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.
Highlights
Introduction published maps and institutional affilIndonesia is a global ecological hotspot, judging from the extent and rich biodiversity of its mangrove ecosystem
This study explores the use of three classification algorithms, spectral angle mapper (SAM), spectral information divergence (SID), and spectral feature fitting (SFF), to map the mangrove distribution on Karimunjawa and Kemujan Island
The center wavelengths of the WV-2 image obtained from the “Radiometric Use of WorldView-2 Imagery” guidelines by DigitalGlobe [13] were used as the targeted spectra in the spectral resampling process
Summary
Introduction published maps and institutional affilIndonesia is a global ecological hotspot, judging from the extent and rich biodiversity of its mangrove ecosystem. The estimated global mangrove area is approximately 137,600 km , and Indonesia has the largest mangrove forest, with a total area of 26,890 km. The estimated global mangrove area is approximately 137,600 km , and Indonesia has the largest mangrove forest, with a total area of 26,890 km2 It accounts for 19.5% of the mangroves worldwide and 50.4% of those in Asia. The characteristics of mangrove forests generally differ from those of mainland forests Their habitats are not climate-dependent but are shaped by tides, the extent of seawater-inundated soils, elevation, and the presence of canopy structures. They especially thrive on low-lying land without canopy structures [4].
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