Creating a satisfying quantitative color scheme is challenging for both novices and experts. Geovisualization often suffers from the misuse and misunderstanding of quantitative color schemes. This article presents an adaptive method to create ready-to-use quantitative schemes. A probability-based method for color selection is presented to quantify the selection of quantitative colors from learning samples of varying popularity. To shape the color transitions, a regression analysis is performed to fit the mathematical curves for the transitions of hue, saturation, and brightness. Finally, the problem of creating satisfying quantitative schemes is translated into a multiconstraint optimization problem. A discretize-and-filter method is also presented to solve the optimization problem of globally identifying a suitable scheme in a continuous color space. The proposed method is evaluated with a case study, and the results indicate that the proposed method can derive satisfying schemes. In addition, the proposed method is adaptive to mapping feature, target reader and target device.