Soil Organic Carbon Mapping Seminar

Rome, 23 November 2016

Development of a soil carbon map for the United

Republic of Tanzania

Bas Kempen in collaboration with TFS (MNRT), SUA, NSS (MoA), ZAFORMA, AfSIS, FAO-TZ

Project overview

• Carbon concentration: 0-10 cm, 10-20 cm, 20-30 cm, 0-30 cm (Walkley-Black)

• Bulk density & Carbon stock: 0-30 cm

• Regression-kriging

• Raster with 250 m spatial resolution

• Uncertainty: 90% Prediction Interval

• GeoTIFF format with xml metadata

• Hands-on training digital soil mapping (Wageningen)

• Hands-on validation workshop (Dar es Salaam)

Final report

Literate programming: R / LaTeX

• Documentation and computer script (R code) weaved in 1 document (PDF report).

• Transparent and reproducible.

trend, explanatory part

𝑍 𝐬 = 𝑚 𝐬 + 𝜀(𝐬)

dependent, target variable

stochastic residual, unexplanatory

part, can be spatially correlated!

Unlike ordinary kriging, in regression kriging the trend is no longer constant but a function of ’explanatory’ variables, for example:

𝑠𝑜𝑖𝑙 𝑐𝑎𝑟𝑏𝑜𝑛 𝐬 = 𝛽0 + 𝛽1 ∙ 𝑒𝑙𝑒𝑣𝑎𝑡𝑖𝑜𝑛 𝐬 + 𝛽2 ∙ 𝑠𝑙𝑜𝑝𝑒 𝐬 + 𝛽3 ∙ 𝑁𝐷𝑉𝐼 𝐬 + 𝑟𝑒𝑠𝑖𝑑𝑢𝑎𝑙 𝐬

Regression kriging

Regression kriging algorithm

1. Select explanatory variables and fit regression model

2. Compute residuals (fitted trend – observed values) at observation locations

3. Compute semivariogram (quantify the spatial correlation)

4. Apply the regression model to all unobserved locations (usually a grid)

5. Krige the residuals to all unobserved locations

6. Add up the results of steps 4 and 5

Soil point data

• NAFORMA: 1409

• NSS: 306

• AfSIS: 975

• AfSP v1.1: 525 (>1992)

• 3215 observations

Four depth layers

• 0-10 cm: 3,215; 13.2

• 10-20 cm: 3,187; 11.0

• 20-30 cm: 2,839; 7.8

• 0-30 cm: 2,926; 10.7

Environmental covariate layers

• 37 layers from:

- AfSIS Grids – MODIS: 24

- AfSIS Grids – SRTM: 3

- WorldGrids.org: 4

- SOTER map (SOTERSAF): 2

- e-SOTER: 3

- NAFORMA: 1

• Raster: 31x (250 m, 500 m, 1000 m)

• Polygon: 6x

Climate (AfSIS grids)

• Land surface day and night temperature, 1000 m

Land cover

• NAFORMA LULC map (incl. Unguja , Pemba)

• ESA GlobCover v2.2 2005, 1000 m (WorldGrids)

- % mosaic vegetation

- % shrubland

Topography

WorldGrids

(1000 m)

• Landform

• Slope

AfSIS Grids

(250 m)

• DEM

• TWI

• SCA

Topography

e-SOTER

(Polygon)

• Elevation

• Slope

• Relief intensity

SOTER

(Polygon)

• Landform

MODIS Imagery: Vegetation (AfSIS grids)

1000 m

• FPAR

• LAI

• NPP (’00/’10)

• GPP (’00/’10)

250 m

• EVI

• NDVI

MODIS Imagery: Reflactance (AfSIS grids)

250 m

• Band1-R

• Band2-NIR

• Band3-B

• Band7-MIR

Yearly average

September

SOTER: dominant soil class

Model selection: selected model

• Explained variation (R2)

- CARBON:

• 0-10 cm: 0.36

• 10-20 cm: 0.39

• 20-30 cm: 0.36

• 0-30 cm: 0.45

- BULK DENSITY: 0.42

- SOC STOCK: 0.40

Variogram modelling

• Spatial correlation is quantified by the variogram in geostatistics

Spatial prediction

• Prepare a prediction grid of 250 m resolution (based on a MODIS image): >14 Million prediction points

• Sample covariate layers

• Computational intensive: prediction for two tiles of 7M points each requires >20 GB RAM memory

• Apply the regression-kriging algorithm

• Compute the uncertainty (90% prediction interval)

• Monte Carlo analysis to quantify uncertainty SOC stock

Predicted carbon concentration (%)

Prediction uncertainty: 90%PI

SOC stock

• Average: 4.1 kg/m2

• Total: 3.60 Pg

Uncertainty (95% CI):

4.0 - 4.15 kg/m2

.54 - 3.65 Pg

SOC stock uncertainty

• Average: 4.1 kg/m2

• Total: 3.60 Pg

• Uncertainty (95% CI):

- 4.0 - 4.15 kg/m2

- 3.54 - 3.65 Pg

Validation I

• 10-fold cross-validation

• Mean-error (bias)

• Mean absolute error / Root mean square error (accuracy)

Layer ME MAE RMSE RMedSE R2-RK R2-R

SOC concentration (g/kg)

0-10 cm -0.95 5.4 8.9 3.5 0.47 0.36

10-20 cm -0.66 3.8 6.2 2.3 0.49 0.39

20-30 cm -0.62 3.1 5.4 1.9 0.44 0.36

0-30 cm -0.44 3.4 5.4 2.1 0.59 0.45

Bulk density (g/cm3)

0-30 cm 0.00 0.1 0.14 0.08 0.56 0.42

SOC stock (kg/m2)

0-30 cm 0.00 1.23 1.8 0.9 0.53 0.40

Validation II

Thank you!

www.isric.org

bas.kempen(at)wur.nl