Updating traditional soil maps with DSM techniques European

Updating traditional soil maps with DSM techniques European Commission DG JRC Senthil Selvaradjou 3/16/2018 F. JRC Ispra NCSS, 07/06/06 - IES Carré, H. Reuter, A. Jones, L. Montanarella Selvaradjou et al.

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 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

Soil type map Objectives ‘Extract the soil distribution rules’ Soil covariates (RS images, DEM…) Update the soil map New soil type map Original soil type map 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

Two applications Updating the Asian part of the FAO Soil Map (1988) No change in time New soil type map Soil map MODEL Soil covariates Updating potential soil erosion assessment Change in time New soil erosion map (t 1) Soil erosion map (to) MODEL 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Soil covariates to Soil covariates t 1 Selvaradjou et al.

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 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

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 Mean ratios of ratio and optimal nutrient ratios Consider 3 nutrients (A), (B) and (N) where the reference population Z = 2 (n-1) Equilibrium Index of the System (EIS) EIS ~ 0 (optimum state of the system 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

DRIS for updating soil erosion map 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

The original soil erosion map Soil Map of erosion of Tamil Nadu region (NBSS & LUP, 1997) 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

Legend transformation 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

The nutrients equivalent Soil erosion is a function of 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

Division of the population High yield ~ none to slight erosion {class 1} Low yield ~ From slight to severe erosion {classes 2 to 4} 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

Calculation of the EIS Erosion factor 1 (EF 1) Index (EF 1) Erosion factor 2 (EF 2) Index (EF 2) Erosion factor n (EFn) Index (EFn) n EFi EIS 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

Map of the EIS Reclassification of the EIS according to the original classes of soil erosion Introduction of classes for quantifying ‘continuously’ soil erosion 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

New quantitative map of soil erosion 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

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 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

DRIS for updating soil map 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

The FAO soil map of South Asia 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

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 1 EIS (T 1) Min(EIS) Soil Type 2 EIS (T 2) Soil Type n EIS (T 3) 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al. Corresponding soil type

The updated soil map 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.

Conclusions The DRIS approach allows for updating soil maps based 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 (Arc. Info algorithms) We are now comparing this approach to classic DSM soil inference systems 3/16/2018 JRC Ispra NCSS, 07/06/06 - IES Selvaradjou et al.