MTA ATK TAKI Institute for Soil Sciences and Agricultural Chemistry,

Centre for Agricultural Research, Hungarian Academy of Sciences

Comparison of a soil texture map synthetized from GlobalSoilMap standard layers

with a goal specifically compiled product

Annamária Laborczi, László Pásztor, Gábor Szatmári, Katalin Takács, Zsófia Bakacsi

7th Global Digital Soil Mapping Workshop 2016 Aarhus, Denmark

• Introduction two ways to compile topsoil texture class maps

• Mapping process reference data, co-variables, methods…

• Results maps, comparison, validation…

• Conclusions

Comparison of a soil texture map synthetized from GlobalSoilMap standard layers

with a goal specifically compiled product

Topsoil 0-30 cm texture class maps

Reference point data

weighted average

0-5, 5-15, 15-30 cm 0-30 cm

SYNTHETIZED MAP

EXPECTED MODEL INPUT

SPLINE

CLAY/SILT/SAND MAP

DIRECTLY COMPILED MAP

SIMS Hungarian Soil Information

and Monitoring System

Particle size (mm)

Particle size fraction

< 0,002 CLAY 0,002-0,005

SILT 0,005-0,01 0,01-0,02 0,02-0,05 0,05-0,2 SAND 0,2<

~ 1200 points

Recently sampled point database

Laboratory measurements e.g. pH, SOM, CaCO3, heavy metals & particle size distribution

Reference soil data

Environmental co-variables

TOPOGRAPHY EU-DEM and derivatives • Elevation • Slope • Aspect • General Curvature • Vertical Distance to Channel Network • SAGA Wetness Index • Topographic Wetness Index • Diurnal Anisotropic Heating • Real Surface Area • Channel Network Base Level • MRVBF - Multiresolution Index

of Valley Bottom Flatness • MRRTF - Multiresolution Index

of Ridge Top Flatness • Mass Balance Index • Stream Power Index • LS Factor • Topographic Position Index

LAND USE AND VEGETATION MODIS images March 2012 & September 2013 NDVI 16-day average

SOIL Digital Kreybig Soil Information System (DKSIS) Soil physical property categories

METEOROLOGY average annual evapotranspiration average annual precipitation average annual temperature annual evaporation

LITHOLOGY Geological Map of Hungary 1:100.000 – merged FAO categories

Environmental co-variables

Regression Kriging

Environmental co-variables

CLAY, SILT, SAND rasters

Nationwide soil texture class map

SIMS Hungarian Soil Information and Monitoring System

0-5 cm

5-15 cm

15-30 cm

Synthetized

0-30 cm

CLAY SILT SAND 0%

100%

Synt

hetiz

ed m

ap

Dire

ctly

com

pile

d m

ap

D

S

D - Directly compiled 0-30 cm USDA texture class map

S - Synthetized 0-30 cm USDA texture class map

CLAY

D

S

Histogram

SAND D S

Histogram

D

CLAY

SAND

S

D

S

Scatterplot

Difference D - S

SAND

Difference D - S

CLAY

Accordance Minor difference Major difference

USDA texture class differences (D, S) based on taxonomical distances

Validation with independent data

MARTHA Hungarian Detailed Soil Hydrophysical Database • 692 point • particle size distribution • laboratory measurements • spline

ME: Mean Error

MAE: Mean Absolute Error

RMSE: Root Mean Square Error

CLAY SAND

D S D S

ME -1,56 -1,06 1,76 1,40

MAE 6,50 6,84 12,19 12,36

RMSE 8,91 9,32 16,38 16,92

Total

Accuracy Kappa Index

D 0,85 0,42 S 0,84 0,40 D & S 0,93 0,76

clay clay loam

loam loamy sand

sand sandy clay

loam

sandy loam

silt loam

silty clay

silty clay

loam

user accuracy

D 0,82 0,81 0,83 0,74 0,86 0,72 0,83 0,86 0,89 0,87 S 0,77 0,81 0,83 0,83 0,80 0,80 0,82 0,85 0,88 0,87 diff. (%) 5 0 0 -9 6 -8 1 1 2 0

producer accuracy

D 0,70 0,80 0,87 0,82 0,86 0,73 0,84 0,87 0,88 0,86 S 0,72 0,79 0,85 0,83 0,89 0,71 0,84 0,86 0,87 0,85 diff. (%) -2 1 2 -1 -2 2 0 0 1 1

Validation with independent data

USDA texture classes (weighted Kappa according to taxonomical distances)

Conclusions

• The synthetized and the directly compiled soil texture maps have little differences.

• However, in case of particle size fractions, the differences are greater in the extreme ranges.

• Misclassification concerns more the extreme categories.

• Risk of using the synthetized map: it can intensify extremities

THANK YOU FOR YOUR KIND ATTENTION!