GIS-based measurements can combine vector and raster data to produce thematic data obtained from remote sensing data. The data used in this study uses data on land use in the city of Pekanbaru. After the data is obtained, the pixel calculation process is carried out using three methods: the cell center method, the maximum area, and the maximum combined area. This data describes information with multiple raster data resolutions and then interprets the level of distortion in the data. The research findings found that in the process of raster data from 8 different resolution levels for the 5x5 meter category, it is able to provide results that are closest to the area of vector data, where PL 1 code produces 404229 pixels, PL 2 code ranges from 225717 pixels, PL 3 code ranges from 160323 pixels, code PL 4 ranges from 92268 pixels, PL 5 code reaches 73384 pixels, PL 6 code reaches 57237 pixels, and PL 7 code reaches 48315 pixels. Meanwhile, of the 3 methods that were compared to determine distortion with vector data, the cell center approach was the closest to raster data by calculation through eight levels of raster resolution compared to the other two methods. In choosing the right pixel resolution for further use in mathematical modeling, it is necessary to pay attention to the level of resolution by generalizing the resolution of satellite imagery data so that the data can have the same resolution. The weakness of the three methods lies in increasing the resolution the greater it will make the data coarser. This research is expected to be used as a consideration in future research to add a more precise process and be able to produce less storage capacity.
Pangkalan Kuras District is a small part of Pelalawan Regency which is located in Riau Province. The resulting hydrometeorological disasters have impacts ranging from material losses and non-material losses such as loss of livelihoods, loss of life, damage to land, threatened habitat, and disruption of interaction with human activities. The purpose of this study is to provide the appearance of disaster-prone areas with the ultimate goal of producing potential disaster-safe areas through a spatial approach. This study uses data on topography, climatology, lithology, groundwater basins, soil characteristics, and land use. While the method applied is divided into 5 analyzes, namely analysis of area functions, land capability, land suitability, prone to flooding, and prone to landslides. The results of this study explain the division into 2 final areas, such as the potential area reaching 160,985 ha and the limiting area reaching 43,889 ha. This condition can be developed in various sectors to support the improvement of the community's economy by minimizing losses from various hydrometeorological disasters.
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