SPATIAL TEMPORAL MAPPING OF VEGETATION COVER INDICES USING SENTINEL-2 MULTISPECTRAL INSTRUMENT IN UNAAHA CITY

Authors

  • Septianto Aldiansyah Department of Geography, Faculty of Mathematics and Natural Sciences, University of Indonesia
  • Duwi Setiyo Wigati Ningsih Department of Geography, Faculty of Social Science, State University of Malang
  • Risna Department of Microbiology, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University

Keywords:

NDVI, EVI, SAVI, MSARVI, vegetation cover, Google Earth Engine

Abstract

Vegetation cover in urban areas contributes to providing livable ecosystem services for humans. As urbanization continues to expand, vegetation cover in urban areas will change rapidly. This research aims to monitor changes in vegetation cover in the last 5 years in Unaaha City using Google Earth Engine. This study also explores vegetation index algorithms such as NDVI, EVI, SAVI, and MSARVI. The research results show that forest vegetation cover continues to decline, followed by an increase in built-up land with an average change of 1,021 ha or the equivalent of 55% of the total area. This research also found that the NDVI algorithm had the best average accuracy with a value of OA=82.54%, followed by MSARVI=73.23%, SAVI=69.52%, and EVI=63.62%. This makes the NDVI method have good accuracy requirements for identifying vegetation compared to other vegetation index algorithms.

References

Aldiansyah, S., Mannesa, M. D. M., & Supriatna, S. (2021). Monitoring of vegetation cover changes with geomorphological forms using Google Earth engine in Kendari City. Jurnal Geografi Gea, 21(2), 159-170.

Aldiansyah, S., & Saputra, R. A. (2023a). Comparison of machine learning algorithms for land use and land cover analysis using Google Earth engine (Case study: Wanggu watershed). International Journal of Remote Sensing and Earth Sciences (IJReSES), 19(2), 197-210.

Aldiansyah, S., & Saputra, R. A. (2023b). Monitoring Shoreline Changes for Evaluation of Regional Spatial Plans Using Google Earth Engine in West Wawonii District. Jurnal Geografi: Media Informasi Pengembangan dan Profesi Kegeografian, 20(1), 1-8.

Aldiansyah, S., & Saputra, R. A. (2023c). Spatial model of industrial area suitability using spatial multi criteria evaluation: A case study in Kendari City. Sustinere: Journal of Environment and Sustainability, 6(3), 214–226.

Aldiansyah, S., & Wardani, F. (2023). Analisis Spasio-Temporal Fenomena Urban Heat Island dan Hubungannya Terhadap Aspek Fisik di Kota Makassar (1993-2021). Jurnal Sains & Teknologi Modifikasi Cuaca, 24(1), 1-11.

Cai, Y., Zhang, M., & Lin, H. (2020). Estimating the urban fractional vegetation cover using an object-based mixture analysis method and Sentinel-2 MSI imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 341-350.

Cristiano, P. M., Madanes, N., Campanello, P. I., Di Francescantonio, D., Rodríguez, S. A., Zhang, Y. J., Carrasco, L. O., & Goldstein, G. (2014). High NDVI and potential canopy photosynthesis of South American subtropical forests despite seasonal changes in leaf area index and air temperature. Forests, 5(2), 287-308.

Dos Santos, G. M., Meléndez-Pastor, I., Navarro-Pedreño, J., & Lucas, I. G. (2019). A Review of Landsat TM/ETM based Vegetation Indices as Applied to Wetland Ecosystems. Journal of Geographical Research/Maǧallaẗ Al-buḥūṯ Al-Ǧuġrāfiyyaẗ, 2(1).

Gamon, J. A., Field, C. B., Goulden, M. L., Griffin, K. L., Hartley, A. E., Joel, G., ... & Valentini, R. (1995). Relationships between NDVI, canopy structure, and photosynthesis in three Californian vegetation types. Ecological applications, 5(1), 28-41.

Giovos, R., Tassopoulos, D., Kalivas, D., Lougkos, N., & Priovolou, A. (2021). Remote sensing vegetation indices in viticulture: A critical review. Agriculture, 11(5), 457.

Gonçalves, R. M., Saleem, A., Queiroz, H. A. A., & Awange, J. L. (2019). A fuzzy model integrating shoreline changes, NDVI and settlement influences for coastal zone human impact classification. Applied Geography, 113, 102093.

Hanif, M. (2015). Bahan Pelatihan Penginderaan Jauh Tingkat Lanjut. Padang: Universitas Negeri Padang.

Hartoyo, A.P.P., Sunkar, A., Ramadani, R., Faluthi, S. & Hidayati, S. (2021). Normalized Difference Vegetation Index (NDVI) Analysis for Vegetation Cover in Leuser Ecosystem Area, Sumatra, Indonesia. Biodiversitas, 22(3), 1160-1171.

Huete, A.R. (1988). A Soil-Adjusted Vegetation Index (SAVI). Remote Sensing of Environment, 25(3), 295–309.

Jensen, J. R. (2004). Introductory Digital Image Processing - A Remote Sensing Perspective, 3rd edition. Englewood Cliffs, N.J.: Prentice Hall.

