Title
Prediction of Common Surface Soil Properties Based on Vis-NIR Airborne and Simulated EnMAP Imaging Spectroscopy Data: Prediction Accuracy and Influence of Spatial Resolution.
Abstract
With the upcoming availability of the next generation of high quality orbiting hyperspectral sensors, a major step toward improved regional soil mapping and monitoring and delivery of quantitative soil maps is expected. This study focuses on the determination of the prediction accuracy of spectral models for the mapping of common soil properties based on upcoming EnMAP (Environmental Mapping and Analysis Program) satellite data using semi-operational soil models. Iron oxide (Fe-d), clay, and soil organic carbon (SOC) content are predicted in test areas in Spain and Luxembourg based on a semi-automatic Partial-Least-Square (PLS) regression approach using airborne hyperspectral, simulated EnMAP, and soil chemical datasets. A variance contribution analysis, accounting for errors in the dependent variables, is used alongside classical error measurements. Results show that EnMAP allows predicting iron oxide, clay, and SOC with an R-2 between 0.53 and 0.67 compared to Hyperspectral Mapper (HyMap)/Airborne Hyperspectral System (AHS) imagery with an R-2 between 0.64 and 0.74. Although a slight decrease in soil prediction accuracy is observed at the spaceborne scale compared to the airborne scale, the decrease in accuracy is still reasonable. Furthermore, spatial distribution is coherent between the HyMap/AHS mapping and simulated EnMAP mapping as shown with a spatial structure analysis with a systematically lower semivariance at the EnMAP scale.
Year
DOI
Venue
2016
10.3390/rs8070613
REMOTE SENSING
Keywords
Field
DocType
imaging spectroscopy,airborne,satellite,simulated EnMAP,soil properties,Partial-Least-Square regression,variogram,autoPLSR
Soil science,Variogram,Semivariance,Remote sensing,Partial least squares regression,Hyperspectral imaging,Soil carbon,Soil map,Geology,EnMAP,HyMap
Journal
Volume
Issue
Citations 
8
7
1
PageRank 
References 
Authors
0.35
0
5
Name
Order
Citations
PageRank
Andreas Steinberg110.35
Sabine Chabrillat28112.53
Antoine Stevens3151.88
Karl Segl431539.58
saskia foerster5617.01