The study obtained data for the selected area by acquiring Google satellite imagery on Google Earth, which covered a surface area of 5km x 5km. Digital data for bathymetric charts and models was downloaded using Offline Map Maker at various zoom levels, resulting in 93743 tile images in ".jpg" format. These tile images were combined to form a complete image, and some were converted to ".tif" format for use in ArcGIS.

In ArcGIS, the imagery was analysed, revealing three distinct natural features: vegetation, rivers, and bare land. Shapefiles were created for these features, and the imagery in ".tif" format was digitized using editing tools. A layer containing the coordinates of points in the area was added to the existing layers, with coordinates specified in terms of longitude, latitude, and depth.

Spatial interpolation, specifically the "Kriging" method, was applied to estimate unknown depth values based on the known depth values of some points. The results were visualized as a kriging raster surface showing depth variations through color gradation.

Contours were generated to represent depth variations, and the contours were edited to enhance their clarity. The raster points were converted into equally spaced grid points.

Coordinates (longitude and latitude) of the points were determined using the attribute table's "geometry calculation" function. Focus was placed on the water body's depth values, which were separated from the depth values of other features like vegetation and bare land using the "clip tool" in ArcGIS.

Depth values on the bathymetric chart were labeled uniquely, with decimal numbers presented as subscripts to integers. The bathymetric chart included digitized features from the imagery along with the water body's depth values. Additional elements like a scale bar and north arrow were added to complete the chart.

In bathymetry, depth values are typically expressed in their negative form, so a field calculator tool was used to convert depth values to negative by multiplying them by "-1." A bathymetric model was created in Surfer using the x-coordinates, y-coordinates, and negative depth values as data. Contour maps, shaded relief, 3D wireframes, and 3D surface models were also generated using the same data in Surfer.

Overall, the study involved the acquisition and detailed analysis of geospatial data, conversion, interpolation, and visualization techniques, and the creation of comprehensive bathymetric charts and models for the selected area.