Evaluating Land Use Change Detection Methods in Damavand City Using Remote Sensing
Subject Areas : Journal of Radar and Optical Remote Sensing and GISFatah Hasan family 1 , Zahra Azizi 2
1 - msc student, Department of RS-GIS
Faculty of Environment and Energy
Science and Research Branch, Islamic Azad University
Tehran, IRAN
2 - Science and Research Branch, Daneshgah Blvd, Simon Bulivar Blvd, Tehran
Keywords: Landsat, Damavand, Land Use Change Detection, Band Ratio Method,
Abstract :
Land-use change has significant impacts on environmental and natural resources, including water quality, air and terrestrial resources, ecosystem processes and functions, and climate systems. Therefore, accurate and timely detection of land-use changes is crucial for understanding the interactions between humans and natural phenomena and managing natural resources effectively. This study aimed to monitor land-use changes in Damavand city using remote sensing techniques. Two Landsat 5 and 8 satellite images from 1996 and 2018 were used after applying radiometric and atmospheric corrections. Four methods, including band differentiation, band ratio, principal component analysis, and post-classification image detection were employed to detect land-use changes. The results showed that man-made areas increased by 7288 hectares due to construction activities in agricultural fields, leading to a reduction of 4047 hectares of agricultural lands. Additionally, 10324 hectares of rich rangeland cover were transformed into poor pastures. The principal component analysis method using band 3 and the band difference method using band 5 effectively detected the changes in the region; however, the band ratio method did not perform well. The findings of this study can help policymakers make informed decisions about land use planning in Damavand city.
Agrawal A., Yadama, G. N. (1997) How do local institutions mediate market and population pressures on resources? Forest panchayats in Kumaon. India. Dev Change, 28,435–465.
Alawi Panah, K., & Masoudi, M. (2001). Land use mapping using LandsatTM digital data and GIS: Case study of Mok region of Fars province. Journal of Agricultural Sciences and Natural Resources, 8(1), 65-76.
Almutairi, A., & Warner, T. A. (2010). Change detection accuracy and image properties: A study using simulated data. Remote Sensing, 2(6), 1508-1529.
Amir Entekhi, S., Javan, F., & Hassani Moghadam, H. (2017). Detection of land use changes and factors affecting it using artificial neural network: Case study of Talesh city. Journal of Geographic Information System Application and Remote Sensing in Planning, 8 (3), 1-11.
Angelsen, A., Kaimowitz, D. (1999). Rethinking the causes of deforestation: Lessons from economic models. World Bank Res Obser, 14(1),73–98.
Arkhi, S. (2015). Detection of land cover/ land use changes by object-oriented processing of satellite imagery using Idrisi selvi software: Case study of Abdanan area. Journal of Geographical Information, 95, 51-62.
Arkhi, S. (2015). Predicting the trend of spatial land use change using LCM model in GIS environment: Case study of Sarableh region. Journal of Geographical Information, 95, 51-62.
Arnoff, A. (2001). Remote sensing for GIS managers [Trans.]. University of Tehran Press.
Arzandeh, S., & Wang, J. (2003). Monitoring the change of Phragmites distribution using satellite data. Canadian Journal of Remote Sensing, 29(1), 24-35.
Atyabi, S., & Organi, M. (2018). Detection of land use changes using remote sensing data: Case study: Bojnourd city [Paper presentation]. Conference on Civil Engineering, Architecture and Urban Planning of Islamic World Countries, Tabriz, Tabriz University - Shahid Madani University of Azerbaijan - Tabriz Municipality University of Applied Sciences.
Becker, C. D. (1999). Protecting a Garua forest in Ecuador: The role of institutions and ecosystem valuation. Ambio 28(2),156–161.
Bruzzone, L., & Prieto, D. F. (2000). Automatic analysis of the difference image for unsupervised change detection. IEEE Transactions on Geoscience and Remote sensing, 38(3), 1171-1182.
Celik, T. (2009). Unsupervised change detection in satellite images using principal component analysis and $ k $-means clustering. IEEE Geoscience and Remote Sensing Letters, 6(4), 772-776.
Crippen, R. E. (1988). The dangers of underestimating the importance of data adjustments in band ratioing. Remote Sensing, 9(4), 767-776.
