Soil Science Example

Input Data

• are gathered from sensors stored in the ground.
• contain attributes: data quality, date, solar radiation, rain, wind velocity, temperature, pressure, etc.

The input file looks like:
'8639-SAM',21,01-MAY-87,15,24.06,16.85,958.8,0.0,0.0,-6.61,4.52,.09,10.68,.4,22.56,24.43,16.58,37.69,43.44,-8.54,210.09,210.08,161.58,472.54,99.51,295.69,'GGGGGGGGGGGGGGGG*GGGC*** ',23-MAY-89,'CPI-MRG'
'8639-SAM',21,01-MAY-87,45,22.83,16.28,958.85,0.0,0.0,-6.11,3.94,.06,10.24,.38,20.8,24.04,16.58,16.29,-6.07,-9.23,210.09,210.08,65.85,196.59,39.0,116.72,'GGGGGGGGGGGGGGGG*GGGGGGG ',23-MAY-89,'CPI-MRG'
...

Problem

Visualization

The visualization is created as follows:

1. Define Window 0 showing the global picture: solar radiation versus date, quality of solar radiation versus date, rain versus date, and quality of solar radiation versus date.
2. link the X axes of the views.
3. Define Window 1 as a copy of Window 0. It shows a zoomed in view.
4. Create a cursor to show the relationship between the Window 0 and Window 1.
5. Navigate Window 1 to find areas where there are lots of rain before a clear day, using the top views are reference points.
6. Windows 2, 3, 4 and 5 are windows that have been duplicated, showing possible places where there are lots of rain before a clear day.

Observations

1. This example shows need need to generate different views of the same data, and to keep track interesting places in the data.
2. Seasonal variation in the solar radiation observed for the first view: high in the sumer, and low in the winter.
3. Seasonal variation in the rain observed for the second view: high in the summer and spring.
4. Daily variation in the solar radiation, shown in the third view: radiation is high around noon.
5. Lots of rain before a clear day observed for the 3rd and fourth views.