I am currently working with rainfall data on a large grid layer and want to transfer the data onto smaller grids. In the image below the large blue polygons currently have the data stored in them and I want to smaller pink polygons to have the same data dependent on which blue polygon they lie within (which central point of blue polygon they are closest to).
The data in the large blue grid is in the following columns structure:
- Location (corresponds to each polygon of the grid e.g. A1, A2, B1, B2)
- Date (the measures occur over a time period split up into equal
- chunks in the format of text e.g. 'Time 1' 'Time 2' 'Time 3') Mean rainfall (a measure of rainfall averaging the rain across the time period I chose)
There are 9 time chunks so for each blue grid square there are nine corresponding rows in the attribute table, each recording the location, date and mean rainfall, so for example in grid square G5 the structure is:
and so on for each grid cell in the table.
The pink squares are where I actually want the rainfall data. I've been trying different joins but it only takes one of the time values, whereas I need all 9 as the mean rainfall is dependent on the date.
How do I get it so that every pink square that overlays blue G5 contains all nine rows of information about G5, and do the same for each of the other blue squares with their overlaying pink squares too? So the end result should be this within the attribute table for the pink squares (where pink location = label for unique pink grids, no relationship to blue location names):
Then this is repeated for every pink square, rather than what has been happening which is only the mean rainfall for Time 1 being copied over to the pink square.