Data fusion techniques for delineation of site-specific management zones in a field in UK

Data fusion techniques for delineation of site-specific management zones in a field in UK Fusion of different data layers, such as data from soil analysis and proximal soil sensing, is essential to improve assessment of spatial variation in soil and yield. On-line visible and near infrared (Vis–NIR) spectroscopy have been proved to provide high resolution information about spatial variability of key soil properties. Multivariate geostatistics tools were successfully implemented for the delineation of management zones (MZs) for precision application of crop inputs. This research was conducted in a 18 ha field to delineate MZs, using a multi-source data set, which consisted of eight laboratory measured soil variables (pH, available phosphorus (P), cation exchange capacity, total nitrogen (TN), total carbon (TC), exchangeable potassium (K), sand, silt) and four on-line collected Vis–NIR spectra-based predicted soil variables (pH, P, K and moisture content). The latter set of data was predicted using the partial least squares regression (PLSR) technique. The quality of the calibration models was evaluated by cross-validation. Multi-collocated cokriging was applied to the soil and spectral data set to produce thematic spatial maps, whereas multi-collocated factor cokriging was applied to delineate MZ. The Vis–NIR predicted K was chosen as the exhaustive variable, because it was the most correlated with the soil variables. A yield map of barley was interpolated by means of the inverse distance weighting method and was then classified into 3 iso-frequency classes (low, medium and high). To assess the productivity potential of the different zones of the field, spatial association between MZs and yield classes was calculated. Results showed that the prediction performance of PLSR calibration models for pH, P, MC and K were of excellent to moderate quality. The geostatistical model revealed good performance. The estimates of the first regionalised factor produced three MZs of equal size in the studied field. The loading coefficients for TC, pH and TN of the first factor were highest and positive. This means that the first factor can be assumed as a synthetic indicator of soil fertility. The overall spatial association between the yield classes and MZs was about 40 %, which reveals that more than 50 % of the yield variation can be attributed to more dynamic factors than soil parameters, such as agro-meteorological conditions, plant diseases and nutrition stresses. Nevertheless, multivariate geostatistics proved to be an effective approach for site-specific management of agricultural fields. Precision Agriculture Springer Journals

Data fusion techniques for delineation of site-specific management zones in a field in UK

Loading next page...
Springer US
Copyright © 2015 by Springer Science+Business Media New York
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
Publisher site
See Article on Publisher Site


  • A comparison of geostatistical methodologies used to estimate snow water equivalent
    Carroll, SS; Cressie, N
  • Study of spatial relationships among some soil physico-chemical properties of a field in central Italy using multivariate geostatistics
    Castrignanò, A; Giugliarini, L; Risaliti, R; Martinelli, N
  • Use of EMI, gamma-ray emission and GPS height as multi-sensor data for soil characterisation
    Castrignanò, A; Wong, MTF; Stelluti, M; Benedetto, D; Sollitto, D

You’re reading a free preview. Subscribe to read the entire article.

DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches


Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.



billed annually
Start Free Trial

14-day Free Trial