Sensor data fusion to predict multiple soil properties
- 24 August 2012
- journal article
- research article
- Published by Springer Nature in Precision Agriculture
- Vol. 13 (6) , 628-645
Abstract
No abstract availableKeywords
This publication has 16 references indexed in Scilit:
- Partial least squares regression as an alternative to current regression methods used in ecologyOikos, 2009
- Identifying optimal spectral bands to assess soil properties with VNIR radiometry in semi-arid soilsGeoderma, 2008
- ParLeS: Software for chemometric analysis of spectroscopic dataChemometrics and Intelligent Laboratory Systems, 2008
- Validation requirements for diffuse reflectance soil characterization models with a case study of VNIR soil C prediction in MontanaGeoderma, 2005
- Relating apparent electrical conductivity to soil properties across the north-central USAComputers and Electronics in Agriculture, 2005
- Effectiveness of spectroscopy in identification of swelling indicator clay mineralsInternational Journal of Remote Sensing, 2004
- Robust methods for partial least squares regressionJournal of Chemometrics, 2003
- Multi-sensor data fusion for supervised land-cover classification using Bayesian and geostatistical techniquesGeosciences Journal, 2002
- The efficiency of various approaches to obtaining estimates of soil hydraulic propertiesGeoderma, 2002
- Estimating average rootzone salinity from electromagnetic induction (EM-38) measurementsSoil Research, 1990