Mapping of Rhizophora stylosa in the Karimunjawa Mangrove Forest, Indonesia Using Spectral Reflectance Based on WorldView-2 Imagery

Information regarding the species types and distribution of mangroves is essential for prioritizing biodiversity conservation and effective forest management. Remotely sensed data has been demonstrated to be a valuable tool in differentiating between mangrove and non-mangrove features. Nevertheless, the application of this data for the identification and mapping of specific mangrove species poses challenges, particularly when relying on field-based spectral reflectance measurements. This study seeks to achieve three primary objectives: (i) to collect spectral reflectance data for Rhizophora stylosa (Griff.) from field measurements, (ii) to develop a spectral library specifically for Rhizophora stylosa, and (iii) to map the distribution of this target species using WorldView-2 (WV-2) imagery. The spectral library for the targeted species was compiled utilizing a JAZ EL-350 portable field spectrometer, which operates across a wavelength range of 350 nm to 1024 nm. To ensure compatibility between the spectral data collected in the field and the WV-2 imagery, a spectral resampling technique was employed to standardize the number of spectral bands. Subsequently, the spectral angle mapper (SAM) algorithm was applied to the WV-2 imagery, using the resampled spectral data for Rhizophora stylosa to facilitate the spatial mapping of this species. The results indicate that Rhizophora stylosa can be effectively identified and mapped at an overall accuracy of 80% using both the spectral reflectance data obtained from field measurements and the WV-2 imagery. This study provides significant evidence supporting the feasibility of utilizing remote sensing data for the species-level mapping of mangroves based on the spectral reflectance characteristics of the targeted objects. By enhancing our understanding of mangrove species distribution, this research contributes to more informed conservation and management strategies for these vital ecosystems.

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Publication Details

Journal
International Journal of Geoinformatics
Published
2025-03-19
DOI
https://doi.org/10.52939/ijg.v21i3.3993
Citations
1
Primary Topic
Forest Ecology and Conservation
Type
article
Field-Weighted Citation Impact
6.43

Funders

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article

Mapping of Rhizophora stylosa in the Karimunjawa Mangrove Forest, Indonesia Using Spectral Reflectance Based on WorldView-2 Imagery

1 citations
International Journal of Geoinformatics
Forest Ecology and Conservation
6.43
article

Mapping of Rhizophora stylosa in the Karimunjawa Mangrove Forest, Indonesia Using Spectral Reflectance Based on WorldView-2 Imagery

article en
1 citations

Abstract

Information regarding the species types and distribution of mangroves is essential for prioritizing biodiversity conservation and effective forest management. Remotely sensed data has been demonstrated to be a valuable tool in differentiating between mangrove and non-mangrove features. Nevertheless, the application of this data for the identification and mapping of specific mangrove species poses challenges, particularly when relying on field-based spectral reflectance measurements. This study seeks to achieve three primary objectives: (i) to collect spectral reflectance data for Rhizophora stylosa (Griff.) from field measurements, (ii) to develop a spectral library specifically for Rhizophora stylosa, and (iii) to map the distribution of this target species using WorldView-2 (WV-2) imagery. The spectral library for the targeted species was compiled utilizing a JAZ EL-350 portable field spectrometer, which operates across a wavelength range of 350 nm to 1024 nm. To ensure compatibility between the spectral data collected in the field and the WV-2 imagery, a spectral resampling technique was employed to standardize the number of spectral bands. Subsequently, the spectral angle mapper (SAM) algorithm was applied to the WV-2 imagery, using the resampled spectral data for Rhizophora stylosa to facilitate the spatial mapping of this species. The results indicate that Rhizophora stylosa can be effectively identified and mapped at an overall accuracy of 80% using both the spectral reflectance data obtained from field measurements and the WV-2 imagery. This study provides significant evidence supporting the feasibility of utilizing remote sensing data for the species-level mapping of mangroves based on the spectral reflectance characteristics of the targeted objects. By enhancing our understanding of mangrove species distribution, this research contributes to more informed conservation and management strategies for these vital ecosystems.

International Journal of Geoinformatics
Universitas Gadjah Mada (ID)
Universitas Gadjah Mada
Life in Land
Openalex Percentile: Top 7%
Forest Ecology and Conservation
6.43
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Mapping of Rhizophora stylosa in the Karimunjawa Mangrove Forest, Indonesia Using Spectral Reflectance Based on WorldView-2 Imagery · International Journal of Geoinformatics (2025) | TGRS Research Map | TGRS