Data integration in GIS refers to the process of combining data from multiple sources into a unified and coherent spatial database for analysis, visualization, and decision-making. In the context of Geographical Information Systems, data integration is essential because spatial data often originates from diverse sources such as satellite imagery, GPS surveys, census data, remote sensing platforms, and various governmental and non-governmental organizations. These datasets differ in format, scale, projection, accuracy, and temporal resolution, making integration a complex but necessary task. One of the primary aspects of data integration in GIS is the harmonization of spatial reference systems. Different datasets may use different coordinate systems and projections, which can lead to spatial misalignment. Therefore, transformation and reprojection are performed to ensure that all datasets align correctly in a common coordinate framework. Without this step, overlay analysis and spatial operations would produce inaccurate results. Another key component is data format standardization. GIS data can be stored in raster or vector formats, and each format serves different analytical purposes. Integration often involves converting data into compatible formats or using software tools that support multiple formats simultaneously. Additionally, attribute data associated