A pedometric technique to delimitate soil-specific zones at field scale
Autor: | Mariano Córdoba, Mónica Balzarini, José Luis Costa, Mauricio Castro-Franco |
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Rok vydání: | 2018 |
Předmět: |
Soil map
ARGENTINA 010504 meteorology & atmospheric sciences RANDOM FOREST Soil Science Soil classification Soil science Terrain 04 agricultural and veterinary sciences 01 natural sciences Soil survey PRECISION AGRICULTURE CIENCIAS AGRÍCOLAS DIGITAL SOIL MAPPING Digital soil mapping 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Environmental science Precision agriculture SPATIAL PRINCIPAL COMPONENTS Agricultura Silvicultura y Pesca Scale (map) Digital elevation model Ciencias del Suelo 0105 earth and related environmental sciences |
Zdroj: | Geoderma. 322:101-111 |
ISSN: | 0016-7061 |
DOI: | 10.1016/j.geoderma.2018.02.034 |
Popis: | Delimitation of soil types within a farm field is key for site-specific crop management. An alternative to this, is to develop pedometric techniques that allow an efficient combination of soil survey information and high-resolution terrain attribute data. The aim of this study was to present and evaluate a pedometric technique to delimit soil-specific zones at field scale by coupled Random forest, fuzzy k-means clustering and spatial principal components algorithms (RF-KM-sPCA) and by using information from soil surveys and terrain attributes derived from a digital elevation model. The protocol involves three-steps: 1) automatic classification of small (20x20m) spatial units (SU) using the knowledge of the soil map units present in the farm landscape, 2) aggregation of SUM at farm scale and 3) validation of soil-specific zones. For the first step, we used the random forest algorithm with 10 terrain attributes. For the second step, KM-sPCA algorithms were used to cluster within field SU accounting for autocorrelation. For the third step, apparent soil electrical conductivity and yield maps was used to validate the delimitation of soil-specific zones. This technique produced more contiguous zones than other cluster methods which do not use spatiality. Six farm fields with highly differences in soils were partitioned by the proposed pedometric strategy. Apparent soil electrical conductivity and yield maps present significant differences among zones in all experimental fields. This analytic strategy, based in easy-to-obtain data, could be used to improve precision agricultural managements. Fil: Castro Franco, Mauricio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Barrow; Argentina Fil: Córdoba, Mariano. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Balzarini, Monica Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba; Argentina Fil: Costa, José Luis. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina |
Databáze: | OpenAIRE |
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