No Clocks

1. Sequential schemes are suited to ordered data that progress from low to high. Lightness steps dominate the look of these schemes, with light colors for low data values to dark colors for high data values.

X TYPES OF COLOR SCHEMES 1. Sequential schemes are suited to ordered data that progress from low to high. Lightness steps dominate the look of these schemes, with light colors for low data values to dark colors for high data values. 2. Diverging schemes put equal emphasis on mid-range critical values and extremes at both ends of the data range. The critical class or break in the middle of the legend is emphasized with light colors and low and high extremes are emphasized with dark colors that have contrasting hues.

3. Qualitative schemes do not imply magnitude differences between legend classes, and hues are used to create the primary visual differences between classes. Qualitative schemes are best suited to representing nominal or categorical data.

The appearance and robustness of a color scheme is in part a product of what else goes on the map and the background over which you are trying to show your colors. Small differences in the color of linework or the presence of other map items (like labels) really has a big impact on the appearance of a color scheme, so be sure to try these options here before settling on a final color scheme. Overlay cities and roads for a first look at how well text and symbols can be read with the area colors you select. Though the examples we have chosen are highways and cities, they should give you a good idea of how other linework or typography will function on the map. We have also provided a grayscale DEM so you can see what happens to your colors when you combine them with other underlying map data: Generally speaking, colors become harder to distinguish and you will need to user fewer classes of data.

TIP: Try turning off the county borders or making them white; notice a big difference? Try changing the background surrounding the map to see how colors are changed by their surroundings.

Choosing the number of data classes is an important part of map design. Increasing the number of data classes will result in a more "information rich" map by decreasing the amount of data generalization. However, too many data classes may overwhelm the map reader with information and distract them from seeing general trends in the distribution. In addition, a large numbers of classes may compromise map legibility—more classes require more colors that become increasingly difficult to tell apart. Many cartographers advise that you use five to seven classes for a choropleth map. Isoline maps, or choropleth maps with very regular spatial patterns, can safely use more data classes because similar colors are seen next to each other, making them easier to distinguish.

To understand how zoom levels work, first we need a basic introduction to geodesy.

When we represent the world at zoom level zero, it’s 256 pixels wide and high. When we go into zoom level one, it doubles its width and height, and can be represented by four 256-pixel-by-256-pixel images:

At each zoom level, each tile is divided in four, and its size (length of the edge, given by the tileSize option) doubles, quadrupling the area. (in other words, the width and height of the world is 256·2zoomlevel pixels):

In technical terms, the cylindrical projection that Leaflet uses is conformal (preserves shapes), but not equidistant (does not preserve distances), and not equal-area (does not preserve areas, as things near the equator appear smaller than they are).

setView(center, zoom), which also sets the map center flyTo(center, zoom), like setView but with a smooth animation zoomIn() / zoomIn(delta), zooms in delta zoom levels, 1 by default zoomOut() / zoomOut(delta), zooms out delta zoom levels, 1 by default setZoomAround(fixedPoint, zoom), sets the zoom level while keeping a point fixed (what scrollwheel zooming does) fitBounds(bounds), automatically calculates the zoom to fit a rectangular area on the map