ID: 59077
Title: Distribution of Polycyclic Aromatic Hydrocarbons (PAH) in Natuna Coastal Waters.
Author: Sophia L Sagala, Mariska A Kusumaningtyas, Rizki A Adi, Anastasia R T D Kuswardani, Widodo S Pranowo.
Editor: V Subramanian.
Year: 2013
Publisher: Capital Publishing Company.
Source: Centre for Ecological Sciences
Reference: Asian Journal of Water, Environment and Pollution Vol 10(no. 4), pp. 25-31, 2013
Subject: Asian Journal of Water, Environment and Pollution
Keywords: PAH, hydrocarbon, Natuna coastal waters.
Abstract: Surface seawater samples collected in Natuna coastal waters were analysed for 17 parent polycylic aromatic hydrocarbons (PAHs) to get insight their presence for their toxic and carcinogenic impacts. The study was aimed to collect some PAHs preliminary data for baseline data as Natuna coastal waters are susceptible from this continuation possibly arisen from oil spills, shipping activities and mariculture industries. The samples were collected from 10 selected stations along the survey location. The results showed that total PAH concentrations at the sampling sites ranged <0.02-5.84 ?g/L. A higher concentration was found in the northwest of Sedanau Islands with PAH compound dominated by acenaphthene at 4.5 ?g/L. The value is still acceptable for aquatic resources in seawater. Wind and tidal profiles in the location were also presented in the study to get insights on the PAH migration which varied depending on the direction and speed of each profile. It can be concluded that the PAH profile in Natuna coastal water is still low and feasible for aquatic resources and marine environment.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59076
Title: Ecological Impacts and Management of Acid Sulphate Soil: A Review.
Author: Patrick S Michael.
Editor: V Subramanian.
Year: 2013
Publisher: Capital Publishing Company.
Source: Centre for Ecological Sciences
Reference: Asian Journal of Water, Environment and Pollution Vol 10(no. 4), pp. 13-24, 2013
Subject: Asian Journal of Water, Environment and Pollution
Keywords: Acid sulphate soils, ecological impacts, management options.
Abstract: The ecological impacts of acid sulphate soils (ASS) and the management of the impacts are a major concern globally. The reasons being how to minimize the exposure, reduce the residual impacts and make available management options. Despite the numerous studies, no review exists that synthesizes the major findings of the impacts from an agricultural soil, water and environment pollution point of view. Therefore, this paper presents a synthesis of the impacts on water and the soil together with the management options that are available. The review also identifies main areas that need further investigations.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59075
Title: Atmospheric Heavy Metal Accumulation in Epiphytic Lichens and Their Phorophytes in the Brahmaputra Valley.
Author: Rebecca Daimari, Raza Rafiqul Hoque, Sanjeeva Nayaka, Dalip K Upreti.
Editor: V Subramanian.
Year: 2013
Publisher: Capital Publishing Company.
Source: Centre for Ecological Sciences
Reference: Asian Journal of Water, Environment and Pollution Vol 10(no. 4), pp. 1-12, 2013
Subject: Asian Journal of Water, Environment and Pollution
Keywords: Air pollution, biomonitoring, lichen, Tezpur, source apportionment.
Abstract: Lichens are indicator species of air quality of a locality. Estimate of heavy metal (HM) accumulation in lichens offers an indirect measure of their levels in the atmosphere. Accumulated HMs of lichen thalli of 16 species belonging to 10 genera and their phorophytes of two characteristics areas of Brahmaputra valley were studied. Acid digested samples of thalli and phorophytes were analysed for Cd, Co, Cr, Cu, Fe, Mn, Ni and Pb by ICP-OES. Mean concentrations of the HMs were found to be higher in lichens at the area situated close to the downtown area of the city and the Brahmaputra River. Accumulation of Cd, Cu, Fe and Ni were found to be higher in lichen thalli; however, leaves accumulated higher levels of Co and Mn. Linear regression analysis shows poor dependency of the thalli on their phorophytes indicating accumulation of metals from atmosphere. The extent of enrichment in the lichen thalli, which was evaluated by calculating enrichment factors (EFs) revealed moderate enrichment of Cr, Cu, Ni and Pb; however, Cd was found to be highly enriched. Ecological risk posed by the heavy metals were calculated and it was found that Principal Component Analysis (PCA) of the data set identifies three contributing sources: coal-fired industrial emission, crustal dust blown from dry river bed and vehicular emission.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59074
Title: Image deblurring for satellite imagery using small-support-regularized deconvolution.
