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A New Approach to High-Resolution Urban Land Use Classification Using Open Access Software and True Color Satellite Images

Author

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  • Fernando Chapa

    (Technische Universität Darmstadt, Institute of Applied Geosciences, Section of Ecological Engineering, SEE-URBAN-WATER Research Group, Schnittspahnstraße 9, 64287 Darmstadt, Germany)

  • Srividya Hariharan

    (National Institute of Technology Tiruchirappalli (NIT Trichy), Department of Civil Engineering, Tanjore Main Road, Tiruchirappalli 620015, Tamil Nadu, India)

  • Jochen Hack

    (Technische Universität Darmstadt, Institute of Applied Geosciences, Section of Ecological Engineering, SEE-URBAN-WATER Research Group, Schnittspahnstraße 9, 64287 Darmstadt, Germany)

Abstract

Urbanization nowadays results in the most dynamic and drastic changes in land use/land cover, with a significant impact on the environment. A detailed analysis and assessment of this process is necessary to take informed actions to reduce its impact on the environment and human well-being. In most parts of the world, detailed information on the composition, structure, extent, and temporal changes of urban areas is lacking. The purpose of this study is to present a methodology to produce high-resolution land use/land cover maps by the use of free software and satellite imagery. These maps can help to understand dynamic urbanizations processes to plan, design, and coordinate sustainable urban development plans, especially in areas with limited resources and advancing environmental degradation. A series of high-resolution true color images provided by Google Earth Pro were used to do initial classifications with the Semi-Automatic Classification Plug-in in QGIS. Afterwards, a new methodology to improve the classification by the elimination of shadows and clouds, and a reduction of misclassifications through superimposition was applied. The classification was carried out for three urban areas in León, Nicaragua, with different degrees of urbanization for the years 2009, 2015, and 2018. Finally, the accuracy of the classification was analyzed using randomly defined validation polygons. The results are three sets of high-resolution land use/land cover maps of the initial and the improved classification, showing the detailed structures and temporal dynamics of urbanization. The average accuracy of classification reaches 74%, but up to 85% for the best classification. The results clearly identify advancing urbanization, the loss of vegetation and riparian zones, and threats to urban ecosystems. In general, the level of detail and simplicity of our methodology is a valuable tool to support sustainable urban management, although its application is not limited to these areas and can also be employed to track changes over time, providing therefore, relevant information to a wide range of decision-makers.

Suggested Citation

  • Fernando Chapa & Srividya Hariharan & Jochen Hack, 2019. "A New Approach to High-Resolution Urban Land Use Classification Using Open Access Software and True Color Satellite Images," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5266-:d:270595
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    References listed on IDEAS

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    1. Liyin Shen & Chenyang Shuai & Liudan Jiao & Yongtao Tan & Xiangnan Song, 2016. "A Global Perspective on the Sustainable Performance of Urbanization," Sustainability, MDPI, vol. 8(8), pages 1-16, August.
    2. Anna Lüke & Jochen Hack, 2018. "Comparing the Applicability of Commonly Used Hydrological Ecosystem Services Models for Integrated Decision-Support," Sustainability, MDPI, vol. 10(2), pages 1-22, January.
    3. Mingxing Chen & Hua Zhang & Weidong Liu & Wenzhong Zhang, 2014. "The Global Pattern of Urbanization and Economic Growth: Evidence from the Last Three Decades," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-15, August.
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    2. Muhammad Amir Siddique & Fan Boqing & Liu Dongyun, 2023. "Modeling the Impact and Risk Assessment of Urbanization on Urban Heat Island and Thermal Comfort Level of Beijing City, China (2005–2020)," Sustainability, MDPI, vol. 15(7), pages 1-18, March.
    3. Lovelace, Robin & Parkin, John & Cohen, Tom, 2020. "Open access transport models: A leverage point in sustainable transport planning," Transport Policy, Elsevier, vol. 97(C), pages 47-54.
    4. Pedro Aguilar & Edgar Mendoza & Rodolfo Silva, 2021. "Interaction between Tourism Carrying Capacity and Coastal Squeeze in Mazatlan, Mexico," Land, MDPI, vol. 10(9), pages 1-24, August.

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