首页> 外文会议>International Symposium on LAPAN-IPB Satellite >Accuracy Test of Total Suspended Solid Concentration by Landsat 8 on In-Situ Data in Lancang Island Waters, Kepulauan Seribu
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Accuracy Test of Total Suspended Solid Concentration by Landsat 8 on In-Situ Data in Lancang Island Waters, Kepulauan Seribu

机译:Landsat 8在Lancang Island Waters的原位数据上悬浮固体浓度总悬浮浓度的精度试验,Kepulauan Seribu

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The Lancang Island waters have the potential of marine biological resources such as the crab (Portunus pelagicus). Thecrab is a species that eats suspended material. Remote sensing can estimate the parameters of Total Suspended Solid (TSS).The purpose of this study was to estimate the distribution and test the accuracy of TSS concentrations in Lancang Islandwaters extracted from Landsat 8 OLI images by field observations. Statistical test indicators that can be used for accuracytests include; root mean square error (RMSE), mean absolute error (MAE) and normalized mean absolute error (NMAE).The results of the RMSE value was 11.5 showed that the size of the error based on the difference between the value of theimage and field data. The smaller the RMSE value, means the results of the model estimation produced was more precisewith those observations. The MAE value of 1.774 showed the simplest form of error size. The MAE results indicated thatit could be seen that the prediction error of the distribution of TSS was too small. It means the prediction of the distributionof TSS in this study had high accuracy. The NMAE of 31.9% shows the error rate that is normalized and expressed inpercent (%). The NMAE value below 30% that could be used as proof of the validity of image data. The high error valuewas caused by differences in the time taken by field data with the recording time of satellite images and the effect of thincloud cover.
机译:澜沧岛水域有螃蟹(Portunus pelagicus)的海洋生物资源的潜力。这蟹是一种吃悬浮材料的物种。遥感可以估计总悬浮固体(TSS)的参数。本研究的目的是估算澜沧港TSS浓度的分布和测试通过现场观测从Landsat 8 Oli图像中提取的水域。可用于精度的统计测试指标测试包括;根均方误差(RMSE),平均绝对误差(MAE)和归一化平均绝对误差(NMAE)。RMSE值的结果为11.5显示了误差的大小,基于值之间的差值图像和现场数据。 RMSE值越小,表示产生的模型估计结果更精确随着这些观察。 1.774的MAE值显示最简单的误差尺寸。 MAE结果表明可以看出,TSS分布的预测误差太小。这意味着预测分布本研究中的TSS精度高。 31.9%的NMAE显示了标准化和表达的错误率百分 (%)。 NMAE值低于30%,可以用作图像数据的有效性的证据。高误差值是由于卫星图像录制时间和薄的录制时间的现场数据所花费的差异引起的云盖。

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