Michaela's GIS Journey

  Understanding the Scale Effects on Vector Data, Basic Resolution Effects on Raster Data, and Gerrymandering Scale Effects on Vector Data : Scale significantly influences how vector data is portrayed. Smaller-scale maps (such as 1:100,000) offer less detail, resulting in the generalization or exclusion of more minor features. Conversely, larger-scale maps (like 1:1,200) provide greater precision, capturing intricate details such as complex boundaries. As the scale reduces, polygons become simplified, and more complex boundaries—like those of irregular coastlines—are smoothed out. This has a direct effect on the accuracy of calculated areas and perimeters. Regarding hydrographic features, moving from a 1:1,200 scale to a 1:100,000 scale demonstrated a notable reduction in detail. Basic Resolution Effects on Raster Data : Raster data divides the world into a grid where each cell holds a single value. The resolution of raster data refers to the dimensions of these cells. A higher resolu

 Interpolating Water Quality Data for Tampa Bay In this exercise, we applied various interpolation techniques to explore water quality conditions in Tampa Bay, Florida, using a dataset of samples collected over a short period. The primary focus was on Biochemical Oxygen Demand (BOD) concentrations, measured in milligrams per liter, a key indicator of water quality. By using methods like Thiessen , IDW , and Spline interpolation, I was able to generate surfaces that estimate BOD levels across Tampa Bay, providing insight into the spatial distribution of pollution. Each method offered a different approach—some emphasizing sharp transitions between points and others providing smoother, more continuous surfaces that better represent gradual changes in water quality conditions. Performing Interpolation Analysis  Thiessen interpolation   assigns each location the value of the nearest point, resulting in abrupt boundaries that  may not be suitable for continuous phenomena like pollution. Inv