Line-of-Sight Dominance Over Vegetation: Simulation-Based LoRa Performance in Tropical Forest Terrain
DOI:
10.33395/sinkron.v10i1.15627Keywords:
elevation effects, environmental monitoring, line-of-sight, LoRa, LPWAN, propagation models, tropical forest, vegetation attenuationAbstract
Low-Power Wide-Area Network (LPWAN) technologies, especially LoRa, are receiving considerable interest for applications involving environmental monitoring in difficult terrain conditions. However, existing research predominantly examines vegetation attenuation or terrain elevation effects separately, leaving a critical research gap in understanding their combined and interactive impacts on LoRa connectivity in tropical forest environments. Furthermore, most studies rely on simplified propagation models that inadequately represent the complex radio environment of tropical forests, and few investigations systematically compare the relative importance of vegetation density, elevation, and line-of-sight conditions. This work addresses these gaps through an in-depth simulation-based investigation of LoRa network behavior in the University of Brawijaya (UB) Forest, which serves as a typical tropical forest setting in Indonesia. We performed detailed simulations using Python and LoRaSim, employing fine-resolution elevation datasets and precise vegetation classification to examine how dense vegetation, medium vegetation, and elevation parameters influence LoRa communication performance. Our findings indicate that, in contrast to traditional propagation models, nodes located in dense vegetation zones reached a 90.0% success rate, as opposed to 65.0% in zones without vegetation. Additional investigation shows that line-of-sight presence (28.6% versus 0.0% success rate) and relative elevation relative to the gateway (11.1% versus 27.3% success rate for nodes positioned above and below the gateway, respectively) represent more crucial factors for connectivity compared to vegetation attenuation by itself. These outcomes offer important guidance for enhancing LoRa-based environmental monitoring systems in tropical forest settings through strategic node positioning that considers elevation characteristics and line-of-sight availability.
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Copyright (c) 2025 Rachmad Atmoko, Rifqi Hidayatullah, Septian Na’im, Izzun Ni`am, AB Setiawan
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