Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
1 file | 1.07 MB
  1. Search results
  2. Estimating grondwater nutrients using...

Estimating grondwater nutrients using hyperspectral satellite imagery in the Flemish Meuse valley

Cornelis Stal (UGent) , Philippe De Maeyer (UGent) , An De Schrijver (UGent) , Mieke Paelinck, Rudi Goossens (UGent) and Alain De Wulf (UGent)
(2016) IEEE International Symposium on Geoscience and Remote Sensing IGARSS. p.3114-3117
Author
Organization
Abstract
In order to improve European biodiversity, natural habitats need to be restored and improved within a large European network of protected areas (Natura 2000). Therefore, agricultural land often needs to be converted to nature. Lowering soil nitrogen and phosphorus levels appears to be a necessary prerequisite for a successful restoration. To select which agricultural fields are most suitable for conversion to natural habitats, large and expensive soil monitoring campaigns are actually executed in situ. n this paper, it is demonstrated that hyperspectral satellite imagery, acquired by the EO-1 Hyperion sensor, has a large potential to substitute the current method. This is demonstrated in a qualitative regional study, where ground water analyses are used to derive the correlation between nutrient concentrations and spectral bands. Additionally, a pair-wise index is calculated for each band and compared with in-situ values. For this study, it is stated that the concentration of nutrients can be explained by a linear model using at least one or two spectral bands, with R-2 correlations between 0.4 and 0.7.
Keywords
SOIL-MOISTURE, SPECTROSCOPY, FRACTIONS, Hyperspectral, satellite remote sensing, soil nutrients, correlation, indexing

Downloads

  • Download
    (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 1.07 MB

Citation

Please use this url to cite or link to this publication:

Chicago
Stal, Cornelis, Philippe De Maeyer, An De Schrijver, Mieke Paelinck, Rudi Goossens, and Alain De Wulf. 2016. “Estimating Grondwater Nutrients Using Hyperspectral Satellite Imagery in the Flemish Meuse Valley.” In IEEE International Symposium on Geoscience and Remote Sensing IGARSS, 3114–3117. New York, NY, USA: IEEE.
APA
Stal, C., De Maeyer, P., De Schrijver, A., Paelinck, M., Goossens, R., & De Wulf, A. (2016). Estimating grondwater nutrients using hyperspectral satellite imagery in the Flemish Meuse valley. IEEE International Symposium on Geoscience and Remote Sensing IGARSS (pp. 3114–3117). Presented at the 36th IEEE International Geoscience and Remote Sensing symposium (IGARSS), New York, NY, USA: IEEE.
Vancouver
1.
Stal C, De Maeyer P, De Schrijver A, Paelinck M, Goossens R, De Wulf A. Estimating grondwater nutrients using hyperspectral satellite imagery in the Flemish Meuse valley. IEEE International Symposium on Geoscience and Remote Sensing IGARSS. New York, NY, USA: IEEE; 2016. p. 3114–7.
MLA
Stal, Cornelis, Philippe De Maeyer, An De Schrijver, et al. “Estimating Grondwater Nutrients Using Hyperspectral Satellite Imagery in the Flemish Meuse Valley.” IEEE International Symposium on Geoscience and Remote Sensing IGARSS. New York, NY, USA: IEEE, 2016. 3114–3117. Print.
@inproceedings{8565696,
  abstract     = {In order to improve European biodiversity, natural habitats need to be restored and improved within a large European network of protected areas (Natura 2000). Therefore, agricultural land often needs to be converted to nature. Lowering soil nitrogen and phosphorus levels appears to be a necessary prerequisite for a successful restoration. To select which agricultural fields are most suitable for conversion to natural habitats, large and expensive soil monitoring campaigns are actually executed in situ. n this paper, it is demonstrated that hyperspectral satellite imagery, acquired by the EO-1 Hyperion sensor, has a large potential to substitute the current method. This is demonstrated in a qualitative regional study, where ground water analyses are used to derive the correlation between nutrient concentrations and spectral bands. Additionally, a pair-wise index is calculated for each band and compared with in-situ values. For this study, it is stated that the concentration of nutrients can be explained by a linear model using at least one or two spectral bands, with R-2 correlations between 0.4 and 0.7.},
  author       = {Stal, Cornelis and De Maeyer, Philippe and De Schrijver, An and Paelinck, Mieke and Goossens, Rudi and De Wulf, Alain},
  booktitle    = {IEEE International Symposium on Geoscience and Remote Sensing IGARSS},
  isbn         = {9781509033324},
  issn         = {2153-6996},
  keyword      = {SOIL-MOISTURE,SPECTROSCOPY,FRACTIONS,Hyperspectral,satellite remote sensing,soil nutrients,correlation,indexing},
  language     = {eng},
  location     = {Beijing, PR China},
  pages        = {3114--3117},
  publisher    = {IEEE},
  title        = {Estimating grondwater nutrients using hyperspectral satellite imagery in the Flemish Meuse valley},
  url          = {http://dx.doi.org/10.1109/IGARSS.2016.7729805},
  year         = {2016},
}
Altmetric
View in Altmetric
Web of Science
Times cited: