From Soil survey to Digital Soil Mapping The LISAH experience First DSM working group meeting...
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Transcript of From Soil survey to Digital Soil Mapping The LISAH experience First DSM working group meeting...
From Soil survey to Digital Soil Mapping
The LISAH experience
First DSM working group meeting University of Miskolc, Hungary, 7-8 April, 2005
P. Lagacherie
Laboratoire d’étude des interactions Sol – Agrosystème – Hydrosystème
Montpellier (France)
The roots : soil survey
1980-1995 : Soil Information System of the Languedoc-Roussillon at 1:250,000 scale (Bornand, et al, 1994)
1980-1990 : 1:10,000 scale reference areas (Favrot et al, 1981, 1989)
1960-1980: Soil surveying at various scale over the French territory (several millions ha)
1990-2005: A wide range of DSM problems explored
Pre-processing of soil covariate
Modelling soil information inputs
Building class Scorpan and class property functions
Evaluating and representing the quality of digital soil maps
Pre-processing of soil covariate
Modelling soil information inputs
Building class Scorpan and class property functions
Evaluating and representing the quality of digital soil maps
CLAPAS: Interactive Classification of Soilscapes (J.M. Robbez-Masson phD 1994, DSM 2004 proc.,2004)
AlluvionsColluvions
Old alluvions
Fallen rocks,
glacis
Towns, etc.
Hard limestones
Soft limestones
Dolomites
Marls, clays
Argilites
Schists, shales
Sandstones
Volcanic
formations
Gneiss and
granite
Lithological map
Low
Steep
Slope map
Images of soil forming factors
Reference areas
User selected reference areas
Unit 1
Unit 2
Unit 3
Unit 4
Unit 5
Unit 6
Unit 7
Unit 8
Unit 9
Unit 10
Unit 11
Map units
Image of classified soilscape(contextual image processing)
Reference areas (2nd pass)
Good
Medium
Bad
Mathematical distances
Image of landscape distance from reference areas
Unit 1
Unit 2
Unit 3
Unit 4
Unit 5
Unit 6
Unit 7
Unit 8
Unit 9
Unit 10
Unit 11
Unit 12
Unit 13
Unit 14
Unit 15
Unit 16
Map units
Good
Medium
Bad
Pre-processing of soil covariate
Modelling soil information inputs
Building class Scorpan and class property functions
Evaluating and representing the quality of digital soil maps
Representing qualitative soil information by means of possibility distributions (Lagacherie, Geod., in press)
Clay% silt% sand%
Hue value chroma
depth % stone react2acid
Soil classAuger hole
A: 0 - 15 cmColor: 75YR32text: LSA stone: 20%Rtoacid: ‘ None ’
B: 15 - 30 cm
Color: 75YR32text: LAS stone: 30%Rtoacid: ‘ None ’
C: 30 - 40 cm
Color: 75YR60text: ?stone: 90%Rtoacid: ‘ None ’
%Clay %Silt %Sand
Hue Chroma
Value
%Stone %RtoacidDepth
cmcm cm
cmcm cm
cmcm cm
% % %
%
Lagacherie et al, 1994
Pre-processing of soil covariate
Modelling soil information inputs
Building class Scorpan and class property functions
Evaluating and representing the quality of digital soil maps
Soil Pattern rulesSoil landscape rules
Scorpan functions using soil surveys of reference area (Lagacherie pHD 1992, Lagacherie et al, Geod. 1995, IJGS 1997, Voltz et al, EJSS 1997, Lagacherie & Voltz, Geod.2001)
Conditional probability approaches
Using the reference area scorpan functions
Reference area
Representative area
New mapped area
Predicting soils from covariates only (classif.
Tree)
(Lagacherie et al, 1997)
Predicting soils by DEM- driven-interpolation of
classified sites (Lagacherie et al, 1995)
Predicting soils properties by
interpolation of classified sites
(Lagacherie et al, 2001)
Pre-processing of soil covariate
Modelling soil information inputs
Building class Scorpan and class property functions
Evaluating and representing the quality of digital soil maps
Using fuzzy logic to propagate imprecision in Soil Information Systems
DTM
Geol map
Logical queries
Arithmetic expressions
Fuzzy pattern
matching
Degré de possibilité d ’US
0.00.20.40.60.81.0
Possibility of soil class
Cazemier, pHD, 1999, Martin-Clouaire et al, Compag, 2000
loamy clayey deep soil
moderate stoniness
Pedotransfer functions
awc = (w100i - w1500i) * bdi * thicknessi * ((100 - stonesi)/100))
Possibly > 240 mm
Surely > 240 mm
Undecided
Fuzzy constraint
solver
Cazemier, pHD, 1999, Cazemier et al, Geod., 2001
Geology = GU1 (1) or GU2 (0.8) or GU3 (0.2
Slope = most likely in [2%,5%] , not out of [0.5%, 8%]
Soil Class 506
Conclusion
A wide range of DSM questions examined
Integration of the soil survey experience in numerical procedures
Possible contributions to a more generic tool