MODIS Satellite Imagery for Monitoring Carbon Sequestration Potential and Its Drivers in Jambi Province, Indonesia
DOI:
https://doi.org/10.24114/jg.v17i1.62343Keywords:
Carbon, MODIS, Net Primary Productivity (NPP)Abstract
Jambi Province is a province in Indonesia whose land use is dominated by forests and plantations. Threats to land conversion and forest fires in the region have reduced vegetation and will threaten carbon absorption in the future. This study aims to map and assess the potential for carbon absorption and triggering factors by evaluating the spatiotemporal Net Primary Productivity (NPP) pattern to estimate Jambi Province's carbon absorption. This study uses remote sensing data to obtain NPP values and several variables that will be assessed for their influence on NPP. MODIS satellite imagery is used to obtain NPP data, forest cover, Normalized Data Vegetation Index (NDVI) and Land Surface Temperature (LST). Shuttle Radar Topography Map (SRTM) imagery obtains topography and slope data. Population data in the form of the Human Development Index, total population and population in urban areas were obtained from the Central Statistics Agency of Jambi Province. The average NPP value 2003 in Jambi Province was 0.911 kgC/m/year, then the average NPP decreased to 0.754 kgC/m/year in 2023. Based on statistical analysis, there is a correlation between NPP and NDVI, slope, and topography.References
Arrafi, M., Widayani, P., & Arjasakusuma, S. (2024). Perhitungan Net Primary Productivity ( NPP ) Harian Menggunakan Model CASA Berbasis Citra Penginderaan Jauh di Kabupaten Muaro Jambi. Jurnal Geosains dan Remote Sensing (JGRS), 5(2), 91–100. https://doi.org/10.23960/jgrs.ft.unila.305
Central Statistics Agency of Jambi Province. 2003. Data Kependudukan Provinsi Jambi. https://jambi.bps.go.id
Das, M., Mandal, A., Das, A., Inácio, M., & Pereira, P. (2023). Mapping and assessment of carbon sequestration potential and its drivers in the Eastern Himalayan Region (India). Case Studies in Chemical and Environmental Engineering, 7(June). https://doi.org/10.1016/j.cscee.2023.100344
Fahey, T. J., & Knapp, A. K. (2007). Principles and Standards for Measuring Primary Production. Oxford University Press.
Ganie, M. A., & Nusrath, A. (2016). Determining the Vegetation Indices (NDVI) from Landsat 8 Satellite Data. International Journal of Advanced Research, 4(8), 1459–1463. https://doi.org/10.21474/ijar01/1348
Global Forest Resources Assessment 2020. Retrieved from https://www.fao.org/forest-resources-assessment/2020/en/
Global Forest Watch (2021). Primary Rainforest Destruction Increased 12% from 2019 to 2020. Retrieved from https://wri-indonesia.org/en/insights/primary-rainforest-destruction-increased-12-2019-2020
Gonsamo, A., & Chen, J. M. (2017). Vegetation primary productivity. In Comprehensive Remote Sensing (Vol. 1–9). Elsevier. https://doi.org/10.1016/B978-0-12-409548-9.10535-4
Houghton, R. A., & Goodale, C. L. (2004). Effects of land-use change on the carbon balance of terrestrial ecosystems. Geophysical Monograph Series, 153, 85–98. https://doi.org/10.1029/153GM08
Huang, X., He, L., He, Z., Nan, X., Lyu, P., & Ye, H. (2022). An improved Carnegie-Ames-Stanford Approach model for estimating ecological carbon sequestration in mountain vegetation. Frontiers in Ecology and Evolution, 10(December). https://doi.org/10.3389/fevo.2022.1048607
Indiarto, D., & Sulistyawati, E. (2013). Monitoring Net Primary Productivity dynamics in Java Island using MODIS satellite imagery. 34th Asian Conference on Remote Sensing 2013, ACRS 2013, 2, 1730–1737.
