栅格结构（Raster data）

最新推荐文章于 2025-10-11 09:50:25 发布

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本文探讨了基于二维平面上的矩形网格划分的栅格数据结构如何用于汇总点模式，并通过实例展示了如何将点模式叠加到网格上形成计数矩阵。详细介绍了从实际坐标值、整数单元计数到有序颜色的转换过程，以及这一过程带来的信息损失与获得的便利性，包括数据结构更紧凑、可视化直观和与其他栅格数据的关联性。

Using a raster to summarize a point pattern.

A raster data structure is based on a (usually rectangular, square-based) tessellation of the 2D plane into cells. In the example the cells of tessellation A is overlayed on the point pattern B resulting in an array C of quadrat counts representing the number of points in each cell. For purposes of visualization a lookup table has been used to color each of the cells in an image D. Here are the numbers as a simple vector in row/column order:

1 3 0 0 1 12 8 0 1 4 3 3 0 2 0 2 1 7 4 1 5 4 2 2 0 3 1 2 2 2 2 3 0 5 1 9 3 3 3 4 5 0 8 0 2 4 3 2 8 4 3 2 2 7 2 3 2 10 1 5 2 1 3 7

Finally, here is a run-length encoded representation of the raster, which has 55 positions:

values : 1 3 0 1 12 8 0 1 4 3 ...
lengths: 1 1 2 1 1 1 1 1 1 2 ...

This process clearly results in a loss of information, from the real-valued coordinates of the points, through the integer cell counts, to the ordinal colors, but there are also gains:

The data structure is usually more compact,
The raster is easy to visualize, and
It can be related to other rasters provided the locations and resolutions are properly conflated.