Hubungan Stok Karbon Mangrove Lapangan dengan Indeks Vegetasi dan Principal Component Analysis
Bilah Samping Artikel
Isi Artikel Utama
Abstrak
Penelitian tentang studi stok karbon mangrove menggunakan data penginderaan jauh sudah banyak dilakukan, dengan berbagai topik, metode dan citra yang digunakan. Pada penelitian ini bertujuan untuk mengetahui hubungan antara stok karbon mangrove di lapangan dengan indeks vegetasi dan Principal Component Analysis (PCA). Metode dalam penelitian ini menggunakan analisis statistik antara lain uji normalitas dan uji korelasi. Berdasarkan hasil penelitian data PCA menghasilkan nilai negatif dan indeks vegetasi bernilai positif, sehingga data PCA tidak mampu melewati batas signifikansi uji korelasi. Hal tersebut menunjukkan bahwa pemetaan stok karbon efektif dilakukan dengan menggunakan data indeks vegetasi. Hal ini perlu dikaji ulang terkait PCA khususnya penggunaan citra Planetscope.
Rincian Artikel
Artikel ini berlisensiCreative Commons Attribution-ShareAlike 4.0 International License.
Referensi
Alongi, D. M., Murdiyarso, D., Fourqurean, J. W., Kauffman, J. B., Hutahaean, A., Crooks, S., Lovelock, C. E., Howard, J., Herr, D., Fortes, M. 2015. Indonesia’s blue carbon: a globally significant and vulnerable sink for seagrass and mangrove carbon. Wetl. Ecol. Manag., 24, 3–13
Bengen, D. G. 2002. Sinopsis Ekosistem dan Sumberdaya Alam Pesisir dan Laut serta Prinsip Pengelolaannya (Synopsis of Coastal and Marine Natural Ecosystems and Resources and their Management Principles). Pusat Kajian Sumberdaya Pesisir dan Lautan, Bogor.
Ghazali, I. 2011. Aplikasi Analisis Multivariate dengan Program IBM SPSS 19. Semarang: Badan Penerbit Universitas Diponegoro.
Haq, S. M., Rashid, I., Calixto, E. S., Ali, A., Kumar, M., Srivastava, G., Bussmann, R. W., Khuroo, A. 2022. A. Unravelling patterns of forest carbon stock along a wide elevational gradient in the Himalaya: implications for climate change mitigation. Forest ecology and management, 2022.
Hidayatullah, M. F., Kamal, M., Wicaksono, P. 2023. Species-Based Aboveground Mangrove Carbon Stock Estimation Using Worldview-2 Image Data. Remote Sensing Applications: Society and Environment, 30. https://doi.org/10.1016/j.rsase.2023.100959.
Jesudhas, C. J., C. Titus, J., Roy, T. 2023. Remote Sensing-based Drought Hazard Monitoring and Assessment in a Coastal Plain: A Principal Component Approach. Environmental Research, 243.
Komiyama, A., Poungparn, S., dan Ong, J. E. 2008. Allometry, Biomass and Productivity of Mangrove Forest: A Review. Aquatic Botany, 2008(89), 128-137. https://doi.org/10.1016/j.aquabot.2007.12.006
Lestariningsih, W. A., Soenardjo, N., Pribadi, R. 2018. Estimasi Cadangan Karbon Pada Kawasan Mangrove Di Desa Timbulsloko, Demak, Jawa Tengah. Buletin Oseanografi Marina, 2018(7), 121-130.
Maxwell, T. L., Hengl, T., Parente, L. L., Minarik, R., Worthington, T. A., Bunting, P., Smart, L. S., Spalding, M. D., Landis, E. 2023. Global Mangrove Soil Organic Carbon Stocks Dataset at 30 m Resolution for the Year 2020 Based on Spatiotemporal Predictive Machine Learning. Data in Brief, 50.
Mokarram, M., Zarei, A. R. 2023. Soil Erosion Prediction Using Markov and CA-Markov Chains Methods and Remote Sensing Drought Indicators. Ecological Informatics, 78.
Munyati, C., 2022. Detecting the distribution of grass aboveground biomass on a rangeland using Sentinel-2 MSI vegetation indices. Adv. Space Res., 69, 1130–1145.
