Spatial Dynamical Modelling
with TerraME (lectures 3 –
4)
Gilberto Câmara
Land-Use modelling
example
Vale do Anari (Rondonia.mdb database)

Small-scale government planned rural settlement in Vale
do Anari (RO), established in 1982 and land parcels
sized around 50 ha
TYPOLOGY OF LAND CHANGE ACTORS IN VALE DO ANARI REGION
Land use
patterns
Spatial
distribution
Clearing
size
Variable
Actors
Main land
use
Linear
(LIN)
Roadside
Irregular
(IRR)
Near main Small
settlements
(< 50 ha)
and
main
roads
Regular
(REG)
Near main Medium and Midsized
Cattle
settlements large
and
large ranching
and
main (> 50 ha)
farms
roads
irregular
Description
Small
households
Subsistence Settlement parcels less than
agriculture 50 ha. Deforestation uses
linear patterns following
government planning.
Small
farmers
Cattle
ranching
and
subsistence
agriculture
linear
Settlement parcels less than
50 ha. Irregular clearings
near
roads
following
settlement parcels.
Patterns produced by land
concentration.
regular
Vale do Anari – 1985
source: Escada (2006)
Pattern type
Geometrical
Irregular
Linear
Vale do Anari – 1985 - 1988
source: Escada (2006)
Pattern type
Geometrical
Irregular
Linear
Vale do Anari – 1988 - 1991
source: Escada (2006)
Pattern type
Geometrical
Irregular
Linear
Vale do Anari – 1991 - 1994
source: Escada (2006)
Pattern type
Geometrical
Irregular
Linear
Vale do Anari – 1994 - 1997
source: Escada (2006)
Pattern type
Geometrical
Irregular
Linear
Vale do Anari – 1997 - 2000
source: Escada (2006)
Pattern type
Geometrical
Irregular
Linear
Vale do Anari – 1985 - 2000
source: Escada (2006)
Pattern type
Geometrical
Irregular
Linear
Can you grow it?
Anari -1985
Anari -1995
Anari -2000
1. Simple diffusive model: number of deforested neighbours
2. Diffusive model: : number of deforested neighbours + additional
factors
3. Statistical model without neighbours
4. Statistical model with neighbours
Can you grow it?
Anari -1985
Anari -1995
Anari -2000
-- CONSTANTS (MODEL PARAMETERS)
CELL_AREA = 0.25; -- 500 x 500 meters or 0.25 km2
DEMAND= 500; -- 100 km2
Vale do Anari (1985)
Vale do Anari (1995)
Vale do Anari (2000)
Pattern type
Geometrical
Irregular
Linear
General outline of land change models
Calculate potential
for change
Order cells according
to potential
Demand for
change
Allocate change
on cells
Spatial Iterator in TerraME
it = SpatialIterator {
csQ,
function(cell) return cell.champion == “Brazil”; end
}
Ordering cells in TerraME
Demand for
change
Calculate potential
for change
Order cells according
to potential
Allocate change
on cells
-- Step 2: Order cells according to potential
it = SpatialIterator {
csQ,
function(cell) return cell.pot > 0; end,
function (c1,c2) return c1.pot > c2.pot; end
}
-- Step 3: allocate changes to most suitable cells
count = 0;
for i, cell in pairs( it.cells ) do
if (count < num_cells_ch) and (count < it.count) then
cell.cover_ = "deforested";
count = count + 1;
end
Exercise 1 – Simple diffusive model
Expansion based on neighbourhood potential
More deforested neigbours, more potential for
change
Exercise 2 – Modified diffusive model
Expansion based on five factors:
1. Neighbourhood potential
2. Distance to main road (dist_rodovia_BR)
3. Distance to primary side roads (dist_ramal_princ)
4. Distance to secondary side roads (dist_ramal_sec)
5. Distance to urban centers (dist_urban)
main road
primary side road
secondary side road
Exercise 3 – Neighbourhood + regression
Expansion based on two factors:
1. Neighbourhood potential (50%)
2. Linear regression (50%)
poti= - 0.0012* dist_rodovia_BR
- 0.06* dist_ramal_princ
- 0.003* dist_ramal_sec
(normalize to [0,1])
Simple Linear Regression
20
18
16
14
12
10
8
6
4
2
0
-0.5
R2= 0.43
0
forest
0.5
1
deforested
1.5
Exercise 4 – Spatial regression
Expansion based on spatial regression
(includes neighbourhoods)
poti = 0.173*num_deforested_neigh
-0.1 * math.log10 (cell.dist_rodovia_BR/1000)
+ 0.053*math.log10 (cell.dist_ramal_princ/1000)
-0.157 * math.log10 (cell.dist_ramal_sec/1000)
(normalize to [0,1])
Exercise 4 – Spatial Regression
R2= 0.84