IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i24p16373-d996420.html
   My bibliography  Save this article

Simulation of Land Use/Land Cover Dynamics Using Google Earth Data and QGIS: A Case Study on Outer Ring Road, Southern India

Author

Listed:
  • SrinivasaPerumal Padma

    (Department of Civil Engineering, Saveetha Engineering College, Chennai 602105, Tamilnadu, India)

  • Sivakumar Vidhya Lakshmi

    (Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, Tamilnadu, India)

  • Ramaiah Prakash

    (Department of Civil Engineering, Alagappa Chettiar Government College of Engineering and Technology, Karaikudi 630004, Tamilnadu, India)

  • Sundaresan Srividhya

    (Department of Civil Engineering, Varuvan Vadivelan Institute of Technology, Dharmapuri 636703, Tamilnadu, India)

  • Aburpa Avanachari Sivakumar

    (Department of Mechanical Engineering, Varuvan Vadivelan Institute of Technology, Dharmapuri 636703, Tamilnadu, India)

  • Nagarajan Divyah

    (Department of Civil Engineering, PSG Institute of Technology and Applied Research, Coimbatore 641062, Tamilnadu, India)

  • Cristian Canales

    (Department of Mechanical Engineering (DIM), Faculty of Engineering, University of Concepción, Edmundo Larenas 219, Concepcion 4070409, Chile)

  • Erick I. Saavedra Flores

    (Departamento de Ingeniería en Obras Civiles, Universidad de Santiago de Chile, Av. Ecuador 3659, Estación Central, Santiago 9170201, Chile)

Abstract

The land use and land cover change dynamics is in par with the increasing growth of urban developments and associated sprawl. The objective of the study is to quantify such land cover changes caused due to the urban expansion along the outer ring road using Remote Sensing and GIS. The land cover maps are created for four segments namely Chikkarayapuram, Nazarathpettai, Meppur, and Perungalathur for the years of 2009, 2012, and 2016, respectively. The land cover maps are analyzed for changes among seven classes, namely agriculture, barren land, residential units, industry, water body, other vegetation, and marshland (swamp). Further, the land cover maps of the four segments are analyzed for changes in terms of spatiotemporal aspects (area-based land cover change), environmental aspects (green cover change), and economical factors. The urban growth of the Chikkarayapuram, Nazarathpettai, Meppur, and Perungalathur segment along the outer ring road corridor in the years 2009, 2012, and 2016 are (5.16%, 20.10%, 7.14%, and 12.63%), (14.31%, 30.62%, 13.9%, and 22.18%), and (19.67%, 33.1%, 23.22%, and 40.27%), respectively. The urban areas have increased from 2009 to 2016 by 20, 76,530 sq. m. The agriculture regions have been reduced from 2009 to 2016 by 12, 62,700 sq. m. Besides, using the MOLUSCE plugin in open-source GIS (QGIS), simulated maps for the year 2022 were created based on the land cover maps of the three years (2009, 2012, and 2016) which are then validated with the ground-truth points obtained from Google Earth. The scope of the study utilization of Google Earth Engine (GEE) and automated feature extraction algorithms for predictive analysis.

Suggested Citation

  • SrinivasaPerumal Padma & Sivakumar Vidhya Lakshmi & Ramaiah Prakash & Sundaresan Srividhya & Aburpa Avanachari Sivakumar & Nagarajan Divyah & Cristian Canales & Erick I. Saavedra Flores, 2022. "Simulation of Land Use/Land Cover Dynamics Using Google Earth Data and QGIS: A Case Study on Outer Ring Road, Southern India," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16373-:d:996420
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/24/16373/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/24/16373/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rizwan Muhammad & Wenyin Zhang & Zaheer Abbas & Feng Guo & Luc Gwiazdzinski, 2022. "Spatiotemporal Change Analysis and Prediction of Future Land Use and Land Cover Changes Using QGIS MOLUSCE Plugin and Remote Sensing Big Data: A Case Study of Linyi, China," Land, MDPI, vol. 11(3), pages 1-24, March.
    Full references (including those not matched with items on IDEAS)

    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. Ram Avtar & Apisai Vakacegu Rinamalo & Deha Agus Umarhadi & Ankita Gupta & Khaled Mohamed Khedher & Ali P. Yunus & Bhupendra P. Singh & Pankaj Kumar & Netrananda Sahu & Anjar Dimara Sakti, 2022. "Land Use Change and Prediction for Valuating Carbon Sequestration in Viti Levu Island, Fiji," Land, MDPI, vol. 11(8), pages 1-17, August.
    2. Sylwia Barwicka & Małgorzata Milecka, 2022. "The “Perfect Village” Model as a Result of Research on Transformation of Plant Cover—Case Study of the Puchaczów Commune," Sustainability, MDPI, vol. 14(21), pages 1-22, November.
    3. Chunliu Gao & Deqiang Cheng & Javed Iqbal & Shunyu Yao, 2023. "Spatiotemporal Change Analysis and Prediction of the Great Yellow River Region (GYRR) Land Cover and the Relationship Analysis with Mountain Hazards," Land, MDPI, vol. 12(2), pages 1-24, January.
    4. Jessica Strzempko & Robert Gilmore Pontius, 2023. "The Flow Matrix Offers a Straightforward Alternative to the Problematic Markov Matrix," Land, MDPI, vol. 12(7), pages 1-18, July.
    5. Md Shihab Uddin & Badal Mahalder & Debabrata Mahalder, 2023. "Assessment of Land Use Land Cover Changes and Future Predictions Using CA-ANN Simulation for Gazipur City Corporation, Bangladesh," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
    6. Julie Echeverría-Puertas & Magdy Echeverría & Franklin Cargua & Theofilos Toulkeridis, 2023. "Spatial Dynamics of the Shore Coverage within the Zone of Influence of the Chambo River, Central Ecuador," Land, MDPI, vol. 12(1), pages 1-21, January.
    7. Saulo Folharini & António Vieira & António Bento-Gonçalves & Sara Silva & Tiago Marques & Jorge Novais, 2023. "A Framework Using Open-Source Software for Land Use Prediction and Climate Data Time Series Analysis in a Protected Area of Portugal: Alvão Natural Park," Land, MDPI, vol. 12(7), pages 1-16, June.
    8. Nivin Abdelrahim Hasan & Dongkai Yang & Fayha Al-Shibli, 2023. "A Historical–Projected Analysis in Land Use/Land Cover in Developing Arid Region Using Spatial Differences and Its Relation to the Climate," Sustainability, MDPI, vol. 15(3), pages 1-24, February.

    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:14:y:2022:i:24:p:16373-:d:996420. 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.