Jiang, C., Wu, Z. F., Cheng, J., Yu, Q., & Rao, X. Q. (2015). Impacts of urbanization on net primary productivity in the pearl river delta, China. International Journal of Plant Production, 9(4), 581–598. https://doi.org/10.22069/IJPP.2015.2464
June, T., Ibrom, A., & Gravenhorsr, G. (2006). Integration of NPP semi mechanistic - Modelling, remote sensing and CIS in estimating CO 2 absorption of forest vegetation in Lore Lindu National Park. Biotropia, 13(1), 22–36. https://doi.org/10.11598/btb.2006.13.1.217
Kerinci Sebelat National Park Main Office. (2023). Data Perambahan Hutan di Kerinci Tahun 2008 - 2023.
Kurniadi, H., Aprilia, E., Utomo, J. B., Kurniawan, A., & Safril, A. (2018). Perbandingan Metode IDW Dan Spline dalam Interpolasi Data Curah Hujan ( Studi Kasus Curah Hujan Bulanan Di Jawa Timur Periode 2012-2016 ). Prosiding Seminar Nasiional GEOTIK 2018, 215.
Ma, X., Huo, T., Zhao, C., Yan, W., & Zhang, X. (2020). Projection of Net Primary Productivity under Global. Atmosphere, C, 1–23. https://doi.org/10.3390/atmos11010071
Pachavo, G., & Murwira, A. (2014). Remote sensing net primary productivity (NPP) estimation with the aid of GIS modelled shortwave radiation (SWR) in a Southern African Savanna. International Journal of Applied Earth Observation and Geoinformation, 30(1), 217–226. https://doi.org/10.1016/j.jag.2014.02.007
Parmadi, Prihanto, P. H., & Ratnawati, R. (2020). Pertumbuhan ekonomi kota dan pengaruhnya terhadap kesempatan kerja di Kota Jambi. Jurnal Paradigma Ekonomika, 15(1), 2085–1960.
Pei, Y., Huang, J., Wang, L., Chi, H., & Zhao, Y. (2018). An improved phenology-based CASA model for estimating net primary production of forest in central China based on Landsat images. International Journal of Remote Sensing, 39(21), 7664–7692. https://doi.org/10.1080/01431161.2018.1478464
Peng, D. L., Huang, J. F., Huete, A. R., Yang, T. M., Gao, P., Chen, Y. C., Chen, H., Li, J., & Liu, Z. Y. (2010). Spatial and seasonal characterization of net primary productivity and climate variables in southeastern China using MODIS data. Journal of Zhejiang University: Science B, 11(4), 275–285. https://doi.org/10.1631/jzus.B0910501
Potter, S., Randerson, T., Field, B., Matson, A., & Mooney, H. A. (1993). Terrestial Ecosystem Production : A Process Model Based on Global Satellite and Surface Data. 7(4), 811–841. https://doi.org/10.1029/93GB02725
Pramudiyasari, T., Tambunan, M. P., Tambunan, R. P., & Manessa, M. D. M. (2021). Analisis LST, NDVI Menggunakan Satelit Landsat 8 Serta Trend Suhu Udara Di Kabupaten Majalengka. Jurnal Geosaintek, 7(3), 2017–2022. https://doi.org/10.12962/j25023659.v7i3.9043
Putra, A. H., Oktari, F., & Putriana, A. M. (2019). Deforestasi dan pengaruhnya terhadap tingkat bahaya kebakaran hutan di Kabupaten Agam Provinsi Sumatera Barat. Jurnal Dialog Penanggulangan Bencana, 10(2), 191–200.
Sari, P. C., Subiyanto, S., & Awaluddin, M. (2014). Analisis Deforestasi Hutan Di Provinsi Jambi Menggunakan Metode Penginderaan Jauh (Studi Kasus Kabupaten Muaro Jambi). Jurnal Geodesi Undip Jurnal Geodesi Undip, 3(April), 28–43. https://doi.org/10.14710/jgundip.2014.5203
Yan, Y., Liu, X., Wang, F., Li, X., Ou, J., Wen, Y., & Liang, X. (2018). Assessing the impacts of urban sprawl on net primary productivity using fusion of Landsat and MODIS data. Science of the Total Environment, 613–614, 1417–1429. https://doi.org/10.1016/j.scitotenv.2017.09.139
Zhang, M., Lin, H., Wang, G., Sun, H., & Cai, Y. (2019). Estimation of vegetation productivity using a Landsat 8 time series in a heavily urbanized area, central China. Remote Sensing, 11(2). https://doi.org/10.3390/rs11020133
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Prima Widayani, Muhammad Arrafi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