Cropper, M., & Griffiths, C. (1994). The interaction of population growth and environmental quality. The American Economic Review, 84(2), 250-254.
El-Kawy, O. A., Rød, J. K., Ismail, H. A., & Suliman, A. S. (2011). Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data. Applied geography, 31(2), 483-494.
Farsi, J., Yousefi, M. (2013). Detection of land use changes using remote measurement data: Case study of Bojnourd plain. Quarterly Journal of Geography and Environmental Studies, 7, 95-106.
Fatemi, S.B., & Rezaei, Y. (2012). Basics of Remote Sensing. Azadeh Publication.
Geist, H. J., Lambin, E. F. (2004). Dynamic causal patterns of desertification. BioScience 54(9), 817–829.
Geist, H., Lambin, E., Palm, C., & Tomich, T. (2006). Agricultural transitions at dryland and tropical forest gins: Actors, scales and trade-offs. In: Brouwer F, McCarl BA (eds) Agriculture and climate beyond 2015: A new perspective on future land use patterns. Environment & Policy Vol. 46. 53–73.
Green, K. (2011). Change matters. Photogrammetric Engineering and Remote Sensing, 77(4), 305-309.
Hadjimitsis, D.G., Papadavid, G., Agapiou, A., Themistocleous, K., Hadjimitsis, M.G., Retalis, A., Michaelides, S., Chrysoulakis, N., Toulios, L., & Clayton C.R.I. (2010). Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices. Natural Hazards and Earth System Sciences, 10, 89–95.
Helming, K., Pérez-Soba, M., & Tabbush, P. (Eds.). (2008). Sustainability impact assessment of land use changes. Springer Science & Business Media.
Im, J., Lu, Z., & Jensen, J. R. (2011). A genetic algorithm approach to moving threshold optimization for binary change detection. Photogrammetric Engineering & Remote Sensing, 77(2), 167-180.
Im, J., Rhee, J., & Jensen, J. R. (2009). Enhancing binary change detection performance using a moving threshold window (MTW) approach. Photogrammetric Engineering & Remote Sensing, 75(8), 951-961.
Jensen, J. R. (1996). Introductory digital image processing: A remote sensing perspective (Ed.). Prentice-Hall Inc.
Jensen, J. R., & Im, J. (2007). Remote sensing change detection in urban environments: In Geo-spatial technologies in urban environments. Springer, Berlin, Heidelberg.
Kennedy, R. E., Townsend, P. A., Gross, J. E., Cohen, W. B., Bolstad, P., Wang, Y. Q., & Adams, P. (2009). Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects. Remote sensing of environment, 113(7), 1382-1396.
Klemas, V. (2011). Remote sensing of wetlands: Case studies comparing practical techniques. Journal of Coastal Research, 27(3), 418-427.
Lambin, E. F., Turner, B. L., Geist, H. J., Agbola, S. B., Angelsen, A., Bruce, J. W., & George, P. (2001). The causes of land-use and land-cover change: moving beyond the myths. Global environmental change, 11(4), 261-269.
Li, Y., Zhang, X., & Liu, X. (2018). Performance evaluation of machine learning algorithms for land cover classification using Landsat imagery. Remote Sensing, 10(8), 1261.
Lotfi, S., Mahmoudzadeh, H., Abdollahi, M., & Salek Farokhi, R. (2010). Application of Spot satellite images to prepare land use map of Marand city with an object-oriented approach. Journal of Remote Sensing Application and GIS in Planning, 2, 47-56.
Lu, D., Mausel, P., Brondizio, E., & Moran, E. (2004). Change detection techniques. International Journal of Remote Sensing, 25(12), 2365-2401.
Lu, T., Ma, K. M., Zhang, W. H., & Fu, B. J. (2006). Differential responses of shrubs and herbs present at the Upper Minjiang River basin (Tibetan Plateau) to several soil variables. Journal of Arid Environments, 67(3), 373-390.
Lunetta, R. S., Knight, J. F., Ediriwickrema, J., Lyon, J. G., & Worthy, L. D. (2006). Land-cover change detection using multi-temporal MODIS NDVI data. Remote sensing of environment, 105(2), 142-154.
