Relationships of Class Number Variation and Image Classification Accuracy in the LAPAN-A3 Multispectral Imager

E. A. Anggari, P. R. Hakim, A. Herawan, S. Salaswati, W. Hasbi
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Abstract

LAPAN-A3 has a multispectral imager payload that can be used for earth observation. One of its uses is for land use and land cover classification. To find out the suitability of the classification results with the actual data, it is necessary to calculate accuracy. This study aims to find out the relationship between variations in the number of classes and the accuracy of the classification results of LAPAN-A3 compare with Landsat-8. The research was conducted in 4 study areas in Indonesia, namely Mandailing Natal Regency (North Sumatra), Pandeglang Regency (Banten), Semarang City (Central Java), and Kupang Regency (NTT). It can be concluded that the accuracy is very good in the classification of 2 classes where the accuracy value is more than 95%. Good accuracy in the classification of 4 classes with an accuracy value of more than 85%. The accuracy is good enough in the 6 class classification with an accuracy value of 80%. The blur effect is the reason of the decrease in accuracy due to the less optimal ability to separate spectrals.
LAPAN-A3多光谱成像仪类数变化与图像分类精度的关系
LAPAN-A3具有可用于地球观测的多光谱成像仪有效载荷。它的用途之一是用于土地利用和土地覆盖分类。为了确定分类结果与实际数据的适用性,需要计算准确率。本研究旨在找出类数变化与LAPAN-A3与Landsat-8分类结果准确率之间的关系。该研究在印度尼西亚的4个研究区域进行,分别是曼达林-纳塔尔县(北苏门答腊)、班德朗县(万丹)、三宝垄市(中爪哇)和库邦县(NTT)。可以得出,在准确率值大于95%的2类分类中,准确率是很好的。在4类分类中准确率较好,准确率值在85%以上。在6类分类中准确率足够好,准确率值达到80%。模糊效应是精度下降的原因,因为较差的分离光谱的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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