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首页> 外文期刊>Geocarto international >Potential fish habitat mapping using MODIS-derived sea surface salinity, temperature and chlorophyll-a data: South China Sea Coastal areas, Malaysia
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Potential fish habitat mapping using MODIS-derived sea surface salinity, temperature and chlorophyll-a data: South China Sea Coastal areas, Malaysia

机译：使用MODIS得出的海面盐度，温度和叶绿素a数据进行鱼类栖息地潜在分布图：马来西亚南海沿岸地区

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摘要

This paper demonstrates the use of moderate resolution imaging spectro-radiometer (MODIS) data for fish forecasting mapping of seasonal spatial distribution of sea surface salinity (SSS), temperature (SST) and chlorophyll-a in the ocean waters off the coast of Semporna, Malaysia. Multi-linear regression analysis was performed to estimate SSS and the Brown and Minnet algorithm was used for the SST. The extracted parameters were validated using in situ measurement taken with Hydro-Lab equipment. The extracted parameters from MODIS images reveal the signature values which establish the relationships between these parameters, and thus delineating the potential fish zonation (PFZ) map. These developed models will help for accurate monitoring of large coverage areas at low cost and within short period of time. Furthermore, such models will allow the prediction of the total fish catch in different seasons, thus contributing to fish industry management and marketing. This research recommends the use of PFZ map for mass scale fish harvesting in short time for larger areas. Finally, the research has developed a potential fish zone model amalgamating all the above parameters. The PFZ mapping was carried out off the coast of Semporna, Sabah as there were sufficient fish catch data for accuracy assessment. The R was computed as 0.93 and the higher fish catch areas have coincided very well with the higher PFZ values, meaning the tool is ready for use for operational near real-time fish forecasting.
机译：本文展示了中分辨率成像光谱仪（MODIS）数据在仙本那（Semporna）沿海海域中的鱼类预测海表盐度（SSS），温度（SST）和叶绿素a的季节性空间分布中的应用，马来西亚。进行多线性回归分析以估计SSS，并将Brown和Minnet算法用于SST。使用Hydro-Lab设备进行的原位测量验证了提取的参数。从MODIS图像中提取的参数揭示了特征值，这些特征值建立了这些参数之间的关系，从而描绘了潜在的鱼区（PFZ）图。这些开发的模型将有助于在短时间内以低成本精确监控大覆盖区域。此外，这种模型将允许预测不同季节的总捕鱼量，从而有助于鱼类产业的管理和销售。这项研究建议使用PFZ地图在较大面积的短时间内大规模捕捞鱼类。最后，研究开发了将上述所有参数融合在一起的潜在鱼区模型。 PFZ制图是在沙巴州仙本那（Semporna）沿海进行的，因为有足够的渔获数据用于准确性评估。 R的计算值为0.93，较高的渔获面积与较高的PFZ值非常吻合，这意味着该工具已准备就绪，可用于操作近实时鱼类预测。

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