IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i2p471-d475624.html
   My bibliography  Save this article

Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model

Author

Listed:
  • Bhanage Vinayak

    (Centre of Studies in Resources Engineering, IIT Bombay, Mumbai 400076, India
    Department of Development Technology, Graduate School for International Development and Cooperation (IDEC), Hiroshima University, Hiroshima 739-8529, Japan)

  • Han Soo Lee

    (Department of Development Technology, Graduate School for International Development and Cooperation (IDEC), Hiroshima University, Hiroshima 739-8529, Japan
    Transdisciplinary Science and Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima 739-8529, Japan)

  • Shirishkumar Gedem

    (Centre of Studies in Resources Engineering, IIT Bombay, Mumbai 400076, India)

Abstract

In this study, prediction of the future land use land cover (LULC) changes over Mumbai and its surrounding region, India, was conducted to have reference information in urban development. To obtain the historical dynamics of the LULC, a supervised classification algorithm was applied to the Landsat images of 1992, 2002, and 2011. Based on spatial drivers and LULC of 1992 and 2002, the multiple perceptron neural network (MLPNN)-based Markov chain model (MCM) was applied to simulate the LULC in 2011, which was further validated using kappa statistics. Thereafter, by using 2002 and 2011 LULC, MLPNN-MCM was applied to predict the LULC in 2050. This study predicted the prompt urban growth over the suburban regions of Mumbai, which shows, by 2050, the Urban class will occupy 46.87% (1328.77 km 2 ) of the entire study area. As compared to the LULC in 2011, the Urban and Forest areas in 2050 will increase by 14.31% and 2.05%, respectively, while the area under the Agriculture/Sparsely Vegetated and Barren land will decline by 16.87%. The class of water and the coastal feature will experience minute fluctuations (<1%) in the future. The predicted LULC for 2050 can be used as a thematic map in various climatic, environmental, and urban planning models to achieve the aims of sustainable development over the region.

