ESTIMATING MANGROVE FOREST DENSITY USING GAP FRACTION METHOD AND VEGETATION TRANSFORMATION INDICES APPROACH

DOI: https://doi.org/10.14710/geoplanning.5.1.35-42
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Published: 25-04-2018
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Mangrove forest represented a coastal ecosystem in Indonesia. Theoretical validation and in-field measurement by calculating the number of trees and the density data that was validated through remote sensing would not be appropriate because the remote sensing recorded canopy density and not tree stands. New method canopy photography or gap fraction method was the technique to predict sun radiation using the photograph taken upward through extremely wide lens and classification object image. The objectives of the study were (1) to examine the acuracy of the estimation of the mangrove forest density using vegetation index transformation, and (2) to map the mangrove forest condition. The location of the study was Alas Purwo Resort Grajagan National Park area. The material of the study was Landsat-8 OLI image recorded on January 19th, 2016 using SAVI vegetation index transformation method. Gap fraction filed measurement method was a new method in Indonesia. The results of the study showed that the regression of the SAVI index between index transformation value and in-field condition (R2) was 0.566, the forest density estimation resulting from the SAVI index transformation had the RMSE of 2.334178 and the density of the mangrove forest in Grajagan Bay of the Alas Purwo National Park included low density of 0-12.5% (30.42 ha), medium density of 12.6-25% (116.55 ha), and high density of 25.1-37.6% (463.68 ha).

Keywords

Mapping; Estimate; Remote Sensing; Mangrove Forest; Gap Fraction; Landsat-8 OLI;

  1. Nurul Khakhim 
    Cartography and Remote Sensing Departement of Geographic Information Science Faculty of Geography Universitas Gadjah Mada, Indonesia
    ketua Laboratorium Kartografi
  2. Akbar Cahyadhi Pratama Putra 
    Remote Sensing Department, Earthline, Jakarta, Indonesia
  3. Tantri Utami Widhaningtyas 
    Cartography and Remote Sensing Faculty of Geography Universitas Gadjah Mada, Indonesia
  1. Bolstad, P. V, & Gower, S. T. (1990). Estimation of leaf area index in fourteen southern Wisconsin forest stands using a portable radiometer. Tree Physiology, 7(1-2-3–4), 115–124. article. https://doi.org/10.1093/treephys/7.1-2-3-4.115 [Crossref]

  2. Danoedoro, P. (2012). Pengantar penginderaan jauh digital. Penerbit Andi, Yogyakarta.

  3. Fawzi, N. I. (2015). Penginderaan Jauh Untuk Ekologi dan Konservasi. Yogyakarta: University Gadjah Mada.

  4. Ilham, M. (2012). Pendekatan Multiregresi Indeks Vegetasi Untuk Pendugaan Stok Karbon. Institute Technology Bandung.

  5. Inoue, A., Yamamoto, K., Mizoue, N., & Kawahara, Y. (2002). Estimation of Relative Iilluminance using Digital Hemispherical Photography. Journal of Forest Planning, 8(2), 67–70.

  6. Irons, J. R. (2015). Operational Land Imager (OLI). Retrieved from https://landsat.gsfc.nasa.gov/operational-land-imager-oli/

  7. Jensen, J. R., & Lulla, K. (1987). Introductory digital image processing: a remote sensing perspective. article.

  8. Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., & Baret, F. (2004). Review of methods for in situ leaf area index determination. Agricultural and Forest Meteorology, 121(1–2), 19–35. [Crossref]

  9. Jonckheere, I., Nackaerts, K., Muys, B., & Coppin, P. (2005). Assessment of automatic gap fraction estimation of forests from digital hemispherical photography. Agricultural and Forest Meteorology, 132(1–2), 96–114. [Crossref]

  10. Kamal, M., Hartono, H., Wicaksono, P., Adi, N. S., & Arjasakusuma, S. (2016). Assessment of Mangrove Forest Degradation through Canopy Fractional Cover in Karimunjawa Island, Central Java, Indonesia. Geoplanning: Journal of Geomatics and Planning, 3(2), 107. [Crossref]

  11. Keputusan Menteri Kehutanan. 1992. No. 283/KPTS-II/1992 tanggal 26 februari 1992 Penentuan Taman Nasional Alas Purwo Sebagai Kawasan Suaka Alam dan Konservasi, Kabupaten Banyuwangi, Jawa Timur. Jakarta : Departemen Kehutanan

  12. Kuenzer, C., Bluemel, A., Gebhardt, S., Quoc, T. V., & Dech, S. (2011). Remote Sensing of Mangrove Ecosystems: A Review. Remote Sensing, 3(5), 878–928. [Crossref]

  13. Lee, T.-M., & Yeh, H.-C. (2009). Applying remote sensing techniques to monitor shifting wetland vegetation: A case study of Danshui River estuary mangrove communities, Taiwan. Ecological Engineering, 35(4), 487–496. [Crossref]

  14. Makridakis, S., Andersen, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R., … Winkler, R. (1982). The accuracy of extrapolation (time series) methods: Results of a forecasting competition. Journal of Forecasting, 1(2), 111–153. [Crossref]

  15. Murti, S. H., & others. (2013). Pemanfaatan Citra ALOS AVNIR-2 untuk Klasifikasi Kerapatan Kanopi Hutan Mangrove berdasarkan Transformasi Indeks Vegetasi Di Delta Wulan Demak, Jawa Tengah (phdthesis). Universitas Gadjah Mada.

  16. Putra, A. C. P., & Khakhim, N. (2016). Pemetaan kerapatan kanopi hutan mangrove menggunakan citra landsat-8 oli di wilayah pengelolaan (resort grajagan), taman nasional alas purwo, kabupaten banyuwangi, jawa timur (phdthesis). Universitas Gadjah Mada.

  17. Rich, P. M. (1990). Characterizing plant canopies with hemispherical photographs. Remote Sensing Reviews, 5(1), 13–29. [Crossref]

  18. Smith, N. J. (1991). Predicting radiation attenuation in stands of Douglas-fir. Forest Science, 37(5), 1213–1223.

  19. Sudarmadji, I. (2011). Identifikasi lahan dan potensi hutan mangrove di bagian timur Propinsi Jawa Timur. Bonoworo Wetlands, 1(1), 7–13.

  20. Walsh, G. E. (1974). Mangroves: a review. In Ecology of halophytes (pp. 51–174). incollection, Elsevier.

  21. Watson, D. J. (1947). Comparative Physiological Studies on the Growth of Field Crops: I. Variation in Net Assimilation Rate and Leaf Area between Species and Varieties, and within and between Years. Annals of Botany, 11(1), 41–76. [Crossref]

  22. Weiss, M. (2002). EYE-CAN User Guide (techreport)