Detection of hydrocarbons in clay soils: A laboratory experiment using spectroscopy in the mid- and thermal infrared
Meijde, M. van der; Knox, N. ; Cundill, S.L. ; Noomen, M.F. ; Werff, H.M.A. van der; Hecker, C. - \ 2013
International Journal of applied Earth Observation and Geoinformation 23 (2013). - ISSN 0303-2434 - p. 384 - 388.
pipeline leakage - natural-gas - reflectance - airborne - spectrometer - regression
Remote sensing has been used for direct and indirect detection of hydrocarbons. Most studies so far focused on indirect detection in vegetated areas. We investigated in this research the possibility of detecting hydrocarbons in bare soil through spectral analysis of laboratory samples in the short wave and thermal infrared regions. Soil/oil mixtures were spectrally measured in the laboratory. Analysis of spectra showed development of hydrocarbon absorption features as soils became progressively more contaminated. The future application of these results airborne seems to be a challenge as present and future sensors only cover the diagnostic regions to a limited extent
Differentiation of plant age in grasses using remote sensing
Knox, N. ; Skidmore, A.K. ; Werff, H.M.A. van der; Groen, T.A. ; Boer, W.F. de; Prins, H.H.T. ; Kohi, E. ; Peel, M. - \ 2013
International Journal of applied Earth Observation and Geoinformation 24 (2013)10. - ISSN 0303-2434 - p. 54 - 62.
difference water index - monitoring vegetation - nitrogen concentration - imaging spectroscopy - hyperspectral data - boreal regions - time-series - green-up - phenology - reflectance
Phenological or plant age classification across a landscape allows for examination of micro-topographical effects on plant growth, improvement in the accuracy of species discrimination, and will improve our understanding of the spatial variation in plant growth. In this paper six vegetation indices used in phenological studies (including the newly proposed PhIX index) were analysed for their ability to statistically differentiate grasses of different ages in the sequence of their development. Spectra of grasses of different ages were collected from a greenhouse study. These were used to determine if NDVI, NDWI, CAI, EVI, EVI2 and the newly proposed PhIX index could sequentially discriminate grasses of different ages, and subsequently classify grasses into their respective age category. The PhIX index was defined as: (An VNIR+ log(An SWIR2))/(An VNIR- log(An SWIR2)), where An VNIRand An SWIR2are the respective nor- malised areas under the continuum removed reflectance curve within the VNIR (500-800 nm) and SWIR2 (2000-2210 nm) regions. The PhIX index was found to produce the highest phenological classification accuracy (Overall Accuracy: 79%, and Kappa Accuracy: 75%) and similar to the NDVI, EVI and EVI2 indices it statistically sequentially separates out the developmental age classes. Discrimination between seedling and dormant age classes and the adult and flowering classes was problematic for most of the tested indices. Combining information from the visible near infrared (VNIR) and shortwave infrared region (SWIR) region into a single phenological index captures the phenological changes associated with plant pigments and the ligno-cellulose absorption feature, providing a robust method to discriminate the age classes of grasses. This work provides a valuable contribution into mapping spatial variation and monitoring plant growth across savanna and grassland ecosystems.
Dry season mapping of savanna forage quality, using the hyperspectral Carnegie
Knox, N. ; Skidmore, A.K. ; Prins, H.H.T. ; Asner, P. ; Werff, H.M.A. van der; Boer, W.F. de; Waal, C. van der; Knegt, H.J. de; Kohi, E. ; Slotow, R. ; Grant, R.C. - \ 2011
Remote Sensing of Environment 115 (2011)6. - ISSN 0034-4257 - p. 1478 - 1488.
kruger-national-park - african savannas - neural-networks - south-africa - absorption features - leaf biochemistry - mineral-nutrition - grass quality - nitrogen - reflectance
Forage quality within an African savanna depends upon limiting nutrients (nitrogen and phosphorus) and nutrients that constrain the intake rates (non-digestible fibre) of herbivores. These forage quality nutrients are particularly crucial in the dry season when concentrations of limiting nutrients decline and non-digestible fibres increase. Using artificial neural networks we test the ability of a new imaging spectrometer (CAO Alpha sensor), both alone and in combination with ancillary data, to map quantities of grass forage nutrients in the early dry season within an African savanna. Respectively 65%, 57% and 41%, of the variance in fibre, phosphorus and nitrogen concentrations were explained. We found that all grass forage nutrients show response to fire and soil. Principal component analysis, not only reduced image dimensionality, but was a useful method for removing cross-track illumination effects in the CAO imagery. To further improve the mapping of forage nutrients in the dry season we suggest that spectra within the shortwave infrared (SWIR) region, or additional relevant ancillary data, are required.
|Remote sensing of onshore hydrocarbon seepage: Problems and solutions
Werff, H.M.A. van der; Noomen, M.F. ; Meijde, M. van der; Meer, F.D. van der - \ 2007
Geological Society Special Publication 283 (2007). - ISSN 0305-8719 - p. 125 - 133.