Suggested Citation

  • Bhanage Vinayak & Han Soo Lee & Shirishkumar Gedem, 2021. "Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model," Sustainability, MDPI, vol. 13(2), pages 1-22, January.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:471-:d:475624
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/2/471/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/2/471/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert G. Cromley & Dean M. Hanink, 1999. "Coupling land use allocation models with raster GIS," Journal of Geographical Systems, Springer, vol. 1(2), pages 137-153, July.
    2. Chen Liping & Sun Yujun & Sajjad Saeed, 2018. "Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    3. Xu QuanLi & Yang Kun & Wang GuiLin & Yang YuLian, 2015. "Agent-based modeling and simulations of land-use and land-cover change according to ant colony optimization: a case study of the Erhai Lake Basin, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(1), pages 95-118, January.
    4. Botlhe Matlhodi & Piet K. Kenabatho & Bhagabat P. Parida & Joyce G. Maphanyane, 2019. "Evaluating Land Use and Land Cover Change in the Gaborone Dam Catchment, Botswana, from 1984–2015 Using GIS and Remote Sensing," Sustainability, MDPI, vol. 11(19), pages 1-21, September.
    5. Chudech Losiri & Masahiko Nagai & Sarawut Ninsawat & Rajendra P. Shrestha, 2016. "Modeling Urban Expansion in Bangkok Metropolitan Region Using Demographic–Economic Data through Cellular Automata-Markov Chain and Multi-Layer Perceptron-Markov Chain Models," Sustainability, MDPI, vol. 8(7), pages 1-23, July.
    6. Fabrizio Battisti & Orazio Campo & Fabiana Forte, 2020. "A Methodological Approach for the Assessment of Potentially Buildable Land for Tax Purposes: The Italian Case Study," Land, MDPI, vol. 9(1), pages 1-22, January.
    7. Ge Shi & Nan Jiang & Lianqiu Yao, 2018. "Land Use and Cover Change during the Rapid Economic Growth Period from 1990 to 2010: A Case Study of Shanghai," Sustainability, MDPI, vol. 10(2), pages 1-15, February.
    8. Muhammad Hadi Saputra & Han Soo Lee, 2019. "Prediction of Land Use and Land Cover Changes for North Sumatra, Indonesia, Using an Artificial-Neural-Network-Based Cellular Automaton," Sustainability, MDPI, vol. 11(11), pages 1-16, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wael Mostafa & Zenhom Magd & Saif M. Abo Khashaba & Belal Abdelaziz & Ehab Hendawy & Abdelaziz Elfadaly & Mohsen Nabil & Dmitry E. Kucher & Shuisen Chen & Elsayed Said Mohamed, 2023. "Impacts of Human Activities on Urban Sprawl and Land Surface Temperature in Rural Areas, a Case Study of El-Reyad District, Kafrelsheikh Governorate, Egypt," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
    2. Nityaranjan Nath & Dhrubajyoti Sahariah & Gowhar Meraj & Jatan Debnath & Pankaj Kumar & Durlov Lahon & Kesar Chand & Majid Farooq & Pankaj Chandan & Suraj Kumar Singh & Shruti Kanga, 2023. "Land Use and Land Cover Change Monitoring and Prediction of a UNESCO World Heritage Site: Kaziranga Eco-Sensitive Zone Using Cellular Automata-Markov Model," Land, MDPI, vol. 12(1), pages 1-21, January.
    3. repec:bcp:journl:v:9:y:2022:i:12:p:69-77 is not listed on IDEAS
    4. Mirza Waleed & Muhammad Sajjad & Anthony Owusu Acheampong & Md. Tauhidul Alam, 2023. "Towards Sustainable and Livable Cities: Leveraging Remote Sensing, Machine Learning, and Geo-Information Modelling to Explore and Predict Thermal Field Variance in Response to Urban Growth," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    5. Sunil Kumar & Swagata Ghosh & Sultan Singh, 2022. "Polycentric urban growth and identification of urban hot spots in Faridabad, the million-plus metropolitan city of Haryana, India: a zonal assessment using spatial metrics and GIS," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8246-8286, June.
    6. Sahar Ahmadzadeh & Tahmina Ajmal & Ramakrishnan Ramanathan & Yanqing Duan, 2023. "A Comprehensive Review on Food Waste Reduction Based on IoT and Big Data Technologies," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    7. NDOH MBUE Innocent & Elvis Kah, 2022. "Lifting the lid on Land Cover/ Use change and its effects on local ecosystems in the Bamenda highlands of Cameroon," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 9(12), pages 69-77, December.
    8. Xiaowei Chuai & Hongbo Xu & Zemiao Liu & Ai Xiang & Yuting Luo & Wanliu Mao & Tong Wang & Xin Ye & Lijuan Miao & Rongqin Zhao & Fengtai Zhang, 2024. "Promoting low-carbon land use: from theory to practical application through exploring new methods," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    9. Liang Guo & Xiaohuan Xi & Weijun Yang & Lei Liang, 2021. "Monitoring Land Use/Cover Change Using Remotely Sensed Data in Guangzhou of China," Sustainability, MDPI, vol. 13(5), pages 1-14, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nguyen Hong Giang & Yu-Ren Wang & Tran Dinh Hieu & Nguyen Huu Ngu & Thanh-Tuan Dang, 2022. "Estimating Land-Use Change Using Machine Learning: A Case Study on Five Central Coastal Provinces of Vietnam," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    2. Zaheer Abbas & Guang Yang & Yuanjun Zhong & Yaolong Zhao, 2021. "Spatiotemporal Change Analysis and Future Scenario of LULC Using the CA-ANN Approach: A Case Study of the Greater Bay Area, China," Land, MDPI, vol. 10(6), pages 1-26, June.