Author: Yan Li, Keith C Clarke.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 148-155, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Remote sensing, Image restoration, Deconvolution, Fourier transform, Huangjing (HJ) imagery.
Abstract: This paper presents a new practical deblurring method, small-support-regularized (SSR) deconvolution, for low quality remotely sensed imagery. In the case that the causes of image blur are various and complicated, a Gaussian degradation model is employed to approximate the composite effect. The model in the frequency domain is deduced which yields a representation with the same small support as the Point Spread Function (PSF). An approximate regularized deconvolution filter is proposed. The regularization term of the deconvolution filter is defined as a function relevant to the equvivalent image power spectrum. All the computations to derive the deconvolution filter are implemented in the same support as the PSF. By this method, large matrix manipulation is avoided and remote sensing images can be filtered one at a time, without memory limitations. Meanwhile the method increases computational efficiency, which is most important for large scale satellite images. A case study was conducted for a Chinese small earth observation satellite HJ imagery. The deblurring result proves that this method successfully restores fine image detail, particularly for line features. Various measurements of the image quality show that the algorithm is comparable with other state-of-the-art methods and has advantages for image contrast and edge strength. The computational efficiency increases by about 8-37% for images with sample sizes from 256 to 1000, and will increase more for larger image sizes.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59073
Title: Assessment of number and distribution of persistent scatterers prior to radar acquisition using open access land cover and topographical data.
Author: Simon Plank, John Singer, Kurosch Thuro.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 132-147, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Radar, SAR, Prediction, GIS, Persistent scatterer processing.
Abstract: Persistent scatterer synthetic aperture radar interferometry (PSI) is a powerful remote sensing technique to detect and measure deformation of the Earth ' s crust - such as subsidence and landslides- with an accuracy of a few millimeters. Deformation is measured at specific points in a radar image called persistent scatterers (PS), which are chacterized by long-term constant backscattering properties (high coherence) of the radar signal. Reliable PSI processing requires a stack of 15-50 SAR images and more, and processing is time-consuming (computational costs) and expensive (referring to both, costs for the SAR data and labor costs). Previous research for PS assessment used already acquired SAR. This paper presents two new methods for predicting PS prior to the radar recording of the area of interest using freely available or low-cost land cover data, topographical maps and OpenStreetMap data. In the procedure, the distance between the assessed PS within the site is analysed. The results of the two assessment methods are validated using data of real PSI processing. Here, we show that the developed PS assessment techniques are fast and reliable tools to test the spatial applicability of PSI.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59072
Title: Urban DEM generation, analysis and enhancements using TanDEM-X.
Author: Cristian Rossi, Stefan Gernhardt.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 120-131, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: TanDEM-X, Urban DEM, InSAR processing, PSI-DEM, DEM fusion.
Abstract: This paper analyzes the potential of the TanDEM-X mission for the generation of urban Digital Elevation Models (DEMs). The high resolution of the sensors and the absence of temporal decorrelation are exploited. The interferometric chain and the problems encountered for correct mapping of urban areas are analyzed first. The operational Integrated TanDEM-X Processor (ITP) algorithms are taken as reference. The ITP main product is called the raw DEM. Whereas the ITP coregistration stage is demonstrated to be robust enough, large improvements in the raw DEM such as fewer percentages of phase unwrapping errors, can be obtained by using adaptive fringe filters instead of the conventional ones in the interferogram generation stage. The shape of the raw DEM in the layerover area is also shown and determined to be regular for buildings with vertical walls. Generally, in the presence of layover, the raw DEM exhibits a height ramp, resulting in a height underestimation for the affected structure. Examples provided confirm the theoretical background. The focus is centered on high resolution DEMs produced using spotlight acquisitions. In particular, a raw DEM over Berlin (Germany) with a 2.5m raster is generated and validated. For this purpose, ITP is modified in its interferogram generation stage by adopting the Intensity Driven Adaptive Neighbourhood (IDAN) algorithm. The height Root Mean Square Error (RMSE) between the raw DEM and a reference is about 8m for the two classes defining the urban DEM: structures and non-structures. The result can be further improved for the structure class using a DEM generated with Persistent Scatterer Interferometry. A DEM fusion is thus proposed and a drop of about 20% in the RMSE is reported.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59071
Title: Impact of feature selection on the accuracy and spatial uncertainity of per-field crop classification using Support Vector Machines.
