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Quality Index Approach for Analysis of Urban Green Infrastructure in Himalayan Cities

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  • Mangalasseril Mohammad Anees

    (Spatial Analysis and Informatics Lab (SAIL), School of Environmental Sciences, Jawaharlal Nehru University, New Delhi 110067, India
    UFZ—Helmholtz Centre for Environmental Research, Department of Urban and Environmental Sociology, 04318 Leipzig, Germany)

  • Ellen Banzhaf

    (UFZ—Helmholtz Centre for Environmental Research, Department of Urban and Environmental Sociology, 04318 Leipzig, Germany)

  • Jingxia Wang

    (Department of Urban Studies and Planning, University of Sheffield, Western Bank, Sheffield S10 2TN, UK)

  • Pawan Kumar Joshi

    (Spatial Analysis and Informatics Lab (SAIL), School of Environmental Sciences, Jawaharlal Nehru University, New Delhi 110067, India
    Special Centre for Disaster Research, Jawaharlal Nehru University, New Delhi 110067, India)

Abstract

In fast urbanizing cities, fragmentation of urban green infrastructure (UGI) commonly arises due to lack of efficient planning to maintain the quantity and improve their quality. As ecological processes and landscape patterns are closely intertwined, it is a prerequisite to investigate landscape structure when aiming at better provision of ecosystem services. This study integrates remote sensing, geographic information system, combination of landscape metrics, and multi-variated statistics to delineate structural attributes influencing UGI Quality (UGIQ). We exemplify our methodology in three capital cities of Indian Himalayan states at administrative ward level. The UGIQ is derived by comparing landscape characters defined by nine metrics denoting area, shape, and aggregation attributes. By employing principal component analysis (PCA) and multi-collinearity diagnosis, a set of quality defining metrics are obtained for each city. Further, to gain insightful spatial basis for improving connectivity, Morphological Spatial Pattern Analysis (MSPA) is used to visualize and classify patches into seven morphological classes. Landscape characterization highlights a pattern of low-quality wards having a limited number and area of UGI patches in urban centers, and high-quality wards with complex and aggregated patches towards fringes. PCA identifies the positive influence of area (LPI, AREA_MN) and shape (LSI, FRAC_AM, CONTIG) metrics and negative influence of patch distance (ENN_MN) and fragmentation (PD) on UGIQ in different combinations across the cities. Higher shares of morphological core and edge classes are recognized for overall UGIQ improvement. The results provide quantitative measures to develop integrated spatial planning strategies.

Suggested Citation

  • Mangalasseril Mohammad Anees & Ellen Banzhaf & Jingxia Wang & Pawan Kumar Joshi, 2023. "Quality Index Approach for Analysis of Urban Green Infrastructure in Himalayan Cities," Land, MDPI, vol. 12(2), pages 1-21, January.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:2:p:279-:d:1040190
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    References listed on IDEAS

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    3. 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.
    4. Karsten Rusche & Mario Reimer & Rico Stichmann, 2019. "Mapping and Assessing Green Infrastructure Connectivity in European City Regions," Sustainability, MDPI, vol. 11(6), pages 1-12, March.
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