    3. Hossain Mohammad Arifeen & Md. Shahariar Chowdhury & Haoran Zhang & Tanita Suepa & Nowshad Amin & Kuaanan Techato & Warangkana Jutidamrongphan, 2021. "Role of a Mine in Changing Its Surroundings—Land Use and Land Cover and Impact on the Natural Environment in Barapukuria, Bangladesh," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    4. Opelele Omeno Michel & Yu Ying & Fan Wenyi & Chen Chen & Kachaka Sudi Kaiko, 2021. "Examining Land Use/Land Cover Change and Its Prediction Based on a Multilayer Perceptron Markov Approach in the Luki Biosphere Reserve, Democratic Republic of Congo," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    5. Youjung Kim & Galen Newman, 2019. "Climate Change Preparedness: Comparing Future Urban Growth and Flood Risk in Amsterdam and Houston," Sustainability, MDPI, vol. 11(4), pages 1-24, February.
    6. Bingkui Qiu & Shasha Lu & Min Zhou & Lu Zhang & Yu Deng & Ci Song & Zuo Zhang, 2015. "A Hybrid Inexact Optimization Method for Land-Use Allocation in Association with Environmental/Ecological Requirements at a Watershed Level," Sustainability, MDPI, vol. 7(4), pages 1-25, April.
    7. Yunfeng Hu & Batu Nacun, 2018. "An Analysis of Land-Use Change and Grassland Degradation from a Policy Perspective in Inner Mongolia, China, 1990–2015," Sustainability, MDPI, vol. 10(11), pages 1-22, November.
    8. Milad Asadi & Amir Oshnooei-Nooshabadi & Samira-Sadat Saleh & Fattaneh Habibnezhad & Sonia Sarafraz-Asbagh & John Lodewijk Van Genderen, 2022. "Urban Sprawl Simulation Mapping of Urmia (Iran) by Comparison of Cellular Automata–Markov Chain and Artificial Neural Network (ANN) Modeling Approach," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    9. Jiangsu Li & Weihua Li & Bo Li & Liangrong Duan & Tianjiao Zhang & Qi Jia, 2022. "Construction Land Expansion of Resource-Based Cities in China: Spatiotemporal Characteristics and Driving Factors," IJERPH, MDPI, vol. 19(23), pages 1-20, December.
    10. Ge Shi & Peng Ye & Liang Ding & Agustin Quinones & Yang Li & Nan Jiang, 2019. "Spatio-Temporal Patterns of Land Use and Cover Change from 1990 to 2010: A Case Study of Jiangsu Province, China," IJERPH, MDPI, vol. 16(6), pages 1-19, March.
    11. Enrico Fattinnanzi & Giovanna Acampa & Fabrizio Battisti & Orazio Campo & Fabiana Forte, 2020. "Applying the Depreciated Replacement Cost Method When Assessing the Market Value of Public Property Lacking Comparables and Income Data," Sustainability, MDPI, vol. 12(21), pages 1-22, October.
    12. Harik, G. & Alameddine, I. & Zurayk, R. & El-Fadel, M., 2023. "Uncertainty in forecasting land cover land use at a watershed scale: Towards enhanced sustainable land management," Ecological Modelling, Elsevier, vol. 486(C).
    13. Vitus Tankpa & Li Wang & Alfred Awotwi & Leelamber Singh & Samit Thapa & Raphael Ane Atanga & Xiaomeng Guo, 2021. "Modeling the effects of historical and future land use/land cover change dynamics on the hydrological response of Ashi watershed, northeastern China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 7883-7912, May.
    14. Yan Liu & Yongjiu Feng, 2016. "Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China," Sustainability, MDPI, vol. 8(10), pages 1-16, October.
    15. Weijia Liang & Quan Quan & Bohua Wu & Shuhong Mo, 2023. "Response of Vegetation Dynamics in the Three-North Region of China to Climate and Human Activities from 1982 to 2018," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
    16. Dawid Kudas & Agnieszka Wnęk & Ľubica Hudecová & Robert Fencik, 2024. "Spatial Diversity Changes in Land Use and Land Cover Mix in Central European Capitals and Their Commuting Zones from 2006 to 2018," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
    17. Ruci Wang & Ahmed Derdouri & Yuji Murayama, 2018. "Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area," Sustainability, MDPI, vol. 10(6), pages 1-18, June.
    18. Esther Shupel Ibrahim & Bello Ahmed & Oludunsin Tunrayo Arodudu & Jibril Babayo Abubakar & Bitrus Akila Dang & Mahmoud Ibrahim Mahmoud & Halilu Ahmad Shaba & Sanusi Bello Shamaki, 2022. "Desertification in the Sahel Region: A Product of Climate Change or Human Activities? A Case of Desert Encroachment Monitoring in North-Eastern Nigeria Using Remote Sensing Techniques," Geographies, MDPI, vol. 2(2), pages 1-23, April.
    19. Huafei Yu & Yaolong Zhao & Yingchun Fu, 2019. "Optimization of Impervious Surface Space Layout for Prevention of Urban Rainstorm Waterlogging: A Case Study of Guangzhou, China," IJERPH, MDPI, vol. 16(19), pages 1-28, September.
    20. Linfeng Xu & Xuan Liu & De Tong & Zhixin Liu & Lirong Yin & Wenfeng Zheng, 2022. "Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model," Land, MDPI, vol. 11(5), pages 1-16, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:471-:d:475624. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.