i've hit a bit of a tricky visualisation issue;
I am quantifying some land use and land use change (LULUC) over a number of years. Typically, for data going from year to the next, a land change matrix is pretty handy;
In the above image you can see what percentage of the total land present in 2005 (the left column) becomes/stays as what in 2006 (the row along the top). Eg category A staying as category A is 50.2% of all land in the dataset, category B changing to category F is 2.4% of the land etc.
(p.s. R is preferable but anything that works is fine too
)
أكثر...
I am quantifying some land use and land use change (LULUC) over a number of years. Typically, for data going from year to the next, a land change matrix is pretty handy;
In the above image you can see what percentage of the total land present in 2005 (the left column) becomes/stays as what in 2006 (the row along the top). Eg category A staying as category A is 50.2% of all land in the dataset, category B changing to category F is 2.4% of the land etc.
- it is important to realise that this represents quantities of change from 05 to 06, not absolute quantities of that land category in either 2005 or 2006.
- I thought this multivariate time series idea for R was pretty nice, but it will only show absolute quantity from one category to another.
- A lattice/trellis plot where by the land categories are the 'outer' axes forming the structure of the trellis while 49 bar charts showing % change over each year step would be displayed, but this sounds horrid.
- A 3D plot where by the matrix above is in a 3D plot like a set of tiles, the colour of the square is used as the quantity indicator (think heatmaps and geom_tile in R), and then the data in the time series is stacked on top of it, almost like a stacked bar chart but each bar would consist of 'tiles' reaching the same height but colour to denote quantity at each level. Sounds complicated.
(p.s. R is preferable but anything that works is fine too
)أكثر...