Malashahi, S., Mordadi, A., Kamyab, H., & Lotfi, Y. (2014). Detection of land use and land cover changes: Case study of Gorgan city [Paper presentation]. The first national conference on new topics in civil engineering, Bandar Gaz, Islamic Azad University, Bandar Gaz branch.
Millennium Ecosystem Assessment. (2005). Ecosystems and human well-being: Synthesis. Island Press.
Mokhtari, A., Azizi, Z., Fradonbeh, SR. (2017). Epidemiological study and spatial modeling of peste des petits ruminants (PPR) in central area of Iran, Revista MVZ Córdoba, 22 (2), 5899-5909
Nielsen, A. A., and M. J. Canty, (2008), Kernel Principal Component Analysis for Change Detection, in L. Bruzzone (Ed.), Image and Signal Processing for Remote Sensing XIV, Proceedings of the SPIE, 7109, 10.
Omidvar, K., Narangi Fard, M., & Abbasi, H. (2017). Detection of land use changes and vegetation in Yasuj city using remote sensing. Quarterly Journal of Geography and Urban-Regional Planning, 5(16), 111-126.
Rokni, K., Ahmad, A., Solaimani, K., & Hazini, S. (2015). A new approach for surface water change detection: Integration of pixel level image fusion and image classification techniques. International Journal of Applied Earth Observation and Geoinformation, 34, 226-234.
Rutchey, K., & Vilchek, L. (1994). Development of an Everglades vegetation map using a SPOT image and the Global Positioning System. Photogrammetric Engineering and Remote Sensing, 60(6), 767-775.
Sabzqabai, G., Jafarzadeh, K., Dashti, S., Safi Khaneghah, S., & Bazmara Belshti, M. (2016). Detection of land use changes using remote sensing methods and GIS: Case study of Ghaemshahr city. Journal of Environmental Science and Technology, 19(3), 143-157.
Safari, A., Azizi, z. (2021). Potentials and barriers of physical development of the Ruodbar city using Remote Sensing and GIS, Journal of Environmental Science and Technology, 22 (10), 225-235
Sharifi, L., Rasooli, A., Hejazi, M. A., & Rostamzadeh, H. (2013). Detection of land use change / land cover with object-oriented processing of satellite images: Case study of Tabriz city. Journal of Geography and Planning, 17 (44), 203-214.
Shiite, I. (2001). Introduction based on urban planning. Iran University of Science and Technology.
Singh, A. (1989). Review article digital change detection techniques using remotely-sensed data. International journal of remote sensing, 10(6), 989-1003.
Sundarakumar, K., M. Harika, S.A. Begum, S. Yamini and K. Balakrishna. (2012). Land Use and Land Cover Change Detection and Urban Sprawl Analysis of Vijayawada City Using a Landsat Data. Engineering Science & Technology, 4, 170-178.
Tian, M., Wan, S., & Yue, L. (2007). A novel approach for change detection in remote sensing image based on saliency map. In Computer Graphics, Imaging and Visualisation (CGIV), 397-402.
Watts, M. J. (1989). The agrarian question in Africa: Debating the crisis. Prog Hum Geog, 13(1).1–41.
Watts, M. J. (1994). Development II: The privatization of everything. Prog Hum Geog 18(3), 371–384.
Watts, M. J. (1996). Development III: The global agrofood system and late twentieth-century development (or Kautsky redux). Prog Hum Geog 20(2),230–245.
Xu, J. C., Fox, J., Xing, L., Podger, N., Leisz, S., Xihui, A. (1999). Effects of swidden cultivation, population growth, and state policies on land cover in Yunnan, China. Mt Res Dev 19(2),123–132.
Wang, Z., Li, W., & Wang, J. (2019). Land cover classification using deep learning techniques with Sentinel-2 imagery. Remote Sensing Letters, 10(9), 821-830.
Zhang, J., Liu, X., & Zhang, L. (2021). Feature extraction methods for land cover classification using high-resolution satellite imagery: A comparative study. International Journal of Remote Sensing, 42(3), 1075-1093.
Zubairi, Mahmoud and Dalaki, Ahmad. (2007). Principles of interpretation of aerial photographs with application in natural resources. University of Tehran Press.