Ruslisan, Nur H. Kalam, Aglis C.Dwinita, Muhammad H. Habibi, Ernawati T. Rahayu, Nurkhovia Dewi, Eleonora E. Henny K., and Wirastuti Widyamanti. 2016. Water Quality Assesment Using Remote Sensing and GIS for In-shore Marine Environment Suitability. Aquaculture Indonesiana, 17 (2): 46-53. In-shore marine environment and its adjoining estuary has a potential susceptibility to water pollution due to the continuous discharge of its unhealthy catchment. Seawater quality studies commonly require a very detailed water sampling and analysis, leading to high expenditures on time and energy. This study aims to examine the water quality of the Dodokan Estuary using remote sensing and geographic information system (GIS) approaches, and to determine the most appropriate water environment mapping unit for marine environment suitability studies. Landsat 8 and QuickBird® were used to extract water quality parameters using related spectral transformations. Field surveys were conducted concurrently to the Landsat 8 acquisition time on the study area, to collect water samples for laboratory analysis including sea surface temperature (SST), chlorophylla, Dissolved Oxygen (DO), and Total Suspended Solid (TSS). Mapping units were generated based on visual interpretation on QuickBird® for estuarine plumes, to identify the possible distribution of suspended material from its catchment. The statistical analyses present that the parameter extracted from the satellite imagery and from laboratory analysis produces R values of 0.7 in average, despite its low value on chlorophyll-a. By utilizing assorted sea-water marine suitability criteria, it can be concluded that the inshore marine environment in the Dodokan Estuary and its surrounding area are suitable for various biota conservation e.g. coral, sea-grass, and mangrove, and in contrast, marine aquaculture. The knowledgeable uses of remote sensing and GIS also assist the sea-water qualities assessment mapping in term of providing boarder understanding of a water environment condition to effectively minimize the cost of sampling.