Mapping Of Aboveground Biomass Estimation Based On Vegetation Index In Banjarbaru City
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Abstract
Climate change increases the importance of aboveground biomass information as an indicator of carbon stocks and a basis for urban vegetation management. This study aims to determine the best model for estimating aboveground biomass using Sentinel-2 imagery-based vegetation indices and to map biomass distribution in Banjarbaru City. The study uses a quantitative approach with remote sensing-based spatial analysis. The study population is all woody vegetation in Banjarbaru City, while the sample consists of 45 plots determined using stratified random sampling. The research instruments include Diameter at Breast Height (DHT), tree height, Global Positioning System (GPS), and Sentinel-2B Level-2A imagery. Data analysis was carried out through biomass calculations using allometric equations, Pearson correlation analysis, linear, exponential, polynomial, and power regressions, regression assumption testing, model validation using SA, SR, RMSE, bias, and chi-square, and spatial mapping. The results showed that the Linear SAVI model was the best model with the equation B = -287.341 + 517.644 SAVI and an R² value of 0.905. In conclusion, the Linear SAVI model is able to provide accurate and representative biomass estimates, while the application of masking improves the quality of biomass mapping, thereby supporting carbon inventory and green open space planning.
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References
Badan Pusat Statistik Kota Banjarbaru. (2025). Kota Banjarbaru dalam angka 2025. Badan Pusat Statistik.
Bindu, G., Rajan, P., Jishnu, E. S., & Ajith Joseph, K. (2020). Carbon stock assessment of mangroves using remote sensing and geographic information system. Egyptian Journal of Remote Sensing and Space Science, 23(1), 1–9. https://doi.org/10.1016/j.ejrs.2018.04.006
Chave, J., Réjou-Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B. C., Duque, A., Eid, T., Fearnside, P. M., Goodman, R. C., Henry, M., Martínez-Yrízar, A., Mugasha, W. A., Muller-Landau, H. C., Mencuccini, M., Nelson, B. W., Ngomanda, A., Nogueira, E. M., Ortiz-Malavassi, E., ... Vieilledent, G. (2014). Improved allometric models to estimate the aboveground biomass of tropical trees. Global Change Biology, 20(10), 3177–3190. https://doi.org/10.1111/gcb.12629
Firmansyah, A., Hamzah, H., & Achmad, E. (2022). Pemodelan penginderaan jauh untuk estimasi simpanan karbon di Blok 1 PT Alam Bukit Tigapuluh. Journal of Science and Applicative Technology, 6(2), 99–108. https://doi.org/10.35472/jsat.v6i2.964
Muhaimin, M., & Ramali, A. (2021). Development of leading sectors and competitiveness of animal husbandry commodities in Banjarbaru City. Advances in Social Science, Education and Humanities Research, 525, 399–403.
Netsianda, A., & Mhangara, P. (2025). Aboveground biomass estimation in a grassland ecosystem using Sentinel-2 satellite imagery and machine learning algorithms. Environmental Monitoring and Assessment, 197(2), 1–16. https://doi.org/10.1007/s10661-024-13610-1
Nirwana, H. D., Saidy, A. R., Hatta, G. M., & Nugroho, A. (2024). Design of a green city with lower carbon based on vegetation in Banjarbaru using Sentinel-2. Journal of Applied Data Sciences, 5(2), 583–599.
Patty, S. I., Nurdiansah, D., Rizqi, M. P., & Huwae, R. (2022). Analysis of mangrove vegetation and distribution using Landsat 8 images in Bolaang Mongondow East, North Sulawesi. Jurnal Ilmiah PLATAX, 10(2), 251–260. https://doi.org/10.35800/jip.v10i2.41069
Phiri, D., Simwanda, M., Salekin, S., Ryirenda, V. R., Murayama, Y., Ranagalage, M., Oktaviani, N., Kusuma, H. A., Zhang, T., Su, J., Liu, C., Chen, W. H., Liu, H., Liu, G., Cavur, M., Duzgun, H. S., Kemec, S., Demirkan, D. C., Chairet, R., ... Peerbhay, K. (2020). Sentinel-2 data for land cover/use mapping: A review. Remote Sensing, 12(14), Article 2291. https://doi.org/10.3390/rs12142291
Pietersz, J. H., Pribadi, R., Pentury, R., & Ario, R. (2024). Estimasi tutupan kanopi berdasarkan NDVI dan kondisi tutupan tajuk pada ekosistem mangrove Negeri Passo, Teluk Ambon Dalam. Jurnal Kelautan Tropis, 27(2), 197–208. https://doi.org/10.14710/jkt.v27i2.22090
Rosianty, Y., Lensari, D., & Syachroni, S. H. (2020). Memotivasi masyarakat untuk menanam pohon dalam mendukung terbentuknya kota hijau di Kelurahan Sukamulya Kecamatan Sematang Borang Kota Palembang. Altifani: International Journal of Community Engagement, 1(1), 40–45. https://doi.org/10.32502/altifani.v1i1.3009
Santoso, N., Sutopo, Pambudi, G. P., Danarta, V. F., Wibisono, R. A., Astuti, T. P., & Wicaksono, D. A. (2021). Pendugaan biomassa dan serapan karbon di beberapa areal taman hutan kota Jakarta, Bekasi dan Bogor. Jurnal Penelitian Hutan Tanaman, 18(1), 167–186.
Wai, P., Su, H., & Li, M. (2022). Estimating aboveground biomass of two different forest types in Myanmar from Sentinel-2 data with machine learning and geostatistical algorithms. Remote Sensing, 14(9), Article 2146. https://doi.org/10.3390/rs14092146