Journal of Food, Agriculture and Environment




Vol 10, Issue 2,2012
Online ISSN: 1459-0263
Print ISSN: 1459-0255


The remote sensing assessment of potential productivity of a field with soil spatial variability


Author(s):

Rafał Pudełko 1, Jacek Niedźwiecki 2, Guillaume Debaene 2*, Janusz Igras 3, Krzysztof Kubsik 4

Recieved Date: 2012-01-30, Accepted Date: 2012-05-03

Abstract:

This paper presents a method of mapping the potential productivity of a field located at the Experimental Station of Baborówko, Poland (52.58° N; 16.64° E) and belonging to the Institute of Soil Sciences and Plant Cultivation, State Research Institute (IUNG-PIB). This field is characterised with a significant spatial variability of soil texture. The method used in the research is based on the combined analyses of different types of data derived from remote sensing measurements. The study used aerial photos and satellite images, measurements of electrical conductivity (EC) of soil, and yield maps. Data were compiled by means of geographic information systems (GIS) with geo-processing tools through the use of geostatistical analysis. The results have revealed different potential productivity zones within the tested field. Established methodology made it possible to generalise the result of geoprocessing and mapping of potential productivity, with resolution corresponding to agricultural practices. Moreover, the experimental field has soil conditions characteristic of the Western part of Poland. For this reason, the results obtained can be applied in practice. The correlations of all types of remote sensing data were established. The most significant of them were the relations yield–soil electrical conductivity and yield– VARI indices. The NDVI map prepared, based on the satellite image, showed the lowest correlation to the other maps. The likely cause is inadequate data for image acquisition, photographed crop (rape) and too low resolution of image. 

Keywords:

Soil spatial variability, correlation coefficient of spatial distribution, remote sensing, precision farming


Journal: Journal of Food, Agriculture and Environment
Year: 2012
Volume: 10
Issue: 2
Category: Environment
Pages: 790-793


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