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SOILS INVENTORIES We can consider two basic approaches: A. Samples points extracted from a population of points. B. Mapping. For the first an example (at.

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Presentation on theme: "SOILS INVENTORIES We can consider two basic approaches: A. Samples points extracted from a population of points. B. Mapping. For the first an example (at."— Presentation transcript:

1 SOILS INVENTORIES We can consider two basic approaches: A. Samples points extracted from a population of points. B. Mapping. For the first an example (at european level) is the “Intensive Monitoring of Forest Ecosystems in Europe” (formerly ICP Forests). For the second an example is the “Soils Geographical Database of Europe” briefly presented at the beginning of this session. The two approaches do not conflict, but aims at different targets.

2 I will describe and briefly analyze some of the problems encountered during the activities of an experts group charged of the so-called HARMONIZATION for SGDB Europe scale 1 M all around ALPS; in other words the homogenisation of national databases, produced separately in different times by France, Switzerland, Austria, Slovenia and Italy. The first and the main task was centered on the transboundary harmonization of the geographic database (i.e. Maps) along the national borders (the so-called 50 km buffer zone), but this exercise requested also a coordination of SMU (Soil Mapping Units), both as polygons on the map as from the point of view of contents. Mapping Units was characterized by combinations of different STU (Soil Typological Units), defined according an array of variables (attributes specifically devised by the european dataset) and by a Soil Name (FAO-Unesco 1990 revised Legend and FAO-Unesco 1974 Legend).

3 A graphical example of the maps used as starting point. This was the situation between Slovenia and Italy: parts of Alps, down to south around Trieste (Carso and Istria).

4 A better example can be this: The situation at the border between Switzerland and Italy. All the data bases was stored using Arc/Info GIS, but here I show you a photograph of the map base, because at that time (and now too) I preferred an handicraft approach to mapping (I consider myself a craftsman in soil mapping); other coworkers will transfer marks and maps on an electronic support, but operation start in the brain, and basic concepts and choices pertain to human brain, not to machines.

5 I selected a sample area (window) for presenting and discussing the problems connected to the exercise of harmonization. The reasons of this selection are not very important, but will be clarified during the presentation. In the next slide you will see a magnification of the area. The analysis about major problems that can arise during an exercise of harmonization will be conducted using LOGICAL RULES IF THE DATA, OPTION OR CHOICE ARE CONGRUENT TO THE RULE, THE PROCESS CAN GO ON (i.e. THE RESULTS WILL BE A SHARED INFORMATION) IF THE CHOICE IS A VIOLATION OF THE RULE, THE PROCESS MUST BE STOPPED, OTHERWISE THE RESULTS WILL BE A MISLEADING INFORMATION = MISINFORMATION

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7 SWITZERLAND Code number 41 ITALY Code number 39

8 FIRST LOGICAL RULE The landscapes present in the area are not very dissimilar. The valley systems north of the Lakes Region are arranged according a similar pattern; the Delta Elevation do not change greatly in IT and SZ; nor the climatic factors; bedrock are mainly metamorphic; the recent geological history (i.e. glaciation and deglaciation events) can be presumed quite homogeneously distributed. QUESTION: This similarity (geometric arrangement or SMU pattern) is recognizable on the map ? NO DECISION: If you want a SHARED INFORMATION rearrange the pattern, i.e. redrawn the geometric data set. This decision can be applied only to the part of the window interested by the aforeside description.

9 Let me open a brief digression. The origin of the basic geometric data sets presented for Italy and Switzerland must be searched in remote times: For Switzerland the digitized base was derived from the Atlas de la Suisse (scale 1:500.000, 2nd edition, 1984; elaborated in the Inst. de Cartografie Ecole Polytech. Fédéral de Zurich, by Prof. Frei & Peyer and coworkers). For Italy the digitized base was derived from the Soil Map of Italy (original scale 1:1M, 1966; prepared by Prof. Mancini and coworkers, with changes and subsequent modifications in 1984 and following years). The basic concepts used by the different authors were not very dissimilar. Mapping units, types of soils and their distribution were decided by the supposed influence of pedogenetic factors (mainly climate, vegetation, bedrock and some very general ideas about landscape). Both maps were not derived from a generalized survey of true soils, but by ideas elaborated from few profiles, the so-called “zonal soils” (*), allotted on the national land. (*) According to D. Dent and A. Young (1980) a ZONAL SOIL is commonly regarded as one in which the properties are primarily determined by climate. Experience suggests a revised definition: a zonal soil is the soil type that was thought to be present before anyone went to have a look.

10 Photogrphic reproduction of Sols de la Suisse. Vue d’ensemble

11 Partial Photogrphic reproduction of Soil Map of Italy.

12 SECOND LOGICAL RULE Soil Mapping Units in soilscapes that present similarities must be congruent, i.e. described with similar assemblage of soil types. QUESTION: There are some SMU in the central part of the window that are described in similar way, i.e. present soil types with names, an array of variables and a percentage of coverage into the SMU that are congruent ? NO DECISION: Rearrange the component descriptions of SMU’s pertaining to soilscapes that can be devised as similar, i.e. choose those parts of landscapes (geometric data set) that can be declared (or supposed) similar and build up a new shared data set of SMU’s. This decision (and the subsequent exercise) assume the observance of a third logical rule. next

13 THIRD LOGICAL RULE Soil Typological Units pertaining to similar landscapes must be described in a congruent way, i.e. each STU that can be present in SZ and IT and is used to describe soil bodies very similar must have an identical (or very similar) array of variables. This identity guarantees soil scientists and users of the database that everyone is talking about same objects. An administrative boundary cannot separate overlapping objects and relative concept (SHARING INFORMATIONS ON SOIL TYPES). QUESTION: There are some STU in the central part of the window that are described in similar way, i.e. present soil types with names, an array of variables and a percentage of coverage into the SMU that are congruent ? NO DECISION: Build up new shared tables of SOIL TYPES. STU tables are a the conceptual bases of any soil data base.

14 Photographic reproduction of West-Northern Alps. Base Soil Map. Draft edition, scale 1:500.000, prepared for discussion of border harmonization.

15 Photographic reproduction of East-Northern Alps. Base Soil Map. Draft edition, scale 1:500.000, prepared for discussion of border harmonization.

16 Example extracted from the semplified legend proposed for the harmonization exercise. Boxes report a synthetic definition of the major landscape characterization.

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18 SUGGESTIONS The basic starting point for a process of harmonization would be: A. Use the “true soil” information, i.e. the point samples (profiles) B. Homogenize the data of profiles (extracted and selected from regional and national databases). C. Grouping the harmonized single profiles into sub-populations. D. Into each sub-populations try to create classes of conceptual entities (Soil Types, Series, Soil Bodies, etc.). E. Define major landscapes, and draw a geometric database. F. Create groups (assemblages) of soil types that are logically present in each landscape (soilscapes). G. Match any one of this soilscape with the surveyed areas that can be reasonably collected and allotted to the geographical database.

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