Time Series vs. Time Slice
As described here, when importing geographies (shapefiles, gdb files, Excel files, or text files) and files of attribute data (Excel files, text files, or DBFs), you will need to determine the most appropriate way to structure your data with respect to time. SpaceStat provides two options, time series and time slice, described below.
Time Series
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Time series data is for data that varies asynchronously (objects move or change attributes at different times).
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Time is specified by the time stamp in the rows in the data file. Time stamps in series data are considered to be inclusive of the start stamp and exclusive of the end stamp. To include all of the end date or time, specify "Through end of time period". For details on how to write dates for SpaceStat, see temporal data formats.
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As an example: the table records that a rate of 56.7 for object 3 is valid from [1980, 1990) and then 89.1 is valid from [1990, 2000). This means that at the beginning of 1990, the value changes from 56.7 to 89.1.
|
ID |
Start Year |
End Year |
Rate |
|
3 |
1980 |
1990 |
56.7 |
|
4 |
1980 |
2000 |
70.6 |
|
3 |
1990 |
2000 |
89.1 |
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If your file includes records with missing values for start or end times, these rows will be skipped upon import into SpaceStat.
Time Slice
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Time slice data is for data that varies in a synchronous matter (objects or attributes change at specified times for all objects in the dataset).
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Time slice data are efficiently represented as files with synchronous observations on all of the objects. The time stamp is set at the level of the entire file or for individual data columns on import, rather than individual data rows.
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File 1
|
File 2
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or Combined
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A note on exporting data
When exporting, SpaceStat exports time slice data, though several time slices can be exported in a single shapefile set.