1952.27.1.11