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Monitoring 3D Changes in Urban Forests Using Landscape Metrics Analyses Based on Multi-Temporal Remote Sensing Data

Author

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  • Karolina Zięba-Kulawik

    (Department of Forest Resource Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, Poland
    Urban Development and Mobility Department, Luxembourg Institute of Socio-Economic Research (LISER), L-4366 Esch-sur-Alzette, Luxembourg)

  • Piotr Wężyk

    (Department of Forest Resource Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, Poland
    ProGea Consulting, 31-223 Krakow, Poland)

Abstract

Rapid urbanization is causing changes in green spaces and ecological connectivity. So far, urban ecosystem research has mainly focused on using landscape metrics (LM) in two-dimensional (2D) space. Our study proposes three-dimensional (3D) measures of urban forests (UF) and LM calculations using LiDAR technology. First, we estimated the UF volume of Krakow (Poland) and the distribution of vegetation (low, medium, high) using a voxel-based GEOBIA approach based on the ALS LiDAR point cloud, satellite imagery, and aerial orthophotos at specific timestamps: 2006, 2012, 2017. Then, the appropriate landscape metrics were selected (NP, AREA_MN, CONTIG_MN, LPI, PARA_MN, SPLIT, MESH, PD, DIVISION, LSI) to quantify the differences between the 2D- and 3D-derived vegetation structures and detect changes in the urban landscape. The results showed that areas with low vegetation decreased due to the expansion of built-up areas, while areas with medium and high vegetation increased in Krakow between 2006, 2012, and 2017. We have shown that the lack of information on the vertical features of vegetation, i.e., 2D greenery analysis, leads to an overestimation of landscape connectivity. In the 3D vegetation classes, it was observed that low vegetation was the best connected, followed by high vegetation, while medium vegetation was dispersed in the city space. These results are particularly relevant for the urban environment, where the distribution of green space is crucial for the provision of ecosystem services.

Suggested Citation

  • Karolina Zięba-Kulawik & Piotr Wężyk, 2022. "Monitoring 3D Changes in Urban Forests Using Landscape Metrics Analyses Based on Multi-Temporal Remote Sensing Data," Land, MDPI, vol. 11(6), pages 1-19, June.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:6:p:883-:d:835635
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    References listed on IDEAS

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    2. Lausch, Angela & Blaschke, Thomas & Haase, Dagmar & Herzog, Felix & Syrbe, Ralf-Uwe & Tischendorf, Lutz & Walz, Ulrich, 2015. "Understanding and quantifying landscape structure – A review on relevant process characteristics, data models and landscape metrics," Ecological Modelling, Elsevier, vol. 295(C), pages 31-41.
    3. Yue Lin & Wenzhan An & Muye Gan & AmirReza Shahtahmassebi & Ziran Ye & Lingyan Huang & Congmou Zhu & Lu Huang & Jing Zhang & Ke Wang, 2021. "Spatial Grain Effects of Urban Green Space Cover Maps on Assessing Habitat Fragmentation and Connectivity," Land, MDPI, vol. 10(10), pages 1-18, October.
    4. Theodore A. Endreny, 2018. "Strategically growing the urban forest will improve our world," Nature Communications, Nature, vol. 9(1), pages 1-3, December.
    5. Johan Colding & Åsa Gren & Stephan Barthel, 2020. "The Incremental Demise of Urban Green Spaces," Land, MDPI, vol. 9(5), pages 1-11, May.
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