Bibliographic citations
This is an automatically generated citacion. Modify it if you see fit
Mestanza, C., (2019). Levantamiento de suelos con la técnica de mapeo digital, en San Mateo de Otao, Huarochirí [Tesis, Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/4090
Mestanza, C., Levantamiento de suelos con la técnica de mapeo digital, en San Mateo de Otao, Huarochirí [Tesis]. : Universidad Nacional Agraria La Molina; 2019. https://hdl.handle.net/20.500.12996/4090
@mastersthesis{renati/248360,
title = "Levantamiento de suelos con la técnica de mapeo digital, en San Mateo de Otao, Huarochirí",
author = "Mestanza Novoa, Carlos Julián",
publisher = "Universidad Nacional Agraria La Molina",
year = "2019"
}
Title: Levantamiento de suelos con la técnica de mapeo digital, en San Mateo de Otao, Huarochirí
Authors(s): Mestanza Novoa, Carlos Julián
Advisor(s): Nazario Ríos, Julio César
Keywords: Suelo; Reconocimiento aéreo; Cartografía del uso de la tierra; Fotogrametría; Sistemas de información geográfica; Evaluación; Zona de montaña; Análisis de imágenes; Mapas; Métodos; Perú; Mapeo digital de suelos; Levantamiento de suelos; San mateo de Otao (dist); Huarochiri (prov); Región Lima
OCDE field: https://purl.org/pe-repo/ocde/ford#4.01.04
Issue Date: 2019
Institution: Universidad Nacional Agraria La Molina
Abstract: En el Perú, la producción de mapas de suelo se realiza utilizando el modelo de factores de formación de suelo. Los límites de las unidades cartográficas se establecen intersectando los mapas de fisiografía, geología y zonas de vida, que representan los factores relieve, material parental, tiempo y clima. Con el apogeo de la era digital iniciaron los métodos numéricos para inferir y analizar la distribución espacial de los suelos. El uso de la estadística para modelar los factores de formación de suelo se denomina mapeo digital de suelos (MDS). La presente investigación busca comprobar esta nueva metodología estableciendo un mapa de suelos del distrito de San Mateo de Otao, provincia de Huarochirí (Perú). Para ello se establecieron tres objetivos específicos: evaluar la incertidumbre del mapa obtenido, reconocer la relación de las covariables ambientales y los suelos, y comparar el método tradicional de mapeo y el digital. Como datos de partida se utilizó información cualitativa y cuantitativa, derivada del modelo digital de elevaciones, imágenes Landsat 8, información climática de WorldClim, mapa geológico y mapa ecológico del Perú para planificar el muestreo utilizando el enfoque geopedológico. Se evaluaron y clasificaron sesenta y cuatro (64) perfiles hasta nivel de subgrupo con la doceava edición de las claves del Soil taxonomy. Se modelaron taxones de suelo utilizando el método naive bayes, así como veinte covariables representando el clima, organismos, relieve y material parental. Como resultado se obtuvo un mapa de unidades taxonómicas, con los subgrupos Fluventic Haplocambids, Lithic Haplocambids, Lithic Torriorthents, Sodic Haplocambids, Typic Haplocambids, y Typic Torriorthents. Las medidas de incertidumbre, exactitud global e índice Kappa fueron 0.77 y 0.59. El factor relieve fue el más influyente en la predicción de los taxones de suelo. La comparación del mapa de unidades cartográficas (método tradicional) y el de unidades taxonómicas (mapeo digital) demuestra que existe una estrecha relación entre ambos, pueden utilizarse de manera conjunta para actualizar las unidades cartográficas, pero no es posible establecer cuál de los dos métodos es mejor.
In Peru, the production of soil maps is done using the model of soil formation factors. The boundaries of the cartographic units are established by intersecting the maps of physiography, geology and life zones, which represent relief, parent material, time and climate. With the heyday of the digital era, they began using numerical methods to infer and analyze the spatial distribution of soils. The use of statistics to model soil formation factors is called digital soil mapping (DSM). The present investigation seeks to verify this new methodology establishing a soil map of the district of San Mateo de Otao, province of Huarochirí (Peru). To this end, three objectives were established: evaluate the uncertainty of the map obtained, recognize the relationship between environmental covariates and the soils, and compare the traditional method of mapping and digital. As starting data, qualitative and quantitative information was used, derived from the digital elevation model, Landsat 8 images, WorldClim climate information, geological map and ecological map of Peru to plan the sampling using the geopedologic approach. Sixty-four (64) profiles were evaluated and classified up to subgroup level with the twelfth edition of keys to soil taxonomy. Soil taxa were modeled using the naive bayes method, as well as twenty covariates representing climate, organisms, relief and parent material. As a result, a map of taxonomic units was obtained, with the subgroups Fluventic Haplocambids, Lithic Haplocambids, Lithic Torriorthents, Sodic Haplocambids, Typic Haplocambids, and Typic Torriorthents. The measures of uncertainty, global accuracy and Kappa index were 0.77 and 0.59. The relief was the most influential factor in the prediction of soil taxa. The comparison of the map of cartographic units (traditional method) and that of taxonomic units (digital mapping) shows that there is a close relationship between both, can be used together to update cartographic units, but it is not possible to establish which of the two methods is better
In Peru, the production of soil maps is done using the model of soil formation factors. The boundaries of the cartographic units are established by intersecting the maps of physiography, geology and life zones, which represent relief, parent material, time and climate. With the heyday of the digital era, they began using numerical methods to infer and analyze the spatial distribution of soils. The use of statistics to model soil formation factors is called digital soil mapping (DSM). The present investigation seeks to verify this new methodology establishing a soil map of the district of San Mateo de Otao, province of Huarochirí (Peru). To this end, three objectives were established: evaluate the uncertainty of the map obtained, recognize the relationship between environmental covariates and the soils, and compare the traditional method of mapping and digital. As starting data, qualitative and quantitative information was used, derived from the digital elevation model, Landsat 8 images, WorldClim climate information, geological map and ecological map of Peru to plan the sampling using the geopedologic approach. Sixty-four (64) profiles were evaluated and classified up to subgroup level with the twelfth edition of keys to soil taxonomy. Soil taxa were modeled using the naive bayes method, as well as twenty covariates representing climate, organisms, relief and parent material. As a result, a map of taxonomic units was obtained, with the subgroups Fluventic Haplocambids, Lithic Haplocambids, Lithic Torriorthents, Sodic Haplocambids, Typic Haplocambids, and Typic Torriorthents. The measures of uncertainty, global accuracy and Kappa index were 0.77 and 0.59. The relief was the most influential factor in the prediction of soil taxa. The comparison of the map of cartographic units (traditional method) and that of taxonomic units (digital mapping) shows that there is a close relationship between both, can be used together to update cartographic units, but it is not possible to establish which of the two methods is better
Link to repository: https://hdl.handle.net/20.500.12996/4090
Note: Universidad Nacional Agraria La Molina. Escuela de Posgrado. Maestría en Suelos
Discipline: Suelos
Grade or title grantor: Universidad Nacional Agraria La Molina. Escuela de Posgrado
Grade or title: Magister Scientiae - Suelos
Register date: 3-Sep-2019
This item is licensed under a Creative Commons License