Li, S., Xu, L., Chen, J., Jiang, Y., Sun, S., Yu, S., ... & Li, X. (2023). Monitoring vegetation dynamics (2010–2020) in Shengnongjia Forestry District with cloud-removed MODIS NDVI series by a spatio-temporal reconstruction method. The Egyptian Journal of Remote Sensing and Space Science, 26(3), 527-543.

Liu, H.Q. & Huete, A. (1995). Feedback Based Modification of The NDVI To Minimize Canopy Background and Atmospheric Noise. IEEE Transactions on Geoscience and Remote Sensing, 33(2), 457–465.

Lizuka, K., Kato, T., Silsigia, S., Soufiningrum, A. Y., & Kozan, O. (2019). Estimating and examining the sensitivity of different vegetation indices to fractions of vegetation cover at different scaling Grids for Early Stage Acacia Plantation Forests Using a Fixed-Wing UAS. Remote Sensing, 11(15), 1816.

Lonita, B. I., Prasetyo, Y., & Haniah, H. (2015). Analisis Perubahan Luas Dan Kerapatan Hutan Menggunakan Algoritma NDVI (Normalized Difference Vegetation Index) Dan EVI (Enhanced Vegetation Index) Pada Citra Landsat 7 ETM+ Tahun 2006, 2009, Dan 2012 (Studi Kasus: Kabupaten Kendal, Provinsi Jawa Tengah). Jurnal Geodesi Undip, 4(3), 112-120.

Muhsoni, F. F., Sambah, A. B., Mahmudi, M., & Wiadnya, D. G. R. (2018). Comparison of different vegetation indices for assessing mangrove density using sentinel-2 imagery. GEOMATE Journal, 14(45), 42-51.

Pu, R., Gong, P., Tian, Y., Miao, X., Carruthers, R. I., & Anderson, G. L. (2008). Using classification and NDVI differencing methods for monitoring sparse vegetation coverage: a case study of saltcedar in Nevada, USA. International Journal of Remote Sensing, 29(14), 3987-4011.

Purevdorj, T. S., Tateishi, R., Ishiyama, T., & Honda, Y. (1998). Relationships between percent vegetation cover and vegetation indices. International Journal of Remote Sensing, 19(18), 3519-3535.

Simarmata, N., Wikantika, K., Tarigan, T. A., Aldyansyah, M., Tohir, R. K., Fauziah, A., & Purnama, Y. (2021). Analisis Transformasi Indeks NDVI, NDWI dan SAVI untuk Identifikasi Kerapatan Vegetasi Mangrove Menggunakan Citra Sentinel di Pesisir Timur Provinsi Lampung. Jurnal Geografi, 19(2), 69-79.

Sun, C., Li, J., Cao, L., Liu, Y., Jin, S., & Zhao, B. (2020). Evaluation of vegetation index-based curve fitting models for accurate classification of salt marsh vegetation using sentinel-2 time-series. Sensors, 20(19), 5551.

Thakur, S., Mondal, I., Ghosh, P. B., Das, P., & De, T. K. (2020). A review of the application of multispectral remote sensing in the study of mangrove ecosystems with special emphasis on image processing techniques. Spatial information research, 28, 39-51.

Umarhadi, D., & Syarif, A. (2017). Regression model accuracy comparison on mangrove canopy density mapping. International Conference on Science and

Technology, 2(7), 1-10.

Whittaker, R. H. (1978). The population structure of vegetation. Phytosociology-Benchmark papers in ecology, 6, 360-380.

Wulandari, N. (2020). Penggunaan Metode Ndvi (Normalized Difference Vegetation Index) Dan Savi (Soil Adjusted Vegetation Index) Untuk Mengetahui Ketersediaan Ruang Terbuka Hijau Terhadap Pemenuhan Kebutuhan Oksigen (Studi Kasus: Kota Yogyakarta) (Doctoral dissertation, Imstitut Teknologi Nasional Malang).

Xue, J., & Su, B. (2017). Significant remote sensing vegetation indices: A review of developments and applications. Journal of Sensors, 2017.

Zhang, J. H., Feng, Z. M., Jiang, L. G., & Yang, Y. Z. (2015). Analysis of the correlation between NDVI and climate factors in the Lancang River Basin. J. Nat. Resour, 30(9), 1425-1435.

Zhou, H., Wang, J. A., Yue, Y. J., & Li, R. (2009). Research on spatial pattern of human-induced vegetation degradation and restoration: a case study of Shaanxi Province. Acta Ecologica Sinica, 29(9), 4847-4856.

Downloads

Published

2024-05-08

How to Cite

Septianto Aldiansyah, Duwi Setiyo Wigati Ningsih, & Risna. (2024). SPATIAL TEMPORAL MAPPING OF VEGETATION COVER INDICES USING SENTINEL-2 MULTISPECTRAL INSTRUMENT IN UNAAHA CITY. ajalah lmiah lobe, 26(1), 1–10. etrieved from https://jurnal.big.go.id/GL/article/view/136