Author: F Low, U Michel, S Dech, C Conrad.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 102-119, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Crop classification, Feature selection Map uncertainity, Random forest, RapidEye, Support Vector Machines.
Abstract: Crop mapping is one major component of agricultural resource monitoring using remote sensing. Yield or water demand modeling requires that both, the total surface that is cultivated and the accurate distribution of crops, respectively is known. Map qualilty is crucial and influences the model outputs. Although the use of multi-spectral time series data in crop mapping has been acknowledged, the potentially high dimensionality of the input data remains an issue. In this study Support Vector Machines (SVM) are used for crop classification in irrigated landscapes at the object-level. Input to the classification is 71 multiseasonal spectral and geostatistical features computed from RapidEye time series. The random forest (RF) feature importance score was used to select a subset of features that achieved optimal accuracies. The relationship between the hard result accuracy and the soft output from the SVM is investigated by employing two measures of uncertainity, the maximum a posteriori probability and the alpha quadratic entropy. Specifically the effect of feature selection on map uncertainity is investigated by looking at the soft outputs of the SVM, in addition to classical accuracy metrics. Overall the SVMs applied to the reduced feature subspaces that were composed of the most informative multi-seasonal features led to a clear increase in classification accuracy up to 4.3% and to a significant decline in thematic uncertainity. SVM was shown to be affected by feature space size and could benefit from RF-based feature selection. Uncertainty measures from SVM are an informative source of information on the spatial distribution of error in the crop maps.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59070
Title: Diurnal and seasonal impacts of urbanization on the urban thermal environment: A case study of Beijing using MODIS data.
Author: Zhi Qjao, Guangjin Tian, Lin Xiao.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 93-101, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Urbanization, Land Surface temperature, Contribution index, MODIS, Beijing.
Abstract: Beijing has experienced rapid urbanization and associated urban hear-island effects and air pollution. In this study, a contribution index was proposed to explore the effect of urbanization on land surface temperature (LST) using Moderate-Resolution Imaging Spectroradiometer (MODIS)-derived data with high temporal resolution. The analysis indicated that different zones and landscapes make diurnally and seasonally different contributions to the regional thermal environment. The differences in contributions by landscapes in this process varied diurnally and seasonally. Urban land was the most important contributor to increases in regional LSTs. The contributions of cropland and forest varied distinctly between daytime and nighttime owing to differences in their thermal inertias. Vegetation had a notable cooling effect as the normalized vegetation difference index (NDVI) increased during summer. However, when the NDVI reached a certain value, the nighttime LST shifted markedly in other seasons. The results suggest that urban design based on vegetation partitions would be effective for regulating the thermal environment.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59069
Title: An approach for developing Landsat-5 TM-based retrieval models of suspended particulate matter concentration with the assistance of MODIS.
Author: Guofeng Wu, Lijuan Cui, Hongtao Duan, Teng Fei, Yaolin Liu.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 84-92, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Water quality, Remote Sensing, Model Development, Exponential model.
