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 in | Pesquisa agropecuaria brasileira Vol. 54 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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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. |
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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 |
AuthorAffiliation_xml | – name: Universidade Federal do Rio Grande do Sul – name: Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina |
Author_xml | – sequence: 1 givenname: José Janderson Ferreira orcidid: 0000-0002-3891-8111 surname: Costa fullname: Costa, José Janderson Ferreira organization: Universidade Federal do Rio Grande do Sul, Brazil – sequence: 2 givenname: Elvio orcidid: 0000-0003-3659-6873 surname: Giasson fullname: Giasson, Elvio organization: Universidade Federal do Rio Grande do Sul, Brazil – sequence: 3 givenname: Elisângela Benedet da orcidid: 0000-0001-6288-3273 surname: Silva fullname: Silva, Elisângela Benedet da organization: Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina, Brazil – sequence: 4 givenname: Alcinei Ribeiro orcidid: 0000-0003-0070-2101 surname: Campos fullname: Campos, Alcinei Ribeiro organization: Universidade Federal do Rio Grande do Sul, Brazil – sequence: 5 givenname: Israel Rosa orcidid: 0000-0002-3937-374X surname: Machado fullname: Machado, Israel Rosa organization: Universidade Federal do Rio Grande do Sul, Brazil – sequence: 6 givenname: Benito Roberto orcidid: 0000-0002-3730-0723 surname: Bonfatti fullname: Bonfatti, Benito Roberto organization: Universidade Federal do Rio Grande do Sul, Brazil – sequence: 7 givenname: Ivan Luiz Zilli orcidid: 0000-0002-1224-6089 surname: Bacic fullname: Bacic, Ivan Luiz Zilli organization: Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina, Brazil |
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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 |
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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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