Individualization of soil classes by disaggregation of physiographic map polygons

The objective of this work was to disaggregate the polygons of physiographic map units in order to individualize the soil classes in each one, representing them as simple soil map units and generating a more detailed soil map than the original one, making these data more useful for future reference....

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Published inPesquisa agropecuaria brasileira Vol. 54
Main Authors Costa, José Janderson Ferreira, Giasson, Elvio, Silva, Elisângela Benedet da, Campos, Alcinei Ribeiro, Machado, Israel Rosa, Bonfatti, Benito Roberto, Bacic, Ivan Luiz Zilli
Format Journal Article
LanguageEnglish
Published Embrapa Secretaria de Pesquisa e Desenvolvimento; Pesquisa Agropecuária Brasileira 01.01.2019
Embrapa Informação Tecnológica
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Abstract The objective of this work was to disaggregate the polygons of physiographic map units in order to individualize the soil classes in each one, representing them as simple soil map units and generating a more detailed soil map than the original one, making these data more useful for future reference. A physiographic map, on a 1:25,000 scale, of the Tarumãzinho watershed, located in the municipality of Águas Frias, in the state of Santa Catarina, Brazil, was used. For disaggregation, three geomorphometric parameters were applied: slope and landforms, both derived from the digital terrain model; and an elevation map. The boundaries of the physiographic units and the elevation, slope, and landform maps were subjected to cross tabulation to identify the existing combinations between the soil classes of each physiographic unit. Based on these combinations, rules were established to select typical areas of occurrence of each soil type in order to train a decision tree model to predict the occurrence of soil classes. The model was trained using the Weka software and was validated with a set of georeferenced soil profiles. Disaggregation enables the individualization and spatialization of soil classes and is useful in producing detailed soil maps. Resumo: O objetivo deste trabalho foi desagregar os polígonos de mapas de unidades fisiográficas, de modo a individualizar as classes de solos ocorrentes em cada unidade, para representá-las como unidades de mapeamento simples de solos e gerar um mapa de solos com maior detalhe cartográfico que o mapa original, ampliando a utilidade desses dados em demandas futuras. Foi utilizado um mapa fisiográfico, em escala 1:25.000, da microbacia Córrego Tarumãzinho, localizada no Município de Águas Frias, no Estado de Santa Catarina. Para realizar a desagregação, foram utilizados três parâmetros geomorfométricos: declividade e formas do terreno, ambas derivadas do modelo digital do terreno; e mapa de elevação. Os limites das unidades fisiográficas e os mapas de elevação, declividade e formas do terreno foram submetidos à tabulação cruzada para identificar as combinações existentes entre as classes de solos que compõem cada unidade fisiográfica. A partir dessas combinações, foram elaboradas regras para selecionar áreas de ocorrência típica de cada tipo de solo, para treinar um modelo de árvores de decisão para predição da ocorrência das classes de solos. O treinamento do modelo foi realizado no programa Weka, e a sua validação foi feita com um conjunto de perfis de solos georreferenciados. A desagregação possibilita a individualização e a espacialização das classes de solos e é útil para a produção de mapas de solos detalhados.
AbstractList The objective of this work was to disaggregate the polygons of physiographic map units in order to individualize the soil classes in each one, representing them as simple soil map units and generating a more detailed soil map than the original one, making these data more useful for future reference. A physiographic map, on a 1:25,000 scale, of the Tarumãzinho watershed, located in the municipality of Águas Frias, in the state of Santa Catarina, Brazil, was used. For disaggregation, three geomorphometric parameters were applied: slope and landforms, both derived from the digital terrain model; and an elevation map. The boundaries of the physiographic units and the elevation, slope, and landform maps were subjected to cross tabulation to identify the existing combinations between the soil classes of each physiographic unit. Based on these combinations, rules were established to select typical areas of occurrence of each soil type in order to train a decision tree model to predict the occurrence of soil classes. The model was trained using the Weka software and was validated with a set of georeferenced soil profiles. Disaggregation enables the individualization and spatialization of soil classes and is useful in producing detailed soil maps. Resumo: O objetivo deste trabalho foi desagregar os polígonos de mapas de unidades fisiográficas, de modo a individualizar as classes de solos ocorrentes em cada unidade, para representá-las como unidades de mapeamento simples de solos e gerar um mapa de solos com maior detalhe cartográfico que o mapa original, ampliando a utilidade desses dados em demandas futuras. Foi utilizado um mapa fisiográfico, em escala 1:25.000, da microbacia Córrego Tarumãzinho, localizada no Município de Águas Frias, no Estado de Santa Catarina. Para realizar a desagregação, foram utilizados três parâmetros geomorfométricos: declividade e formas do terreno, ambas derivadas do modelo digital do terreno; e mapa de elevação. Os limites das unidades fisiográficas e os mapas de elevação, declividade e formas do terreno foram submetidos à tabulação cruzada para identificar as combinações existentes entre as classes de solos que compõem cada unidade fisiográfica. A partir dessas combinações, foram elaboradas regras para selecionar áreas de ocorrência típica de cada tipo de solo, para treinar um modelo de árvores de decisão para predição da ocorrência das classes de solos. O treinamento do modelo foi realizado no programa Weka, e a sua validação foi feita com um conjunto de perfis de solos georreferenciados. A desagregação possibilita a individualização e a espacialização das classes de solos e é útil para a produção de mapas de solos detalhados.
The objective of this work was to disaggregate the polygons of physiographic map units in order to individualize the soil classes in each one, representing them as simple soil map units and generating a more detailed soil map than the original one, making these data more useful for future reference. A physiographic map, on a 1:25,000 scale, of the Tarumãzinho watershed, located in the municipality of Águas Frias, in the state of Santa Catarina, Brazil, was used. For disaggregation, three geomorphometric parameters were applied: slope and landforms, both derived from the digital terrain model; and an elevation map. The boundaries of the physiographic units and the elevation, slope, and landform maps were subjected to cross tabulation to identify the existing combinations between the soil classes of each physiographic unit. Based on these combinations, rules were established to select typical areas of occurrence of each soil type in order to train a decision tree model to predict the occurrence of soil classes. The model was trained using the Weka software and was validated with a set of georeferenced soil profiles. Disaggregation enables the individualization and spatialization of soil classes and is useful in producing detailed soil maps.
Author Silva, Elisângela Benedet da
Bonfatti, Benito Roberto
Campos, Alcinei Ribeiro
Machado, Israel Rosa
Giasson, Elvio
Costa, José Janderson Ferreira
Bacic, Ivan Luiz Zilli
AuthorAffiliation Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina
Universidade Federal do Rio Grande do Sul
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Keywords predição de classes de solos
árvores de decisão
decision trees
digital soil mapping
pedology
mapeamento digital de solos
pedologia
soil class prediction
Language English
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SubjectTerms AGRICULTURE, DAIRY & ANIMAL SCIENCE
AGRICULTURE, MULTIDISCIPLINARY
decision trees
digital soil mapping
pedology
soil class prediction
Title Individualization of soil classes by disaggregation of physiographic map polygons
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