Murdiyarso, D., Arifanti, V. B., Sidik, F., Sillanp, M., Sasmito, S.D. 2021. Optimizing carbon stocks and sedimentation in Indonesian mangroves under different management regimes, in: K.W. Krauss, Z. Zhu, C.L. Stagg (Eds.). Wetland Carbon and Environmental Management, American Geophysical Union Publications, 159–172.
Murdiyarso, D., Purbopuspito, J., Kauffman, J. B., Warren, M. W., Sasmito, S. D., Donato, D. C., Manuri, S., Krisnawati, H., Taberima, S., Kurnianto, S. 2015. The potential of Indonesian mangrove forests for global climate change mitigation. Nat. Clim. Change, 5, 1089–1092.
Noor, Y. R., Khazali, M., Suryadiputra, I. N. N. 2006. Panduan Pengenalan Mangrove di Indonesia. Jakarta: Wetlands International, Indonesia Programme.
Pendleton, L., Donato, D.C., Murray, B.C., Crooks, S., Jenkins, W.A., Sifleet, S., Craft, C., Fourqurean, J.W., Kauffman, J.B., Marb, N. 2012. Estimating global “blue carbon’ emissions from conversion and degradation of vegetated coastal ecosystems. PLoS One, 7.
Planet Labs. (2018). Planet Imagery Product Specification. Planet Labs Inc 2018.
Poedjirahajoe, E., Marsono, D., Wardhani, F. K. 2017. Penggunaan Principal Component Analysis dalam Distribusi Spasial Vegetasi Mangrove di Pantai Utara Pemalang. Jurnal Ilmu Kehutanan, 11(2017): 29-42.
Poley, G., Lucy, Mcdermid, Gregory, J., 2020. A systematic review of the factors influencing the estimation of vegetation aboveground biomass using unmanned aerial systems. Remote Sens. 12, 1052.
Purnamasari, E., Kamal, M., Wicaksono, P. 2020. Comparison of Vegetation Indices for Estimating Above-Ground Mangrove Carbon Stocks Using PlanetScope Image. Regional Studies in Marine Science, 44. https://doi.org/10.1016/j.rsma.2021.101730
Rahma, I. Y., Amalia, A. R., Maulana, I. S., Hilal, M. S., Aulya, Z. S., Nandi., Ridwana, R. 2020. Analisis Komparasi Metode Pemetaan Ekosistem Mangrove Menggunakan Penginderaan Jauh dan Sistem Informasi Geografis. Jurnal Geografi, 17(2): 49-55.
Riduwan, A. 2007. Rumus dan Data dalam Aplikasi Statistika. Bandung: Alfabeta.
Salampessy, M. L., Febryano, I. G., Martin, E., Siahaya, M. E., Papilaya, R. 2015. Cultural capital of the communities in the mangrove conservation in the coastal areas of Ambon Dalam Bay, Moluccas, Indonesia. Environ. Sci., 23, 222–229.
Sofian, A., Kusmana, C., Fauzi, A., Rusdiana, O. 2019. Ecosystem services-based mangrove management strategies in Indonesia: a review. AACL Bioflux, 12 (1),151–166.
Standar Nasional Indonesia (SNI). 2011. Pengukuran dan Perhitungan Cadangan Karbon – Pengukuran Lapangan untuk Penaksiran Cadangan Karbon 111 Hutan (Ground Based Forest Carbon Accounting). Jakarta: Badan Standardisasi Nasional.
Sudjana. 2002. Metode Statistika. Bandung: Tarsito.
Sun, D., Robbins, K., Morales, N., Shu, Q., Cen, H., 2022. Advances in optical phenotyping of cereal crops. Trends Plant Sci., 27 (2), 191–208.
Taddeo, S., Dronova, I., Depsky, N., 2019. Spectral vegetation indices of wetland greenness: responses to vegetation structure, composition, and spatial distribution. Remote Sens. Environ., 234, 111467.
Yuwono, R. A. 2017. Pemanfaatan Citra Satelit Landsat 8 OLI untuk Pemetaan Kerapatan Kanopi Hutan Mangrove di Segara Anakan, Kabupaten Cilacap, Jawa Tengah. Skripsi. Universitas Gadjah Mada, Yogyakarta.
Zhao, C., Zhang, Y., Du, J., Guo, X., Wen, W., Gu, S., Wang, J., Fan, J., 2019. Crop phenomics: current status and perspectives. Front. Plant Sci., 10, 714.