Research Article

Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood

Algorithm 3

The algorithm of data prefetching and incremental data schedule.
Input: The dynamic error of view-dependent   ,
       data scale of current data of scene , data
       position: longitude LONG, latitude LAT.
Output: Pre-fetch data set , and load file mapping buffer.
Description of function: Locate physical data block, and
        load data buffer in memory through the threshold of screen
        error and the position of scene, as the requirement of
        the amount of data in memory.
(1) Initialization: Clear data set .
(2) Traverse the head file of data source (physical model),
and determine which data block belongs to it
according to (LONG, LAT), meanwhile, record the number of involved files.
(3) For each file from to fileN, do the process as follows:
//If it is a single file, then execute once,
otherwise, execute more than once
       (3.1) According to and Formula (2), compute the error
         threshold needed by current scene.
       (3.2) Get cluster , and let the arrangement of static error
           thresholds of be: ,
            , determine which interval belongs to,
           and define the cluster which meets the requirements as .
       (3.3) If is less than fileN, then go to step 3.
(4) According to the moving direction of viewpoint, update the
value of LONG and LAT, and establish fileN file mapping buffers.
(5) If fileN is 1, then determine the initial position of
(according to LONG, LAT), and intercept data block .
(6) If fileN is greater than 1, then determine the position
      of cluster , and let be  , and fileN:
      (6.1) Judge the relation of the file of two adjacent data block
     (as Figures 5(b), 5(c), and 5(e));
      (6.2) Distribute data blocks in , and form .
          According to the position relation Z-shape filling adjacent
          data block cluster after that.
(7) If the intersection of  and the existed data in data
      buffer is empty, then load , otherwise load ,
      namely load data incrementally.
(8) The end.