COMPARISON OF SEVERAL RED EDGE BAND SENTINEL SATELLITE IMAGERY FOR MANGROVE MAPPING IN LEMBAR BAY LOMBOK INDONESIA
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Arhatin, R.E. (2007). Pengkajian Algoritma Indeks Vegetasi Dan Metode Klasifikasi Mangrove Dari Data Satelit Landsat-5 Dan Landsat-7 ETM+ (Studi Kasus di Kabupaten Berau, Kaltim). [Thesis]. Program Pascasarjana IPB. Bogor.
Bengen, D.G. (2002). Ekosistem dan sumberdaya alam pesisir dan laut serta prinsip pengelolaannya. Bogor: Pusat Kajian Sumberdaya Pesisir dan Lautan, IPB.
Danoedoro, P. (2012). Pengantar penginderaan jauh digital. Yogyakarta: Gajah Mada University Press.
Departemen Kehutanan. (2005). Pedoman Inventarisasi Dan Identifikasi Lahan Kritis Mangrove. Jakarta: Direktorat Jenderal Rehabilitasi Lahan Dan Perhutanan Sosial.
Dewanti, R. (1999). Kondisi hutan mangrove di Kalimantan Timur, Sumatera, Jawa, Bali, dan Maluku. Jakarta: Majalah LAPAN Edisi Penginderaan Jauh.
Dewi, N.N.D.K., Dirgayusa, I.G.N.P., & Suteja, Y. (2017). Kandungan Nitrat dan Fosfat Sedimen serta Keterkaitannya dengan Kerapatan Mangrove di Kawasan Mertasari di Aliran Sungai TPA Suwung Denpasar, Bali. Journal of Marine and Aquatic Sciences, 3(2), pp.180-190.
Europan Space Agency [ESA]. (2015). Sentinel-2 User Handbook. Paris (FR): ESA Standart Document.
Gitelson, A. & Merzlyak, M.N. (1994). Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation. J. Plant Physiol., vol. 143, no. 3, pp. 286–292.
Green, E.P., Mumbay, P.J., Edwards, A.J., & Clark, C.D. (2000). Remote Sensing Hand Book for Tropical Coastal Management.Unesco Publishing.
Heumann, & Benjamin W. (2011). An Object-Based Classification of Mangroves Using a Hybrid Decision Tree—Support Vector Machine Approach, ISSN 2072-429.
Hirata, Y., Tabuchi, R., Patanaponpaiboon, P., Poungparn, S., Yoneda, R., & Fujioka, Y. (2014). Estimation Of Aboveground Biomass In Mangrove Forests Using High-Resolution Satellite Data. Journal of forest research, 19(1), pp.34-41.
Jensen, R.R., Hardin, P.J. & Hardin, A.J. (2012). Estimating Urban Leaf Area Index (LAI) Of Individual Trees With Hyperspectral Data. Photogrammetric Engineering & Remote Sensing, 78(5), pp.495-504.
Kementrian Lingkungan Hidup (KEMENLH). (2004). Kriteria Baku dan Pedoman Kerusakan Hutan mangrove. Jakarta: Keputusan Menteri Negara Lingkungan Hidup Nomor: 201 Tahun 2004.
Lefsky, M.A., Harding, D.J., Keller, M., Cohen, W.B., Carabajal, C.C., Del Bom Espirito‐Santo, F., Hunter, M.O., & de Oliveira, R. (2005). Estimates Of Forest Canopy Height And Aboveground Biomass Using Icesat. Geophysical research letters, 32(22).
Lillesand, T.M., & Kiefer, R.W. (1990). Remote Sensing and image Interpretation. Yogyakarta: Gajah Mada University Press.
Makridakis, S. (1982). The accuracy of extrapolative (Time Series Methods): Results of a forecasting. Vol.1, No.2,pp,111-153 (lead article)
Ni‐Meister, W., Lee, S., Strahler, A.H., Woodcock, C.E., Schaaf, C., Yao, T., Ranson, K.J., Sun, G. & Blair, J.B. (2010). Assessing General Relationships Between Aboveground Biomass And Vegetation Structure Parameters For Improved Carbon Estimate From Lidar Remote Sensing. Journal of Geophysical Research: Biogeosciences, 115(G2).
Prahasta, E. (2008). Remote Sensing. Bandung: Informatika bandung. [Indonesian]
Proisy, C., Couteron, P. & Fromard, F. (2007). Predicting And Mapping Mangrove Biomass From Canopy Grain Analysis Using Fourier-Based Textural Ordination Of IKONOS Images. Remote Sensing of Environment, 109(3), pp.379-392.
Shofiyati, R., Las, I. & Agus, F. (2010). Indonesian soil database and predicted stock of soil carbon. In Proceedings of international workshop on evaluation and sustainable management of soil carbon sequestration in Asian countries Bogor, Indonesia Sept (pp. 28-29).
Sofian, A., Harahab, N. & Marsoedi. (2012). Kondisi dan manfaat langsung ekosistem mangrove Desa Penunggul Kecamatan Nguling Kabupaten Pasuruan. ElHayah 2 (2): 56-63.
Sugiyono. (2010). Metode Penelitian Kuantitaif dan RND. Bandung : Alfabeta.
Sudiana, D. & Elfa, D. (2008). Analisis Indeks Vegetasi menggunakan Data Satelit NOAA/AVHRR dan TERRA/AQUA-MODIS. Departemen Teknik Elektro, Fakultas Teknik, Universitas Indonesia.
Sugianthi, N.L.M.A., Arthana, I.W. & Adnyana, I.W.S. (2012). Monitoring Mangrove Area In Benoa Bay Using Landsat Tm And Etm+ Data. Ecotrophic: Journal of Environmental Science, 2(1).
Thapa, R. B., Watanabe, M., Motohka, T., & Shimada, M. (2015). Potential Of High-Resolution ALOS–PALSAR Mosaic Texture For Aboveground Forest Carbon Tracking In Tropical Region. Remote Sensing of Environment, 160, 122-133.
Wicaksono, P., Danoedoro, P., Hartono & Nehren, U. (2016). Mangrove Biomass Carbon Stock Mapping Of The Karimunjawa Islands Using Multispectral Remote Sensing. International Journal of Remote Sensing, 37(1), pp.26-52.
Winarso, G. & Purwanto, A. D. (2014). Evaluation Of Mangrove Damage Level Based On Landsat 8 Image’. International Journal of Remote Sensing and Earth Sciences Vol. 11 No. 2 December 2014 :105 – 116.
Wu, C., Niu, Z., Tang, Q. & Huang, W. (2008). Estimating chlorophyll content from hyperspectral vegetation indices: Modeling and validation. Agricultural Forest Meteorol. vol. 148, no. 8-9, pp. 1230–1241.
Xie, Q., Jadu, D., Wenjiang, H., Dailiang, P., Qiming, Q., Hugh, M., Raffaele, C., Stefano, P., Giovanni, L., Simone, P., Yingying. & Huichun, Y. (2018). Vegetation Indices Combining the Red and Red-Edge Spectral Information for Leaf Area Index Retrieval. IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing.
Zhu, Y., Liu, K., Liu, L., Myint, S.W., Wang, S., Liu, H. & He, Z. (2017). Exploring the Potential of WorldView-2 Red-Edge Band-Based Vegetation Indices for Estimation of Mangrove Leaf Area Index with Machine Learning Algorithms. Remote Sensing, 9(10), p.1060.
DOI: https://doi.org/10.31764/geography.v9i1.4276
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