Statistics Analysis

2006-12-24T21:26:00.000-08:00

Statistic data from a certain year can be mapped and compared with a different set of statistical data from another year which originates from the same geographic extent.
Statistical data can be used to clean up data, smooth out rough edges and make the data more meaningful.
It's an process which can be used to extract averages, highest, lowest, means and even deviations values from your acquired data sets and visualize the data on a map.

Compare values over time is sometimes necessary to calculate the past/current/following years timber/sugar yield, increase of customers, increase of population, encroachment of cities or towns on river banks or indigenous forests, the list can be endless.

The following examples are base on cell x cell analysis to find trends or detect changes between various years data sets.

Land Cover 1990

2006-12-21T21:41:00.000-08:00

Land cover for the year 1990 were recorded and mapped.

Land Cover 2000

2006-12-21T21:39:00.000-08:00

Land cover for 2000 were recorded and mapped

As note from the previous two maps, it is impossible to establish which vegetation has grown vigorously and which vegetation where overpowered by severe competition.

Vegetation Change Analysis

2006-12-21T21:38:00.000-08:00

I produced a raster illustrating the change of vegetation that occurred over the past 10 years. This raster is used to mask(cut) out these areas from both 1990 and 2000 datasets/rasters.

Vegetation 1990

2006-12-21T21:37:00.000-08:00

The mask and a cell statistical analysis where applied which resulted in the above raster. Here I identified the minority vegetation with a graph illustrating the min- vegetation count for 1990.

Vegetation 2000

2006-12-21T21:36:00.000-08:00

The same mask and cell stats analysis where applied to the 2000 data sets.
It's possible to identify which species has grown or declined over the past ten years.

Conclusion
From this analysis the total area can be established to calculate loss/increase of volume. The data set can also be compared to temperature and rainfall data to establish growth patterns related to weather. Once a pattern is establish a model can be constructed to produce future predicaments using current data for calibrations.

Home/Back