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Carbon-Stock Estimation Using High-Resolution Remote Sensing Imagery at Universitas Padjadjaran: A Spatial–Temporal Analysis to Support Sustainable and Green Campus Initiatives

Author

Listed:
  • Rahmihafiza Hanafi

    (Center for Sustainable Campus Development and Environmental Safety, Universitas Padjadjaran, Jl. Ir. Soekarno Km 21, Sumedang 45363, West Java, Indonesia)

  • Bakhrul Midad

    (Department of Geophysics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jl. Ir. Soekarno Km 21, Sumedang 45363, West Java, Indonesia)

  • Rania Alifa Desenaldo

    (Department of Civil Engineering, Geo and Environmental Sciences, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany)

  • Bambang Wijatmoko

    (Department of Geophysics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jl. Ir. Soekarno Km 21, Sumedang 45363, West Java, Indonesia)

  • Gemilang Lara Utama Saripudin

    (Department of Food Industrial Technology, Faculty of Agro-industrial Technology, Universitas Padjadjaran, Jl. Ir. Soekarno Km 21, Sumedang 45363, West Java, Indonesia)

  • Muhammad Aufaristama

    (College of Science, Geosciences Department, United Arab Emirates University, Al Ain 15551, United Arab Emirates)

  • Kusnahadi Susanto

    (Center for Sustainable Campus Development and Environmental Safety, Universitas Padjadjaran, Jl. Ir. Soekarno Km 21, Sumedang 45363, West Java, Indonesia
    Department of Geophysics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jl. Ir. Soekarno Km 21, Sumedang 45363, West Java, Indonesia)

  • Irwan Ary Dharmawan

    (Department of Geophysics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jl. Ir. Soekarno Km 21, Sumedang 45363, West Java, Indonesia)

Abstract

Estimating carbon stocks in semi-urban ecosystems remains challenging due to spatial heterogeneity and the scale limitations of conventional datasets. This study aims to estimate and analyse the spatial and temporal distribution of carbon stocks at Universitas Padjadjaran using high-resolution remote sensing imagery and to support sustainable campus and green campus initiatives. Multi-temporal data from WorldView-2 (2015, 2017), WorldView-3 (2021), and Legion-03 (2025) were used to derive vegetation indices, followed by aboveground biomass (AGB) modelling through regression analysis. Carbon stock was calculated using a standard conversion factor of 0.5. The results show a consistent increase in vegetation density and carbon stock, with average values rising from 20.381 tonnes/ha in 2015 to 29.160 tonnes/ha in 2025. The use of the MSAVI produced an accurate model for predicting AGB (R 2 = 0.987–0.993). This study introduces a novel integration of high-resolution imagery using MSAVI to improve AGB estimation at the campus scale, providing a more detailed and reliable approach for carbon assessment in heterogeneous semi-urban environments and contributing to the implementation of sustainable, environmentally friendly campus management strategies.

Suggested Citation

  • Rahmihafiza Hanafi & Bakhrul Midad & Rania Alifa Desenaldo & Bambang Wijatmoko & Gemilang Lara Utama Saripudin & Muhammad Aufaristama & Kusnahadi Susanto & Irwan Ary Dharmawan, 2026. "Carbon-Stock Estimation Using High-Resolution Remote Sensing Imagery at Universitas Padjadjaran: A Spatial–Temporal Analysis to Support Sustainable and Green Campus Initiatives," Sustainability, MDPI, vol. 18(12), pages 1-22, June.
    • Handle: RePEc:gam:jsusta:v:18:y:2026:i:12:p:6240-:d:1969663
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