ACADSTAFF UGM

CREATION
Title : Spectral Reflectance-Based Mangrove Species Mapping from WorldView-2 Imagery of Karimunjawa and Kemujan Island, Central Java Province, Indonesia
Author :

ARIE DWIKA R (1) Prof. Muhammad Kamal, S.Si., M.GIS., Ph.D. (2) Prof. Dr. Pramaditya Wicaksono, S.Si., M.Sc. (3)
Date : 1 2022
Keyword : Mangrove species,spectrometer,spectral reflectance,WorldView-2,dendrogram Mangrove species,spectrometer,spectral reflectance,WorldView-2,dendrogram
Abstract : Mangrove mapping at the species level enables the creation of a detailed inventory of mangrove forest biodiversity and supports coastal ecosystem management. The Karimunjawa National Park in Central Java Province is one of Indonesia’s mangrove habitats with high biodiversity, namely, 44 species representing 25 true mangroves and 19 mangrove associates. This study aims to (1) classify and group mangrove species by their spectral reflectance characteristics, (2) map mangrove species by applying their spectral reflectance to WorldView-2 satellite imagery with the spectral angle mapper (SAM), spectral information divergence (SID), and spectral feature fitting (SFF) algorithms, and (3) assess the accuracy of the produced mangrove species mapping of the Karimunjawa and Kemujan Islands. The collected field data included (1) mangrove species identification, (2) coordinate locations of targeted mangrove species, and (3) the spectral reflectance of mangrove species measured with a field spectrometer. Dendrogram analysis was conducted with the Ward linkage method to classify mangrove species based on the distance between the closest clusters of spectral reflectance patterns. The dendrogram showed that the 24 mangrove species found in the field could be grouped into four levels. They consisted of two, four, and five species groups for Levels 1 to 3, respectively, and individual species for Level 4. The mapping results indicated that the SID algorithm had the highest overall accuracy (OA) at 49.72%, 22.60%, and 15.20% for Levels 1 to 3, respectively, while SFF produced the most accurate results for individual species mapping (Level 4) with an OA of 5.08%. The results suggest that the greater the number of classes to be mapped, the lower the mapping accuracy. The results can be used to model the spatial distribution of mangrove species or the composition of mangrove forests and update databases related to coastal management.
Group of Knowledge :
Original Language : English
Level : Internasional
Status :
Published
Document
No Title Document Type Action
1 Rahmandhana 2022 Spectral Reflectance-Based Mangrove Species Mapping from WorldView-2.pdf
Document Type : [PAK] Full Dokumen
[PAK] Full Dokumen View
2 MDPIRS_vol 14(1)_january 2022_editorial board_-min.pdf
Document Type : [PAK] Halaman Editorial
[PAK] Halaman Editorial View
3 MDPIRS_vol 14(1)_january 2022_cover.pdf
Document Type : [PAK] Halaman Cover
[PAK] Halaman Cover View
4 MDPIRS_vol 14(1)_january 2022_daftar isi.pdf
Document Type : [PAK] Daftar Isi
[PAK] Daftar Isi View
5 Bukti korespondensi_2022_Rahmandhana_MDPI-RS-min-linked.pdf
Document Type : [PAK] Bukti Korespondensi Penulis
[PAK] Bukti Korespondensi Penulis View
6 Spectral Reflectance-Based Mangrove Species Mapping Cek Similarity.pdf
Document Type : [PAK] Cek Similarity
[PAK] Cek Similarity View
7 Surat Keterangan Publikasi untuk PAK (2022)_Jurnal_Rahmandhana 2022 Spectral Reflectance-Based Mangrove Species Mapping.pdf
Document Type : Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian)
Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian) View