3. ARCHAEOLOGICAL GIS
3.1 Primary Data
Table.1 Base data used in the constructed GIS
result of the preceding pollen analyses (Cultural Properties
Protection Department of Aichi, 1994, 1999) around the target
area through the intended period.
Selecting the tree species
interpreting the major species
| POLLEN ANALYSIS DATA e—
DATA NAME spatial attributes
: ; name, period, type, area, store tools,
Ruin point ;
pottenyetc
DEM 10, 50, 250mMESH elevation
Topographic map 1/50000 topography
Geologic map 1/50000 geography
Temperature
Normals for the 1KmMESH Temperature distribution map
Perind
Sea-Level point eustatic chanæ of sea level
Water Hazard 1/50000 micro topography water hazard risk
Pollen point pollen type proportion
River line river
Locations of ruins were digitised from the Ruin Map of Aichi
Prefecture (1994, 1995, 1996), published by Cultural Properties
Protection Department, board of education, Aichi. Attributive
information for each ruin was collected from the chart attached
to the map. Further detailed information was collected from the
individual excavation reports of each ruin. Selection of data
attributes was optimised for environmental archaeology by
paying special attention to excavated remainder. Especially, the
form of the pottery, and types of stone tools were taken into
account as their combinations and proportions could form an
important foundation to estimate the life style of the ancient
people. Such information could be examined and further studied
by multi-layering of the ancient environmental data sets. The
use of GIS enables clarification of not only the contents of the
phenomena but also the spatial relation. As long as spatial
phenomena, such as cultural diffusion or settlement pattern are
vital topics in archaeology, this function is unquestionably
relevant.
3.2 Secondary Data (VEGETATION)
The past vegetation was reconstructed through an analysis of
the preference of vegetation for environments. There are studies
for ancient vegetation reconstruction using GIS (e.g. Spikins,
1999). This present study features Warmth Index to estimate the
basic distribution of the vegetation. WI is a temperature index
of which parallelism with the distribution of tree species (Kira,
1950) is widely recognised. WI can be calculated by the
mathematical expression below.
WI — Y (tm-5) (1)
im»5
where tm — average temperature of the month
Past WI was calculated from Temperature Normality for the
Period (1981-2000), by adjusting the difference of the
temperature (Nogami, 1994). The layers, then, used for the
consequent processing were:
1) WE
2) Topography;
3) Geography;
4) Distance from the sea;
5) Ridge; and
6) Valley.
Each of the above layers and preference of each tree species
were compared, and probable distribution of primary vegetation
was estimated. The selection of tree species was based on the
Compute the broad tree distribution
WI DATA calculating the WI
classify the species to each Wi
TOPOGRAPHIC DATA y
tapography , : p
nda = Estimate the detailed distribution
uy E scoring the tree rule
di stance fo sea averiay
geography
Map of Past Vegetation
Fig.2 Calculating the most competitive vegetation from layer
and matrix
Polygon A
Layer2(ridge):yes
Layer3(valley):no
Layer4(WI):45-50
Layer5(topo) hill
Vegetation Preference Matrix
Most Competitive
vegetation is set to
polygon
Fig.3 Calculating the most competitive vegetation from layer
and matrix
Primary vegetation was estimated by overlaying the data sets. A
matrix was used to score the preference of the tree, the most
competitive vegetation was identified as the primary vegetation,
and polygons were drawn. When the score is same, the
vegetation was regarded as a mixed forest.
-—
3
2$ nonsi]
Tele
SIN
Fig.4 Calculated Vegetation of the 10000Years ago
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ml
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