Spectral Angle Mapper Algorithm for Mangrove Biodiversity Mapping in Semarang Indonesia


Tjaturahono Budi Sanjoto, - (2022) Spectral Angle Mapper Algorithm for Mangrove Biodiversity Mapping in Semarang Indonesia. Visions for Sustainability (18). pp. 1-18. ISSN 2384-8677

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Abstract

Monitoring biodiversity is a key component of sustainability re�search related to safeguarding ecosystems. Although there still exist limits to its application, remote sensing has been used to map mangrove biodiversity and its distribution using spectral reflectance. This study considers the man�grove ecosystem in the Semarang coastal area using the Spectral Angle Map�per (SAM) method for biodiversity identification at species level. The remote sensing data is SPOT 7 imagery, acquired on 24 December 2019. In situ spec�tral reflection measurements were performed using a USB4000 spectrometer. The result from in situ measurement is referred to as the spectral library used for mangrove classification. Eight mangrove species were identified by the SAM method in this study, with a preponderance of the species Avicennia marina in the northern part of the study area, an open area that directly faces the sea, corresponding to the original habitat of Avicennia marina. The study shows that while the SAM method can be considered accurate for species with larger concentrations, the classification results demonstrate an overall mod�erate-low accuracy of 52% because some species classes have small patches that are intermingled with areas of different land-use. Further developments in remote sensing analysis techniques and more research will be necessary to endeavor to overcome these limits.

Item Type: Article
Uncontrolled Keywords: Mangrove biodiversity mapping; Remote sensing; Spectral angle mapper.
Subjects: G Geography. Anthropology. Recreation > GF Human ecology. Anthropogeography > Dams, Irrigation, Agriculture
Fakultas: Fakultas Ilmu Sosial > Pendidikan Geografi, S1
Depositing User: Setyarini UPT Perpus
Date Deposited: 29 Nov 2022 04:20
Last Modified: 05 Jan 2023 20:29
URI: http://lib.unnes.ac.id/id/eprint/53625

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