<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"><identifier identifierType="DOI">10.7910/DVN/WKAOIL</identifier><creators><creator><creatorName nameType="Personal">Da Silva, Mayesse</creatorName><givenName>Mayesse</givenName><familyName>Da Silva</familyName><nameIdentifier nameIdentifierScheme="ORCID">0000-0002-3734-9586</nameIdentifier><affiliation>International Center for Tropical Agriculture - CIAT</affiliation></creator><creator><creatorName nameType="Personal">Rodriguez, Maryory</creatorName><givenName>Maryory</givenName><familyName>Rodriguez</familyName><nameIdentifier nameIdentifierScheme="ORCID">0000-0002-8119-3662</nameIdentifier><affiliation>International Center for Tropical Agriculture - CIAT</affiliation></creator><creator><creatorName nameType="Personal">Majin, Marvin</creatorName><givenName>Marvin</givenName><familyName>Majin</familyName><affiliation>International Center for Tropical Agriculture - CIAT</affiliation></creator><creator><creatorName nameType="Personal">Chirinda, Ngonidzashe</creatorName><givenName>Ngonidzashe</givenName><familyName>Chirinda</familyName><nameIdentifier nameIdentifierScheme="ORCID">0000-0002-4213-6294</nameIdentifier><affiliation>International Center for Tropical Agriculture - CIAT</affiliation></creator></creators><titles><title>Textural classification of soils in rice-growing areas in Colombia</title><title titleType="AlternativeTitle">Clasificación textural de los suelos en las áreas arroceras de Colombia</title></titles><publisher>Harvard Dataverse</publisher><publicationYear>2015</publicationYear><subjects><subject>Earth and Environmental Sciences</subject><subject schemeURI="http://aims.fao.org/aos/agrovoc/c_7199" subjectScheme="AGROVOC">Soil texture</subject><subject>Digital soil mapping</subject><subject schemeURI="http://aims.fao.org/aos/agrovoc/c_1344" subjectScheme="AGROVOC">Cartography</subject><subject subjectScheme="CIAT Region">Latin America and the Caribbean</subject><subject subjectScheme="CIAT Research Area">Soils</subject><subject>Digital soil mapping</subject></subjects><contributors><contributor contributorType="ContactPerson"><contributorName nameType="Organizational">CIAT Data and Research Methods</contributorName><affiliation>International Center for Tropical Agriculture - CIAT</affiliation></contributor><contributor contributorType="Producer"><contributorName nameType="Organizational">International Center for Tropical Agriculture</contributorName></contributor><contributor contributorType="Distributor"><contributorName nameType="Organizational">International Center for Tropical Agriculture</contributorName></contributor></contributors><dates><date dateType="Created">2015-05</date><date dateType="Submitted">2015-11-19</date><date dateType="Updated">2019-07-03</date><date dateType="Collected">2015-05/2015-05</date></dates><resourceType resourceTypeGeneral="Dataset">Geospatial Data</resourceType><sizes><size>309515</size><size>39993242</size><size>1160129286</size><size>1593</size><size>12862102</size><size>4809</size><size>466</size></sizes><formats><format>image/jpeg</format><format>application/zip</format><format>image/tiff</format><format>text/xml</format><format>image/tiff</format><format>application/octet-stream</format><format>text/xml</format></formats><version>1.3</version><rightsList><rights rightsURI="info:eu-repo/semantics/openAccess"/><rights/></rightsList><descriptions><description descriptionType="Abstract">&lt;strong>English&lt;/strong>&#xd;
&lt;p>&#xd;
The Digital Soil Mapping (DSM) approach was used to generate maps of the soil texture (sand, silt, and clay) in Colombia, based on the soil geomorphology. The soil units were differentiated by land shapes using a STRM 90-m DEM, and stratified by geopedological units from the Agustín Codazzi Geographic Institute (IGAC). The digital maps of soil texture were generated using the fuzzy logic approach, which enabled determining statistically the value limits of percent-slope classes, moisture index and standardized height on each of the soil units. Data inherited from IGAC’s soil profiles were used to determine the gauge values for the mapping model (80% of total data) for sand, stilt, and clay, as well as to validate (20% of total data) based on the DSM approach. The root mean squared error (RMSE) was 21, 12, and 15% for sand, stilt, and clay, respectively, and these values are the same as the standard deviation of the field data. The map of texture classes was generated with the information on sand, stilt, and clay.&#xd;
&lt;/p>&#xd;
&lt;strong>Español&lt;/strong>&#xd;
&lt;p>&#xd;
Se usó el enfoque de Mapeo Digital del Suelo (MDS) para generar los mapas de textura del suelo (arena, limo y arcilla) para Colombia basado en la geomorfología del suelo. Las unidades del suelo fueron diferenciadas por formas del terreno usando un DEM SRTM de 90 m de resolución y además, estratificadas por unidades geopedológicas del Instituto Geográfico Agustín Codazzi (IGAC). Los mapas digitales de textura del suelo fueron generados usando el enfoque de lógica difusa, donde se determinaron estadísticamente los límites de los valores de las clases de porcentaje de pendiente, índice de humedad y altura normalizada en cada una de las unidades de suelo. Se usaron datos heredados de perfiles de suelos de IGAC, para determinar los valores de calibración del modelo de mapeo (80% del total de los datos) para arena, limo y arcilla, así como para validar (20% del total de los datos) según el enfoque de MDS. La raíz del error medio cuadrado (RMSE) fue 21, 12 y 15 % para arena, limo y arcilla respectivamente, valores que son iguales a la desviación estándar de los datos de campo. Con la información de arena, arcilla y limo se generó el mapa de clases de textura.&#xd;
&lt;/p></description></descriptions><geoLocations/><fundingReferences><fundingReference><funderName>Climate and Clean Air Coalition (CCAC) to Reduce Short-Lived Climate Pollutants</funderName><awardNumber>Project 1-b/c (01554)</awardNumber></fundingReference></fundingReferences></resource>