Spatial Analysis of Vegetation Density Using MSARVI Algorithm and Sentinel-2A Imagery in Ternate City, Indonesia

Authors

  • Heinrich Rakuasa Department of Geography, Faculty of Geology and Geography, Tomsk State University
  • Viktor Vladimirovich Budnikov Department of Geography, Faculty of Geology and Geography, Tomsk State University, Ulitsa Arkadiya Ivanova

DOI:

https://doi.org/10.69693/jesa.v2i1.14

Keywords:

Ternate, Sentinel-2A, MSARVI, Vegetation Density

Abstract

This study aims to analyze vegetation density in Ternate City, Indonesia, using the Modified Soil-Adjusted and Atmospherically Resistant Vegetation Index (MSARVI) algorithm and Sentinel-2A images processed through Google Earth Engine. The analysis results show that the vegetation density index values range from -0.54 to 1.16, with normalization resulting in four density classes: low, medium, dense, and very dense. Ternate Island sub-district had the largest area of very dense vegetation (4,133.12 hectares), while Ternate Tengah sub-district showed the lowest vegetation density, reflecting the significant impact of urbanization. This study revealed that despite anthropogenic pressures, Ternate Island remains an ecologically critical zone. These findings emphasize the importance of conservation efforts and afforestation initiatives to improve environmental resilience amidst the growing challenges of climate change and urban development.

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References

[1] Kusrini, S. Worosuprojo, A. Kurniawan, and D. R. Hizbaron, “Land Use Changes of Ternate Island 2017-2022,” E3S Web Conf., vol. 468, p. 10005, Dec. 2023, doi: 10.1051/e3sconf/202346810005.

[2] P. C. Latue, H. Rakuasa, and D. A. Sihasale, “Analisis Kerapatan Vegetasi Kota Ambon Menggunakan Data Citra Satelit Sentinel-2 dengan Metode MSARVI Berbasis Machine Learning pada Google Earth Engine,” sudo J. Tek. Inform., vol. 2, no. 2, pp. 68–77, Jun. 2023, doi: 10.56211/sudo.v2i2.270.

[3] A. Ayyappa Reddy and M. Shashi, “IMPACT OF UAV AND SENTINEL-2A IMAGERY FUSION ON VEGETATION INDICES PERFORMANCE,” ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci., vol. X-1/W1-202, pp. 785–792, 2023, doi: 10.5194/isprs-annals-X-1-W1-2023-785-2023.

[4] L. Li, X. Zhou, L. Chen, L. Chen, Y. Zhang, and Y. Liu, “Estimating Urban Vegetation Biomass from Sentinel-2A Image Data,” Forests, vol. 11, no. 2, p. 125, Jan. 2020, doi: 10.3390/f11020125.

[5] Heinrich Rakuasa, “Classification of Sentinel-2A Satellite Image for Ternate City land cover using Random Forest Classification in SAGA GIS Software,” DNS – Digit. NEXUS Syst. JOURNA, vol. 1, no. 1, pp. 34–36, 2025, doi: http://dx.doi.org/10.26753/dns.v1i1.1554.

[6] D. A. Umarhadi and A. Muammar, “Regression model accuracy comparison on mangrove canopy density mapping,” Digit. Press Phys. Sci. Eng., vol. 1, p. 00001, Oct. 2018, doi: 10.29037/digitalpress.11249.

[7] Y. Mega Nurzihan, A. Rinzani, M. R. Kamaluddin, R. Ridwana, and L. Somantri, “Analisis Indeks Kerapatan Vegetasi di Desa Cihanjuang Rahayu Menggunakan Citra Satelit Sentinel-2A dengan Metode MSARVI,” J. Pendidik. Geogr. Undiksha, vol. 11, no. 3, pp. 223–233, Dec. 2023, doi: 10.23887/jjpg.v11i3.66790.

[8] F. A. Piawai, A. S. A. F. Permana, A. M. Fajar, R. Ridwana, and L. Somantri, “PEMANFAATAN CITRA LANDSAT 8 UNTUK PEMETAAN SEBARAN DAN KERAPATAN EKOSISTEM MANGROVE DI KECAMATAN CIJULANG KABUPATEN PANGANDARAN,” J. Geogr., vol. 11, no. 1, pp. 53–64, Apr. 2022, doi: 10.24036/geografi/vol11-iss1/2552.

[9] O. Mutanga and L. Kumar, “Google Earth Engine Applications,” Remote Sens., vol. 11, no. 5, p. 591, Mar. 2019, doi: 10.3390/rs11050591.

[10] D. A. S. Heinrich Rakuasa, “Analysis of Vegetation Index in Ambon City Using Sentinel-2 Satellite Image Data with Normalized Difference Vegetation Index (NDVI) Method based on Google Earth Engine,” J. Innov. Inf. Technol. Appl., vol. 5, no. 1, pp. 74–82, 2023, doi: https://doi.org/10.35970/jinita.v5i1.1869.

[11] L. K. Onisimo Muntaga, “Google Earth Engine Applications,” remotesensing, pp. 11–14, 2019, doi: 10.3390/rs11050591.

[12] M. Drusch et al., “Sentinel-2: ESA’s Optical High-Resolution Mission for GMES Operational Services,” Remote Sens. Environ., vol. 120, pp. 25–36, May 2012, doi: 10.1016/j.rse.2011.11.026.

[13] A. R. Huete, G. Hua, J. Qi, A. Chehbouni, and W. J. D. van Leeuwen, “Normalization of multidirectional red and NIR reflectances with the SAVI,” Remote Sens. Environ., vol. 41, no. 2–3, pp. 143–154, Aug. 1992, doi: 10.1016/0034-4257(92)90074-T.

[14] J. O. Umanailo, H. A., Franklin, P. J., & Waani, “Perkembangan Pusat Kota Ternate (Studi Kasus: Kecamatan Ternate Tengah),” Spasial, vol. 4, no. 3, pp. 222–233, 2017.

[15] Y. Rakuasa, H., & Pakniany, “Spatial Dynamics of Land Cover Change in Ternate Tengah District, Ternate City, Indonesia,” Forum Geogr., vol. 36, no. 2, pp. 126–135, 2022, doi: DOI: 10.23917/forgeo.v36i2.19978.

[16] H. Latue, P. C., & Rakuasa, “Analysis of Land Cover Change Due to Urban Growth in Central Ternate District, Ternate City using Cellular Automata-Markov Chain,” J. Appl. Geospatial Inf., vol. 7, no. 1, pp. 722–728, 2023, doi: https://doi.org/10.30871/jagi.v7i1.4653.

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Published

21-04-2025

How to Cite

Rakuasa, H., & Budnikov, V. V. (2025). Spatial Analysis of Vegetation Density Using MSARVI Algorithm and Sentinel-2A Imagery in Ternate City, Indonesia. Journal of Engineering and Science Application, 2(1), 36–41. https://doi.org/10.69693/jesa.v2i1.14

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