TY  - JOUR
A1  - Omorogie, Martins O.
A1  - Babalola, Jonathan Oyebamiji
A1  - Unuabonah, Emmanuel I.
A1  - Song, Weiguo
A1  - Gong, Jian Ru
T1  - Efficient chromium abstraction from aqueous solution using a low-cost biosorbent: Nauclea diderrichii seed biomass waste
JF  - Journal of Saudi Chemical Society
N2  - Toxic Cr(III) which poses environmental hazard to flora and fauna was efficiently abstracted by low-cost Nauclea diderrichii seed biomass (NDS) with good sequestral capacity for this metal was investigated in this study. The NDS surface analyses showed that it has a specific surface area of 5.36 m(2)/g and pHpzc of 4.90. Thermogravimetric analysis of NDS showed three consecutive weight losses from 50-200 degrees C (ca. 5%), 200-400 C (ca. 35%), >400 degrees C (ca. 10%), corresponding to external water molecules, structural water molecules and heat induced condensation reactions respectively. Differential thermogram of NDS presented a large endothermic peak between 20-510 degrees C suggesting bond breakage and dissociation with the ultimate release of small molecules. The experimental data showed kinetically fast biosorption with increased initial Cr(III) concentrations, indicating the role of external mass transfer mechanism as the rate controlling mechanism in this adsorption process. The Langmuir biosorption capacity of NDS was 483.81 mg/g. The use of the corrected Akaike Information Criterion tool for ranking equilibrium models suggested that the Freundlich model best described the experimental data, which is an indication of the heterogeneous nature of the active sites on the surface of NDS. N. diderrichii seed biomass is an easily sourced, cheap and environmental friendly biosorbent which will serve as a good and cost effective alternative to activated carbon for the treatment of polluted water and industrial effluents. (C) 2012 King Saud University. Production and hosting by Elsevier B.V. All rights reserved.
KW  - Biomass
KW  - Equilibrium
KW  - External mass transfer
KW  - Kinetics
KW  - Adsorption
KW  - Water
Y1  - 2016
U6  - https://doi.org/10.1016/j.jscs.2012.09.017
SN  - 1319-6103
SN  - 2212-4640
VL  - 20
SP  - 49
EP  - 57
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Malinowski, Radostaw
A1  - Höfle, Bernhard
A1  - Koenig, Kristina
A1  - Groom, Geoff
A1  - Schwanghart, Wolfgang
A1  - Heckrath, Goswin
T1  - Local-scale flood mapping on vegetated floodplains from radiometrically calibrated airborne LiDAR data
JF  - ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing
N2  - Knowledge about the magnitude of localised flooding of riverine areas is crucial for appropriate land management and administration at regional and local levels. However, detection and delineation of localised flooding with remote sensing techniques are often hampered on floodplains by the presence of herbaceous vegetation. To address this problem, this study presents the application of full waveform airborne laser scanning (ALS) data for detection of floodwater extent. In general, water surfaces are characterised by low values of backscattered energy due to water absorption of the infrared laser shots, but the exact strength of the recorded laser pulse depends on the area covered by the targets located within a laser pulse footprint area. To account for this we analysed the physical quantity of radio metrically calibrated ALS data, the backscattering coefficient, in relation to water and vegetation coverage within a single laser footprint. The results showed that the backscatter was negatively correlated to water coverage, and that of the three distinguished classes of water coverage (low, medium, and high) only the class with the largest extent of water cover (>70%) had relatively distinct characteristics that can be used for classification of water surfaces. Following the laser footprint analysis, three classifiers, namely AdaBoost with Decision Tree, Naive Bayes and Random Forest, were utilised to classify laser points into flooded and non-flooded classes and to derive the map of flooding extent. The performance of the classifiers is highly dependent on the set of laser points features used. Best performance was achieved by combining radiometric and geometric laser point features. The accuracy of flooding maps based solely on radiometric features resulted in overall accuracies of up to 70% and was limited due to the overlap of the backscattering coefficient values between water and other land cover classes. Our point-based classification methods assure a high mapping accuracy (similar to 89%) and demonstrate the potential of using full-waveform ALS data to detect water surfaces on floodplain areas with limited water surface exposition through the vegetation canopy. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
KW  - ALS
KW  - LiDAR
KW  - Point cloud
KW  - Inundation
KW  - Full-waveform
KW  - Water
Y1  - 2016
U6  - https://doi.org/10.1016/j.isprsjprs.2016.06.009
SN  - 0924-2716
SN  - 1872-8235
VL  - 119
SP  - 267
EP  - 279
PB  - Elsevier
CY  - Amsterdam
ER  -