Geographia Technica, Vol 21, Issue 1, 2026, pp. 271-287
ADVANCING LOW-COST MANGROVE ECOSYSTEM MAPPING: PRECISION VALIDATION OF IPHONE 12 PRO LIDAR FOR DTM GENERATION ACROSS CANOPY DENSITY GRADIENT
Sigit Bayhu IRYANTHONY 
, Anindya WIRASATRIYA , Rudhi PRIBADI , Pujiono Wahyu PURNOMO
ABSTRACT: Precise Digital Terrain Models (DTMs) are essential for mangrove carbon accounting and Measurement, Reporting, and Verification (MRV) frameworks that facilitate climate change mitigation. Although airborne photogrammetry and LiDAR are frequently employed for terrain extraction, their utilization in dense mangrove wetlands is limited by elevated expenses and operational intricacies. This work offers a novel assessment of the iPhone 12 Pro LiDAR sensor as an economical and portable option for Digital Terrain Model (DTM) development in mangrove ecosystems, filling a significant void in accessible carbon monitoring technology. Utilizing the 3D Scanner App for iOS, the study gathered data from 12 locations (55 points per location) encompassing open regions, sparse canopies, and dense canopies, corroborated by 660 NRTK positioning points. The precision of the LiDAR-derived Digital Terrain Model (DTM) was assessed by extensive statistical criteria, such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Bias, Pearson correlation coefficient, and 95% confidence intervals, thereby ensuring rigorous validation of consumer-grade mobile LiDAR for high-resolution topographic mapping. The results indicated exceptional accuracy in open environments (MAE < 0.1 m, negligible RMSE and bias), moderate precision in sparse canopies (MAE 0.086-0.381 m), and diminished performance in dense vegetation (MAE up to 1.064 m, positive bias of 0.928 m). Statistical analysis indicated negligible elevation fluctuation in open areas, however substantial outliers were seen in dense canopies. Regression analysis indicated a robust association in open areas (R² = 0.956), a moderate correlation in sparse vegetation (R² = 0.799), and a lesser correlation in dense canopies (R² = 0.663), implying possibility for enhancement by allometric modifications. Although professional LiDAR systems exhibit superior accuracy, the iPhone LiDAR is a pragmatic and cost-effective option for Digital Terrain Model production in open to moderately vegetated regions. The system's portability and affordability render it especially advantageous for ecological monitoring and geoscientific applications in resource-constrained environments, however dense vegetation poses significant challenges. These findings underscore the capability of consumer-grade LiDAR technology to facilitate precise environmental monitoring while markedly decreasing expenses relative to professional systems.
Keywords: LiDAR; IPhone; DTM; Mangrove; Allometric.
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