Choropleth maps are powerful tools for visually representing geographic data variations. Among the different classification methods, the quartile method stands out for its ability to reveal patterns and outliers in a nuanced way. Let's embark on a cartographic journey to understand this method! Imagine a vast landscape of data points: Each point represents a geographic area (like a country, state, or county) with a corresponding data value (e.g., income, literacy rate, crime rate). Our goal is to create a map that divides these data points into meaningful groups based on their values. Enter the quartiles: The quartile method slices the data distribution into four equal parts: Q1 (First Quartile): Represents the 25% of data points with the lowest values. Q2 (Second Quartile): Also known as the median, it marks the middle 50% of data points. Q3 (Third Quartile): Encompasses the 25% of data points with the highest values. Each quartile threshold becomes a boundary for classif...
Focused on advancing knowledge and expertise in Geography, GIS, Remote Sensing, Geographical Data Science, and Analysis, I am deeply committed to teaching and conducting research in these fields. With a keen interest in leveraging data-driven approaches for informed decision-making, I specialize in crafting maps that facilitate effective analysis and interpretation of spatial information. Assistant Professor Of Geography, PG and Research Department of Geography, Government College Chittur