senthil selvaradjou

Selvaradjou et al.

JRC Ispra - IESNCSS, 07/06/06

Senthil Selvaradjou

European Commission

Updating traditional soil maps with DSM techniques

DG JRC

F. Carré, H. Reuter, A. Jones, L. Montanarella

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Why is it important to be able to update traditional soil maps?

Local knowledge on soils contained in traditional soil maps

Usually, no associated guidelines on soil distribution rules

Soil surveyors are now retiring and field expertise will be lost soon

Due to lack of formalism of soil distribution, soil maps contain uncertainties which need to be removed

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ObjectivesSoil type map

‘Extract the soil distribution rules’

Soil covariates

(RS images, DEM…)

Update the soil map

Original soil type mapNew soil type map

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Two applications

Updating potential soil erosion assessment

Updating the Asian part of the FAO Soil Map (1988)

Soil map

Soil covariates

New soil type map

Soil erosion map (to)

Soil covariates to

Soil covariates t1

MODEL

No change in time

New soil erosion map (t1)

MODEL

Change in time

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Methodology

Based on the DRIS (Diagnosis Recommendation Integrated System) Approach (Beaufils, 1973)

Purpose: to evaluate through indices the effect of each nutrient on the nutritional balance of the plant (agronomic issue) {< 0 = deficit; 0=optimal; >0 = excess}

Premices

(a) Ratios among nutrients are usually better indicators of nutrient deficiencies than isolated concentrations values

(b) Some nutrient ratios are more important or significant than others

(c) Maximum yield are only reached when important nutrient ratios are near the ideal or optimum values (obtained from high yielding-selected populations)

(d) As a consequence, the variance of an important nutrient ratio is smaller in a high yielding (reference population) than in a low yielding populations and the relations between variances of high and low yielding populations can be used in the selection of significant nutrient ratios

(e) The DRIS indices can be calculated individually, for each nutrient, using the average ratio deviation obtained from the comparison with the optimum value of a given nutrient ratio

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Methodology Main steps of DRIS Approach

Dividing the population into two groups: high yield (reference population) and low yield

Calculation of norms using the variance largest ratio among high and low yielding populations

Calculation of nutrient indices based on the comparison between actual nutrient ratio and optimal nutrient ratios

Consider 3 nutrients (A), (B) and (N) where

Z = 2 (n-1)

Mean ratios of the reference population

Equilibrium Index of the System (EIS)

EIS ~ 0 (optimum state of the system

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DRIS for updating soil erosion map

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The original soil erosion map

Soil Map of erosion of Tamil Nadu region (NBSS & LUP, 1997)

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Legend transformation

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The nutrients equivalent

Soil erosion is a function of

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Division of the population

High yield ~ none to slight erosion {class 1}

Low yield ~ From slight to severe erosion {classes 2 to 4}

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Erosion factor n (EFn)

Index (EFn)

Calculation of the EIS

Erosion factor 2 (EF2)

Index (EF2)

Erosion factor 1 (EF1)

Index (EF1)

EIS

EFi

n

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Map of the EIS

Reclassification of the EIS according to the original classes of soil erosion

Introduction of classes for quantifying ‘continuously’ soil erosion

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New quantitative map of soil erosion

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Detecting some changes in soil erosion

Introduction & replacement of ‘dynamic’ parameters like landcover and climate

Conservation of the ‘optimal’ ratios

New indices calculation

New EIS map and derivation of a new soil erosion

Comparison of the two different maps (original and new maps) and detection of the changes

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DRIS for updating soil map

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The FAO soil map of South Asia

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Where are the differences in approaches between erosion and soil classes map?

For soil classes map, there is no semi-quantitative values as for soil erosion

The variable is categorical

For each soil type, we use a DRIS model {presence of the soil type is the population of reference}

For each soil type, we calculate the EIS

Soil Type n

EIS (T3)

Soil Type 2

EIS (T2)

Soil Type 1

EIS (T1) Min(EIS)

Corresponding soil type

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The updated soil map

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Conclusions

The DRIS approach allows for updating soil maps b ased on expert knowledge contained in the original soil map

Since it is updating and not drastically changing the soil map, there is no criticism of the expert knowledge. DRIS consists in ‘harmoinizing’ the expert knowledge over the map

The information of the expert knowledge and the rules of the soil distribution is not directly accessible

This approach is computer demanding but it has been automated (ArcInfo algorithms)

We are now comparing this approach to classic DSM soil inference systems

senthil selvaradjou

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