This is the potential suitability of various soil units for growing different crops.
In this area of Tuscany (Cinigiano), the aim was to create a landscape based platform for establishing the potential land use, to be confronted with other available data.
It’s not a reconstruction of historical crop type distribution over the landscape, that is the final and more complicated step.
For a start was taken a part of the Land Units map created for the project. This thematic map pictures the spatial distribution of the Land Units, intended as portions of the territory with homogeneous characteristics as far as soil, substrate, geomorphology and hydrology are concerned. For the methodology of compiling the map see Arnoldus-Huyzendveld, Pozzuto 2009.
For each Land Unit the Available Water Capacity (AWC) was estimated. This is the range of available water that can be stored in the soil and is available for growing crops, expressed in mm. It is assumed that the water readily available to plants is the difference between water content at field capacity and the permanent wilting point.
Another, independent, procedure has been the calculation of yearly solar radiation for the area. Incoming solar radiation (insolation) received from the sun is the primary energy source that drives many of the earth’s physical and biological processes. On the intermediate landscape scale, topography is a major factor that determines the spatial variability of insolation. Variation in elevation, orientation (slope and aspect), and shadows cast by topographic features all affect the amount of insolation received at different locations. This variability also changes with time of day and time of year, and in turn contributes to the variability of microclimate.
In GIS programs, in order to calculate the insolation of a specific area, a series of variables can be set separately. It is a complicated and time consuming calculation. One starts from the DEM. The output radiation rasters will have units of watt hours per square meter (WH/m2).
For a start, in our case all the variables were kep at default value.
The next and final step is to convert these numbers into an hypothesis on historical crop distribution.
This can only be done by considering also yearly and monthly precipation and temperatures, by confronting our data with others like the individual crop-type requirements and those deriving from vegetation remains and pollen encountered at the excavations or in nearby areas, and with the knowledge of former agricultural techniques and other historical data. Here we move beyond the field of geoarchaeology.