Amélie Marie Beucher

Fuzzy logic for acid sulfate soil mapping: Application to the southern part of the Finnish coastal areas

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Fuzzy logic for acid sulfate soil mapping : Application to the southern part of the Finnish coastal areas. / Beucher, Amélie; Fröjdö, Sören; Österholm, Peter; Martinkauppi, Annu; Edén, Peter.

I: Geoderma, Bind 226-227, Nr. 1, 01.01.2014, s. 21-30.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Beucher, A, Fröjdö, S, Österholm, P, Martinkauppi, A & Edén, P 2014, 'Fuzzy logic for acid sulfate soil mapping: Application to the southern part of the Finnish coastal areas', Geoderma, bind 226-227, nr. 1, s. 21-30. https://doi.org/10.1016/j.geoderma.2014.03.004

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Author

Beucher, Amélie ; Fröjdö, Sören ; Österholm, Peter ; Martinkauppi, Annu ; Edén, Peter. / Fuzzy logic for acid sulfate soil mapping : Application to the southern part of the Finnish coastal areas. I: Geoderma. 2014 ; Bind 226-227, Nr. 1. s. 21-30.

Bibtex

@article{3e8927f9e799459e94d52e30764ba918,
title = "Fuzzy logic for acid sulfate soil mapping: Application to the southern part of the Finnish coastal areas",
abstract = "Acid sulfate (AS) soils constitute a major environmental issue. Leaching considerable amounts of acidity and metals into watercourses, they cause severe ecological damage. Small hot spots may affect large areas of coastal waters and mapping is required in order to carry out an efficient mitigation plan. The primary aim of this study was to assess the use of fuzzy logic for AS soil mapping at reconnaissance scale, applying it to the southern part of the Finnish coastal areas (c. 17,300km2). Using a limited amount of evidential datalayers (aerogeophysical data, quaternary geology and a Digital Elevation Model), it was possible to create probability maps for AS soil occurrence in the study area. On the most balanced probability map, the combined very high and high probability classes covered 12% of the study area and contained about 70% of the validation points corresponding to known AS soil occurrences. Using only the very high probability class, a conservative extent of AS soils could be assessed for the study area (c. 800km2), indicating that the extent of AS soil for the whole Finnish coastal areas would be higher than previously estimated. Being systematic and easily transferable, fuzzy logic represents an efficient approach, particularly adapted to carry out large scale preliminary survey in areas offering a limited amount of data.",
keywords = "Acid sulfate soils, Fuzzy logic, Probability map, Reconnaissance scale",
author = "Am{\'e}lie Beucher and S{\"o}ren Fr{\"o}jd{\"o} and Peter {\"O}sterholm and Annu Martinkauppi and Peter Ed{\'e}n",
year = "2014",
month = jan,
day = "1",
doi = "10.1016/j.geoderma.2014.03.004",
language = "English",
volume = "226-227",
pages = "21--30",
journal = "Geoderma",
issn = "0016-7061",
publisher = "Elsevier BV",
number = "1",

}

RIS

TY - JOUR

T1 - Fuzzy logic for acid sulfate soil mapping

T2 - Application to the southern part of the Finnish coastal areas

AU - Beucher, Amélie

AU - Fröjdö, Sören

AU - Österholm, Peter

AU - Martinkauppi, Annu

AU - Edén, Peter

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Acid sulfate (AS) soils constitute a major environmental issue. Leaching considerable amounts of acidity and metals into watercourses, they cause severe ecological damage. Small hot spots may affect large areas of coastal waters and mapping is required in order to carry out an efficient mitigation plan. The primary aim of this study was to assess the use of fuzzy logic for AS soil mapping at reconnaissance scale, applying it to the southern part of the Finnish coastal areas (c. 17,300km2). Using a limited amount of evidential datalayers (aerogeophysical data, quaternary geology and a Digital Elevation Model), it was possible to create probability maps for AS soil occurrence in the study area. On the most balanced probability map, the combined very high and high probability classes covered 12% of the study area and contained about 70% of the validation points corresponding to known AS soil occurrences. Using only the very high probability class, a conservative extent of AS soils could be assessed for the study area (c. 800km2), indicating that the extent of AS soil for the whole Finnish coastal areas would be higher than previously estimated. Being systematic and easily transferable, fuzzy logic represents an efficient approach, particularly adapted to carry out large scale preliminary survey in areas offering a limited amount of data.

AB - Acid sulfate (AS) soils constitute a major environmental issue. Leaching considerable amounts of acidity and metals into watercourses, they cause severe ecological damage. Small hot spots may affect large areas of coastal waters and mapping is required in order to carry out an efficient mitigation plan. The primary aim of this study was to assess the use of fuzzy logic for AS soil mapping at reconnaissance scale, applying it to the southern part of the Finnish coastal areas (c. 17,300km2). Using a limited amount of evidential datalayers (aerogeophysical data, quaternary geology and a Digital Elevation Model), it was possible to create probability maps for AS soil occurrence in the study area. On the most balanced probability map, the combined very high and high probability classes covered 12% of the study area and contained about 70% of the validation points corresponding to known AS soil occurrences. Using only the very high probability class, a conservative extent of AS soils could be assessed for the study area (c. 800km2), indicating that the extent of AS soil for the whole Finnish coastal areas would be higher than previously estimated. Being systematic and easily transferable, fuzzy logic represents an efficient approach, particularly adapted to carry out large scale preliminary survey in areas offering a limited amount of data.

KW - Acid sulfate soils

KW - Fuzzy logic

KW - Probability map

KW - Reconnaissance scale

UR - http://www.scopus.com/inward/record.url?scp=84896504694&partnerID=8YFLogxK

U2 - 10.1016/j.geoderma.2014.03.004

DO - 10.1016/j.geoderma.2014.03.004

M3 - Journal article

AN - SCOPUS:84896504694

VL - 226-227

SP - 21

EP - 30

JO - Geoderma

JF - Geoderma

SN - 0016-7061

IS - 1

ER -