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I have a data set showing vegetation change over a 100 year period. The data is categorical (ie. Conifer, Deciduous, Mixedwood, Grassland, Shrub, Open Canopy forest, non vegetated). Each cell in my data set represents a hectare. The data is discontinuous (I can only see 59% of the actual landscape, as some parts are hidden from view), and there is no data source to fill the holes.

I can account for all of the landscape change that is reversed succession (ie. anything that went from Coniferous to grassland) with ancillary data about known disturbances (fire, development, roads etc). I now want to understand what has driven the forward succession of some key transitions (ie. areas that were grassland in 1909 may now be Conifer, or Deciduous, etc). I have topographic data, solar insolation, natural subregions as predictors.

I am currently stuck trying to understand what analysis method I can use to model this relationship (ie. For Vegetation = Grassland in 1909, and for Vegetation = more advanced than grassland in 2008, what are the driving forces and correlates).

I am seeking ideas for analysis methods... preferably ArcGIS, but I can dig into other software if necessary

closed as too broad by PolyGeo Apr 13 '16 at 2:46

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

  • Isn't the answer right there in your question: "forward succession". Sure, it's an arguably outmoded concept, but that debate is more over trivial semantics and inferred value judgments than over the usefulness of the theory. So, time is the only correlate you need--and since you only have two snapshots, then you have nothing to model. Unless you're saying that you're interested in, e.g., why Conifer vs Deciduous in a given area. In that case, the historical data is a red herring, as you're only modeling site suitability for one type over another. – Tom Apr 11 '16 at 18:36
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    ...Historic land-use (logging, planting, etc.) may come into play in some areas. Depending on your desired level of detail/accuracy, soils and climate data are probably more important than insolation and "natural subregions". – Tom Apr 11 '16 at 18:39
  • @Tom You may want to provide your comments as an answer because I think this question is too broad for our focussed Q&A format. Most questions that are "seeking ideas" rather than asking a specific question are closed quickly. – PolyGeo Apr 11 '16 at 21:40
  • Thanks for some of the feedback Tom. The comment about succession is a good one, and this is the crux of the analysis: – ChrisStockdale Apr 12 '16 at 14:45