Analysis of full-waveform LiDAR data for classification of an orange orchard scene

Full-waveform laser scanning data acquired with a Riegl LMS-Q560 instrument were used to classify an orange orchard into orange trees, grass and ground using waveform parameters alone. Gaussian decomposition was performed on this data capture from the National Airborne Field Experiment in November 2006 using a custom peak-detection procedure and a trust-region-reflective algorithm for fitting Gauss functions. Calibration was carried out using waveforms returned from a road surface, and the backscattering coefficient c was derived for every waveform peak. The processed data were then analysed according to the number of returns detected within each waveform and classified into three classes based on pulse width and c. For single-peak waveforms the scatterplot of c versus pulse width was used to distinguish between ground, grass and orange trees. In the case of multiple returns, the relationship between first (or first plus middle) and last return c values was used to separate ground from other targets. Refinement of this classification, and further sub-classification into grass and orange trees was performed using the c versus pulse width scatterplots of last returns. In all cases the separation was carried out using a decision tree with empirical relationships between the waveform parameters. Ground points were successfully separated from orange tree points. The most difficult class to separate and verify was grass, but those points in general corresponded well with the grass areas identified in the aerial photography. The overall accuracy reached 91%, using photography and relative elevation as ground truth. The overall accuracy for two classes, orange tree and combined class of grass and ground, yielded 95%. Finally, the backscattering coefficient c of single-peak waveforms was also used to derive reflectance values of the three classes. The reflectance of the orange tree class (0.31) and ground class (0.60) are consistent with published values at the wavelength of the Riegl scanner (1550 nm). The grass class reflectance (0.46) falls in between the other two classes as might be expected, as this class has a mixture of the contributions of both vegetation and ground reflectance properties.

Integrated visual vocabulary in latent Dirichlet allocation-based scene classification for IKONOS image

Scene classification based on latent Dirichlet allocation (LDA) is a more general modeling method known as a bag of visual words, in which the construction of a visual vocabulary is a crucial quantization process to ensure success of the classification. A framework is developed using the following new aspects: Gaussian mixture clustering for the quantization process, the use of an integrated visual vocabulary (IVV), which is built as the union of all centroids obtained from the separate quantization process of each class, and the usage of some features, including edge orientation histogram, CIELab color moments, and gray-level co-occurrence matrix (GLCM). The experiments are conducted on IKONOS images with six semantic classes (tree, grassland, residential, commercial/industrial, road, and water). The results show that the use of an IVV increases the overall accuracy (OA) by 11 to 12% and 6% when it is implemented on the selected and all features, respectively. The selected features of CIELab color moments and GLCM provide a better OA than the implementation over CIELab color moment or GLCM as individuals. The latter increases the OA by only ∼2 to 3%. Moreover, the results show that the OA of LDA outperforms the OA of C4.5 and naive Bayes tree by ∼20%. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.JRS.8.083690]

Model-based vehicle detection and classification using orthographic approximations

This paper reports the current state of work to simplify our previous model-based methods for visual tracking of vehicles for use in a real-time system intended to provide continuous monitoring and classification of traffic from a fixed camera on a busy multi-lane motorway. The main constraints of the system design were: (i) all low level processing to be carried out by low-cost auxiliary hardware, (ii) all 3-D reasoning to be carried out automatically off-line, at set-up time. The system developed uses three main stages: (i) pose and model hypothesis using 1-D templates, (ii) hypothesis tracking, and (iii) hypothesis verification, using 2-D templates. Stages (i) & (iii) have radically different computing performance and computational costs, and need to be carefully balanced for efficiency. Together, they provide an effective way to locate, track and classify vehicles.

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

A review and classification of the existing models of cyanobacteria

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting bloom occurrence in lakes and rivers. In this paper existing key models of cyanobacteria are reviewed, evaluated and classified. Two major groups emerge: deterministic mathematical and artificial neural network models. Mathematical models can be further subcategorized into those models concerned with impounded water bodies and those concerned with rivers. Most existing models focus on a single aspect such as the growth of transport mechanisms, but there are a few models which couple both.

