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Spatial Modeling of Potential Lobster Harvest Grounds in Palabuhanratu Bay, West Java, Indonesia

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Palabuhanratu Bay is a location in the southern part of Java Island with a high lobster population. Based on field observation, the lobster population in Palabuhanratu Bay is dominated by Panulirus homarus (green sand lobster), Panulirus versicolor (bamboo lobster), Panulirus penicillatus (black lobster), and Panulirus ornatus (pearl lobster). This study aimed to develop a spatial model using satellite-derived data to predict potential lobster harvest grounds in Palabuhanratu Bay. The Earth observational satellite data used were multispectral Landsat 8-SR imagery, and information about chlorophyll-a, salinity, total suspended solids (TSSs), sea surface temperature (SST), and distance from the coastline was extracted. Multiple linear regression was applied to build the prediction model, which was validated using 10-fold cross-validation. The result of the lobster harvest prediction model agreed with the root-mean-square error (RMSE) and adjusted R2 values of 0.326 and 0.708, respectively. The distribution of lobsters was strong at the following preferred ranges: chlorophyll-a: 1.1–1.7 mg/m3; salinity: 20.2–23.7 ppt; TSS: 40–56.4 mg/L; SST: 29.5–29.9 °C; and distance from the coastline: 500–4700 m. In this study, the habitats of four species of lobsters and their relationships with satellite-derived parameters were evaluated.
Title: Spatial Modeling of Potential Lobster Harvest Grounds in Palabuhanratu Bay, West Java, Indonesia
Description:
Palabuhanratu Bay is a location in the southern part of Java Island with a high lobster population.
Based on field observation, the lobster population in Palabuhanratu Bay is dominated by Panulirus homarus (green sand lobster), Panulirus versicolor (bamboo lobster), Panulirus penicillatus (black lobster), and Panulirus ornatus (pearl lobster).
This study aimed to develop a spatial model using satellite-derived data to predict potential lobster harvest grounds in Palabuhanratu Bay.
The Earth observational satellite data used were multispectral Landsat 8-SR imagery, and information about chlorophyll-a, salinity, total suspended solids (TSSs), sea surface temperature (SST), and distance from the coastline was extracted.
Multiple linear regression was applied to build the prediction model, which was validated using 10-fold cross-validation.
The result of the lobster harvest prediction model agreed with the root-mean-square error (RMSE) and adjusted R2 values of 0.
326 and 0.
708, respectively.
The distribution of lobsters was strong at the following preferred ranges: chlorophyll-a: 1.
1–1.
7 mg/m3; salinity: 20.
2–23.
7 ppt; TSS: 40–56.
4 mg/L; SST: 29.
5–29.
9 °C; and distance from the coastline: 500–4700 m.
In this study, the habitats of four species of lobsters and their relationships with satellite-derived parameters were evaluated.

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