Open Access

ARTICLE

Urban Tree Health Assessment Using Forest Health Monitoring for Eco Forest City Planning in Medan, Indonesia

Suranto^1,2, Rahmawaty^1,3,*, Isnen Fitri^1,4, Luthfi Hakim^1,3, Abdul Rauf^1,5, Delvian^1,3, Mehmet Cetin⁶, Ilknur Zeren Cetin⁶, Siti Aekbal Salleh^7,*

1 Natural Resources and Environmental Management Study Program, Postgraduate School, Universitas Sumatera Utara, Medan, North Sumatra, Indonesia
2 Faculty of Engineering and Computer Science, Department of Civil Engineering, Universitas Pembinaan Masyarakat Indonesia, Medan, North Sumatra, Indonesia
3 Faculty of Forestry, Universitas Sumatera Utara, Deli Serdang, North Sumatra, Indonesia
4 Faculty of Engineering, Department of Architecture, Universitas Sumatera Utara, Medan, North Sumatra, Indonesia
5 Faculty of Agriculture, Department of Agrotechnology, Universitas Sumatera Utara, Medan, North Sumatra, Indonesia
6 Faculty of Architecture, Department of City and Regional Planning, Ondokuz Mayis University, Samsun, Türkiye
7 Institute for Biodiversity and Sustainable Development (IBSD), Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia

* Corresponding Authors: Rahmawaty. Email: ; Siti Aekbal Salleh. Email:

(This article belongs to the Special Issue: Application of Remote Sensing and GIS in Environmental Monitoring and Management)

Revue Internationale de Géomatique 2026, 35, 291-313. https://doi.org/10.32604/rig.2026.081197

Received 25 February 2026; Accepted 06 May 2026; Issue published 05 June 2026

Abstract

Urban trees are a critical component of green infrastructure in tropical cities, yet city-scale evidence on tree health in Indonesia remains limited. This study assessed urban tree health in Medan City using the Forest Health Monitoring (FHM) protocol, Tree Level Index (TLI), GIS-based spatial analysis, and Normalized Difference Vegetation Index (NDVI) validation to support Eco Forest City planning. A total of 1184 trees, representing a 30% sample from 3947 inventoried trees across six sub-districts, were evaluated based on damage location, type, and severity. Average Nearest Neighbor (ANN) and Kernel Density Estimation (KDE) were applied to examine spatial clustering of health classes, while Sentinel-2 NDVI values were extracted as an indicator of vegetation greenness. Overall, 65.79% of trees were classified as healthy, 30.66% as lightly damaged, 3.04% as moderately damaged, and 0.51% as severely damaged. Tree health differed significantly among sub-districts (Kruskal-Wallis χ² = 82.31, p < 0.001), with Medan Tuntungan showing the best condition, whereas Medan Marelan and Medan Amplas showed the poorest profiles. ANN and KDE results indicated that tree health classes were spatially clustered, supporting geographically targeted management. NDVI values differed significantly among health classes (Kruskal-Wallis H = 49.144, p < 0.001), although the weak Spearman correlation suggests that NDVI is more appropriate as supplementary validation than as a substitute for field assessment. These findings support risk-based tree management through routine FHM monitoring, priority inspection in vulnerable sub-districts, spatially explicit maintenance zoning, and gradual species diversification to strengthen Medan’s Eco Forest City planning.

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