Direct radiative effect of aerosols emitted by transport from road, shipping and aviation

Aerosols and their precursors are emitted abundantly by transport activities. Transportation constitutes one of the fastest growing activities and its growth is predicted to increase significantly in the future. Previous studies have estimated the aerosol direct radiative forcing from one transport sub-sector, but only one study to our knowledge estimated the range of radiative forcing from the main aerosol components (sulphate, black carbon (BC) and organic carbon) for the whole transportation sector. In this study, we compare results from two different chemical transport models and three radiation codes under different hypothesis of mixing: internal and external mixing using emission inventories for the year 2000. The main results from this study consist of a positive direct radiative forcing for aerosols emitted by road traffic of +20±11 mW m−2 for an externally mixed aerosol, and of +32±13 mW m−2 when BC is internally mixed. These direct radiative forcings are much higher than the previously published estimate of +3±11 mW m−2. For transport activities from shipping, the net direct aerosol radiative forcing is negative. This forcing is dominated by the contribution of the sulphate. For both an external and an internal mixture, the radiative forcing from shipping is estimated at −26±4 mW m−2. These estimates are in very good agreement with the range of a previously published one (from −46 to −13 mW m−2) but with a much narrower range. By contrast, the direct aerosol forcing from aviation is estimated to be small, and in the range −0.9 to +0.3 mW m−2.

Soft topographic map for clustering and classification of bacteria

In this work a new method for clustering and building a topographic representation of a bacteria taxonomy is presented. The method is based on the analysis of stable parts of the genome, the so-called “housekeeping genes”. The proposed method generates topographic maps of the bacteria taxonomy, where relations among different type strains can be visually inspected and verified. Two well known DNA alignement algorithms are applied to the genomic sequences. Topographic maps are optimized to represent the similarity among the sequences according to their evolutionary distances. The experimental analysis is carried out on 147 type strains of the Gammaprotebacteria class by means of the 16S rRNA housekeeping gene. Complete sequences of the gene have been retrieved from the NCBI public database. In the experimental tests the maps show clusters of homologous type strains and present some singular cases potentially due to incorrect classification or erroneous annotations in the database.

Financing road transport infrastructure

In the UK, public expenditure on transport infrastructure is nearly £6 billion for the past few years. Over £500 million per year were spent on bridge assessment and strengthening and reducing the backlog of road requiring maintenance. A further £200 million a year will be spent on keeping the safe operation of the network and efficiently through day to day maintenance, lighting and signing . The Department of Transport is planning to extend private sector experience in road management and operation by introducing Design, Build, Finance and Operate (DBFO) This paper investigates the different ways of financing road transport infrastructure including road pricing, private finance in transport infrastructure, the role of the private sector, Design, Build, Finance and Operate (DBFO) schemes, the benefits and problems of such schemes. The paper considers planning gain as a means of financing transport infrastructure with examples of developers to fund link road building and improvements to the local planning system

The slow road to the eukaryotic genome

The eukaryotic genome is a mosaic of eubacterial and archaeal genes in addition to those unique to itself. The mosaic may have arisen as the result of two prokaryotes merging their genomes, or from genes acquired from an endosymbiont of eubacterial origin. A third possibility is that the eukaryotic genome arose from successive events of lateral gene transfer over long periods of time. This theory does not exclude the endosymbiont, but questions whether it is necessary to explain the peculiar set of eukaryotic genes. We use phylogenetic studies and reconstructions of ancestral first appearances of genes on the prokaryotic phylogeny to assess evidence for the lateral gene transfer scenario. We find that phylogenies advanced to support fusion can also arise from a succession of lateral gene transfer events. Our reconstructions of ancestral first appearances of genes reveal that the various genes that make up the eukaryotic mosaic arose at different times and in diverse lineages on the prokaryotic tree, and were not available in a single lineage. Successive events of lateral gene transfer can explain the unusual mosaic structure of the eukaryotic genome, with its content linked to the immediate adaptive value of the genes its acquired. Progress in understanding eukaryotes may come from identifying ancestral features such as the eukaryotic splicesome that could explain why this lineage invaded, or created, the eukaryoticniche.

Risky attitudes towards road use in pre-drivers

Motor vehicle accidents are one of the principal causes of adolescent disability or mortality and male drivers are more likely to be involved in road accidents than female drivers. In part such associations between driver age and sex have been linked to differences in risky behaviour (e.g. speed, violations) and individual characteristics (e.g. sensation seeking, deviant behaviour). The aim of this research is to determine whether associations between risky road user behaviour and individual characteristics are a function of driver behaviour or whether they are intrinsic and measurable in individuals too young to drive. Five hundred and sixty-seven pre-driver students aged 11-16 from three secondary schools completed questionnaires measuring enthusiasm for speed, sensation seeking, deviant behaviour and attitudes towards driver violations. Boys reported more risky attitudes than girls for all measures. Associations between sensation seeking, deviant behaviour and attitudes towards risky road use were present from early adolescence and were strongest around age 14, before individuals learn to drive. Risky attitudes towards road use are associated with individual characteristics and are observed in adolescents long before they learn to drive. Safe attitudes towards road use and driver behaviour should be promoted from childhood in order to be effective. (C) 2007 Elsevier Ltd. All rights reserved.