Abstract: It is challenging to develop Landsat-5 TM(TM5) image-based retrieval models for estimating the suspended particulate matter concentration (CSPM) in water when missing coincident gradient CSPM measurements. This study, with the Poyang Lake in China as a case study, proposed an approach for developing TM5-based CSPM retrieval models with the assisstance of moderate resolution imaging spectroradiometer (MODIS) images. After validation with an independent dataset, a cubic CSPM retrieval model of 250 m MODIS red band was used to estimate the CSPM values at 100 sampling points from the MODIS images (MODIS-based CSPM) captured at three time periods. The MODIS-based CSPM values at the time period with the largest CSPM variation were combined with their coincident TM5 image reflectance for TM5-based model calibrations. The linear, quadratic, cubic, power and exponential models of MODIS-based CSPM against TM5 single bands and their combinations were calibrated, respectively. Four best-fitting TM5-based CSPM were selected to retrieve the CSPM values at 100 sampling points from the TM5 images(TM5-based CSPM) at the other two time periods, and the coincident MODIS- and TM5-based CSPM values were compared to assess TM5-based model performances. Model calibration results showed that the cubic and exponential models of TM5 red band (band 3) and red subtracting mid-infrared band (band 5) obtained the best fitting for estimating CSPM from the TM5 image on 12 August 2005, and they explained 94-97% of the variation of MODIS-based CSPM values with an estimated standard error of 6.617-8.457 mg/l. Model validations indicated that the exponential model of TM5 red band got the best result for estimating CSPM from TM5 images when the MODIS-based CSPM values were assumed as ground truths (correlation coefficient between MODIS- and TM5-based CSPM values=0.96, root mean square error= 4.60 mg/l). We concluded that the TM5-based CSPM retrieval models could be developed with the assistance of MODIS, and the approach proposed in this study will be helpful for other researchers who also want to retrieve CSPM from TM5 image archive but without coincident ground CSPM measurements.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59068
Title: Adaptive algorithm for large scale dtm interpolation from lidar data for forestry applications in steep forested terrrain.
Author: Almasi S Maguya, Virpi Junttila, Tuomo Kauranne.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 74-83, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: LiDAR processing, DTM extraction, Digital surface modeling, Forestry, Point cloud.
Abstract: Light Detection and Ranging (LiDAR) has become a valuable tool in forest inventory because it yields accurate measurements of tree heights. However, tree height can be accurate only if the height of the ground i.e. the Digital Terrain Model (DTM) interpolation is still a challenge, especially in steep and complex terrain with forest cover. Several algorithms proposed in the literature address this challenge but their performance deteriorates with the decreasing point density caused by the presence of forest cover and steep slopes. In this paper, we propose a new adaptive algorithm for DTM interpolation from LiDAR data in steep terrain in forest cover. The algorithm partitions the input data and estimates a section of the DTM by fitting a linear or quadratic trend surface, or uses cubic spline interpolaltion depeding on the complexity of the section of terrain. The performance of the algorithm is tested in three ways : by visual assessment, by comparison of the tree-height estimates produced using the generated DTM with those obtained using field survey, and by use of International Society for Photogrammetry and Remote Sensing (ISPRS) test data. Test results show that the algorithm can cope well with steep slopes and low LiDAR point densities, giving a more accurate estimate of average tree height compared to conventional algorithms. The algorithm can be used for DTM extraction in large scale forest inventory projects in challenging environments-complex terrain and low LiDAR point densities.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59067
Title: Single tree biomass modelling using airborne laser scanning.
Author: Ville Kankare, Minna Raty, Xiaowei Yu, Markus Holopainen, Mikko Vastaranta, Tuula Kantola, Juha Hyyppa, Hannu Hyyppa, Petteri Alho, Risto Viitala.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 66-73, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Airborne laser scanning, Aboveground, Biomass, Point metrics, Modelling, Single tree.
Abstract: Accurate forest biomass mapping methods would provide the means for e.g. detecting bioenergy potential, biofuel and forest-bound carbon. The demand for practical biomass mapping methods at all forest levels is growing worldwide, and viable options are being developed. Airborne laser scanning (ALS) is a promising forest biomass mapping technique, due to its capability of measuring the three-dimensional forest vegetation structure. The objective of the study was to develop new methods for tree-level biomass estimation using metrics derived from ALS point clouds and to compare the results with field references collected using destructive sampling and with existing biomass models. The study area was located in Evo, southern Finland. ALS data was collected in 2009 with pulse density equalling approximately
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59066
Title: Automatic techniques for 3D reconstruction of critical workplace body postures from range imaging data.
