Digital mapping of soil properties in the West of Honduras, Central America.https://doi.org/10.7910/DVN/QVXA7UDa Silva, MayesseMonserrate, FredyValencia, JeffersonQuintero, MarcelaJarvis, AndyHarvard Dataverse2016-10-042019-07-08T16:23:31ZDigital soil property maps were generated at 30 meters resolution for the West of Honduras in order to develop the AGRI v.1 tool (Monserrate et al., 2016). AGRI (from its Spanish words AGua para RIego) is a tool that combines information about climate, relief, soils, land cover, and hydrology to identify suitable water sources for implementing small irrigation projects. The soil properties mapped were sand (%), silt (%), clay (%), texture class, field capacity (v/v), wilting point (v/v), water holding capacity (v/v), and curve numbers. A database of 1887 points from González et al. (2008) were used to generate the maps of sand, silt, and clay. This database was also used to determine field capacity, wilting point and water-holding capacity for each point by applying pedotransfer functions according to Saxton & Rawls (2006). A regression kriging approach was performed by combining 80% of point data with the terrain attributes aspect, mid-slope position, normalized height, plan and profile curvature, slope and topographic wetness index generated from a digital elevation model SRTM of 30 meters resolution. The combination of sand, silt, and clay maps resulted on texture class map. The curve number was mapped using the texture and land cover maps according to Soil Conservation Service of the United States of America (USDA-SCS, 1985). The maps performance was evaluated by the normalized root mean square error (RMSEn) expressed in percentage and using 20% of data point not used for mapping. Clay, sand, silt, field capacity, water holding capacity and wilting point presented error of 16%, 17%, 13%, 19%, 10% and 18% respectively.Earth and Environmental SciencesSoil textureWilting pointField capacityWater holding capacityHondurasDEMTopographic Wetness Index (TWI)Curve numbersDry corridorLatin America and the CaribbeanSoilsGonzalez, J.P., Jarvis, A., Cook, S., Oberthur, T., Rincon-Romero, M., Bagnell, J., Bernardine, D. 2008. Digital Soil Mapping of Soil Properties in Honduras Using Readily Available Biophysical Datasets and Gaussian Processes, in: Hartemink, A.E., McBratney, A., Mendonça-Santos, M. de L. (Eds.), Digital Soil Mapping with Limited Data. Springer Netherlands, Dordrecht, pp. 367–380., doi, 10.1007/978-1-4020-8592-5, http://dx.doi.org/10.1007/978-1-4020-8592-5Monserrate, F., Valencia, J., Quintero, M., Hyman, G., Da Silva, M., Coppus, R., Bautista, O., Rivera, O., León, J., Manueles, A. 2016. Aumentando la resiliencia climática en el occidente de Honduras: explorando fuentes de agua para pequeños productores rurales. United States Agency for International Development (USAID); Centro Internacional de Agricultura Tropical (CIAT); Escuela Agrícola Panamericana Zamorano (EAP Zamorano). Cali, CO. 44 p., handle, 10568/73454, http://hdl.handle.net/10568/734542016Garcia, Carolina2016-08-26Geospatial DataSoil DataRaster maps for using in a GIS environmentHondurasCopanOcotepequeHondurasHondurasLempiraHondurasSanta BárbaraHondurasIntibucáHondurasLa PazHondurasCortesComayaguaHondurasHondurasFrancisco MorazánHondurasValleCholutecaHonduras<a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br /> These data and documents are licensed under a <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank"> Creative Commons Attribution 4.0 International license.</a> You may copy, distribute and transmit the data as long as you acknowledge the source through proper <a href="http://best-practices.dataverse.org/data-citation/" target="_blank">data citation</a>.