We present efficient algorithms to compute simple and complex map algebra operations over raster data stored in main memory, using the k²-acc compact data structure. Raster data correspond to numerical data that represent attributes of spatial objects, such as temperature or elevation measures. Compact data structures allow efficient data storage in main memory and query them in their compressed form. A k²-acc is a set of k²-trees, one for every distinct numeric value in the raster matrix. We demonstrate that map algebra operations can be computed efficiently using this compact data structure. In fact, some map algebra operations perform over five orders of magnitude faster compared with algorithms working over uncompressed datasets.

我们提出了使用k ² - acc紧凑数据结构对存储在主存储器中的栅格数据计算简单和复杂的地图代数运算的有效算法。栅格数据对应于表示空间对象属性（例如温度或高程度量）的数值数据。紧凑的数据结构允许在主内存中高效存储数据并以压缩形式查询它们。A k ² - acc是一组k ²-trees，栅格矩阵中每个不同的数值对应一个。我们证明了使用这种紧凑的数据结构可以有效地计算地图代数运算。事实上，与处理未压缩数据集的算法相比，某些地图代数运算的执行速度要快五个数量级以上。