<![CDATA[The coastal area is a meeting space between land and sea that is easy to change temporally and spatially. The changes were triggered due to an increase in population and community activities such as industry, housing, ports, cultivation, transportation, farms, agriculture, tourism, and so on centered in the coastal area and become the center of Indonesia's economy. Remote sensing technology is one of the right ways for monitoring activities in the near term. This research aims to map the change of coastal land use in Rungkut district, Surabaya, in 2013 and 2019 using high-resolution satellite imagery of SPOT imagery. The method of classification of coastal land use two types of supervised classification, namely Minimum Distance and Maximum Likelihood. Land use class obtained in this study as many as six classes, namely mangrove, settlement, pond, green open space, the body of water, and industry. The results showed that using two different algorithms gave a difference in classification results. The largest land-use change from classification with Minimum Distance method is in mangrove and body of water with +231,80 and –230,89 ha, while the classification result with the method of Maximum Likelihood the change of the largest land use is in mangrove class and ponds respectively +202,41 and –210,89 ha. Accuracy test using error matrix obtained by 85,50% with kappa coefficient 0,78 on the classification result of coastal land use using Minimum Distance algorithm and for Maximum Likelihood algorithm obtained accuracy of 89% with Kappa coefficient is 0,84. It is demonstrated that by using the algorithm, Maximum Likelihood accuracy on the land use map is very good.]]>