Author: Patrick Westfeld, Hans-Gerd Maas, Oliver Bringmann, Daniel Grollich, Martin Schmauder.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 56-65, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Range camera, Least square tracking, Potential energy model surface fit, Human motion, CAD manikin, Awkward body postures.
Abstract: The paper shows techniques for the determination of structured motion parameters from range camera image sequences. The core contribution of the work presented here is the development of an integrated least squares 3D tracking approach based on amplitude and range image sequences to calculate dense 3D motion vector fields. Geometric primitives of a human body model are fitted to time series of range camera point clouds using these vector fields as additional information. Body poses and motion information for individual body parts are derived from the model fit. On the basis of these pose and motion parameters, critical body postures are detected. The primary aim of the study is to automate ergonomic studies for risk assessments regulated by law, identifying harmful movements and awkward body postures in a workplace.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59065
Title: An automated algorithm for extracting road edges from terrestrial mobile LiDAR data.
Author: Pankaj Kumar, Conor P McElhinney, Paul Lewis, Timothy McCarthy.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 85, pp. 44-55, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Edge, Automation, Extraction, LiDAR, Terrestrial mobile.
Abstract: Terrestrial mobile laser scanning systems provide rapid and cost effective 3D point cloud data which can be used for extracting features such as the road edge along a route corridor. This information can assist road authorities in carrying out safety risk management studies along road networks. The knowledge of the road edge is also a prerequisite for the automatic estimation of most other road features. In this paper, we present an algorithm which has been developed for extracting left and right road edges from terrestrial mobile LiDAR data. The algorithm is based on a novel way of initialising the snake model based on the navigation information obtained from the mobile mapping vehicle. We tested our algorithm on different types of road sections representing rural, urban and national primary road sections. The successful extraction of road edges from these multiple road section environments validates our algorithm. These findings and knowledge provide valuable insights as well as a prototype road edge extraction tool-set, for both national road authorities and survey companies.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59064
Title: Object detection in remote sensing imagery using a discriminatively trained mixture model
Author: Gong Cheng, Junwei Han, Lei Guo, Xiaoliang Qian, Peicheng Zhou, Xiwen Yao, Xintao Hu.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 84, pp. 32-43, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Object detection, Remote sensing imagery, Part-based model, Mixt
Abstract: None
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 59063
Title: A semi-ellipsoid-model based fuzzy classifier to map grassland in Inner Mongolia , China.
Author: Hai Lan, Yichun Xie.
Editor: Derek Lichti.
Year: 2013
Publisher: Elsevier
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry and Remote Sensing Vol 84, pp. 21-31, 2013
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Fuzzy classifier, Grassland Classification, Landsat, Semi-ellipsoid-model, Tetragonal pyramid model, Image fusion.
Abstract: Remote sensing techniques offer effective means for mapping plant communities. However, mapping grassland with fine vegetative classes over large areas has been challenging for either the coarse resolutions of remotely sensed images or the high costs of acquiring images with high-resolutions. An improved hybrid-fuzzy-classifier (HFC) derived from a semi-ellipsoid-model (SEM) is developed in this paper to achieve higher accuracy for classifying grasslands with Landsat images. The Xilin River Basin, Inner Mongolia, China, is chosen as the study area, because an acceptable volume of ground truthing data was previously collected by multiple research communities. The accuracy assessment is based on the comparison of the classification outcomes from four types of image sets: (1) Landsat ETM + August 14, 2004, (2) Landsat TM August 12, 2009, (3) the fused images of ETM+ with CBERS, and (4) TM with CBERS, respectively, and by three classifiers, the proposed HFC-SEM, the tetragonal pyramid model (TPM) based HFC, and the support vector machine method. In all twelve classification experiments, the HFC-SEM classifier had the best overall accuracy statistics. This finding indicates that the medium resolution Landsat images can be used to map grassland vegetation with good vegetative detail when the proper classifier is applied.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None