A First Approximation for Acid Sulfate Soil Mapping in Areas with Few Soil Samples

Acid sulfate soil mapping is the first step to avoid possible environmental damages created by one of the most problematic soils existing in nature. One of the problems in acid-sulfate soil mapping is the lack of soil samples in some regions. This prevents the creation of occurrence maps. For the fi...

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Bibliographic Details
Published inEnvironmental Sciences Proceedings Vol. 29; no. 1; p. 4
Main Authors Virginia Estévez, Stefan Mattbäck, Anton Boman
Format Journal Article
LanguageEnglish
Published MDPI AG 01.01.2024
Subjects
acid sulfate soils
digital soil mapping
random forest
remote sensing
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Summary:Acid sulfate soil mapping is the first step to avoid possible environmental damages created by one of the most problematic soils existing in nature. One of the problems in acid-sulfate soil mapping is the lack of soil samples in some regions. This prevents the creation of occurrence maps. For the first recognition of these regions, a possible solution could be the use of soil samples from other areas with similar characteristics. In this study, we analyze if a machine learning method is able to correctly classify the soil samples in an area where it has not been trained. For this, Random Forest and two different regions located in southern Finland with a similar composition of soils are considered.
ISSN:2673-4931
DOI:10.3390/ECRS2023-15831