Automated 3D scene reconstruction from open geospatial data sources: airborne laser scanning and a 2D topographic database

Open geospatial data sources provide opportunities for low cost 3D scene reconstruction. In this study, based on a sparse airborne laser scanning (ALS) point cloud (0.8 points/m2) obtained from open source databases, a building reconstruction pipeline for CAD building models was developed. The pipeline includes voxel-based roof patch segmentation, extraction of the key-points representing the roof patch outline, step edge identification and adjustment, and CAD building model generation. The advantages of our method lie in generating CAD building models without the step of enforcing the edges to be parallel or building regularization. Furthermore, although it has been challenging to use sparse datasets for 3D building reconstruction, our result demonstrates the great potential in such applications. In this paper, we also investigated the applicability of open geospatial datasets for 3D road detection and reconstruction. Road central lines were acquired from an open source 2D topographic database. ALS data were utilized to obtain the height and width of the road. A constrained search method (CSM) was developed for road width detection. The CSM method was conducted by splitting a given road into patches according to height and direction criteria. The road edges were detected patch by patch. The road width was determined by the average distance from the edge points to the central line. As a result, 3D roads were reconstructed from ALS and a topographic database

Power line mapping technique using all-terrain mobile laser scanning

Power line mapping using remote sensing can automate the traditionally labor-intensive power line corridor inspection. Land-based mobile laser scanning (MLS) can be a good choice for the power line mapping if an aerial inspection is impossible, too costly or slow, unsafe, prohibited by regulations, or if more detailed information on the power line corridor is needed. The mapping of the power lines using MLS was studied in a rural environment outside the road network for the first time. An automatic power line extraction algorithm was developed. The algorithm first found power line candidate points based on the shape and orientation of the local neighborhood of a point using principal component analysis. Power lines were retrieved from the candidates using random sample consensus (Ransac) and a new power line labeling method, which takes into account the three-dimensional shape of the power lines. The new labeling method was able to find the power lines and remove false detections, which were found, for example, from the forest. The algorithm was tested in forested and open field (arable land) areas, outside the road environment using two different platforms of MLS, namely, personal backpack and all-terrain vehicle. The recall and precision of the power line extraction were 93.3% and 93.6%, respectively, using 10 cm as a distance criterion for a successful detection. Drifting of the positioning solution of the scanner was the largest error source, being the (contributory) cause for 60–70% of the errors. The platform did not have a significant effect on the power line extraction accuracy. The accuracy was higher in the open field compared to the forest, because the one-dimensional point density along the power line was inhomogeneous and GNSS (global navigation satellite system) signal was weak in the forest. The results suggest that the power lines can be mapped accurately enough for inspection purposes using MLS in a rural environment outside the road network.</p

On the Sample Size for the Estimation of Primary Activity Statistics Based on Spectrum Sensing

Dynamic spectrum access (DSA)/cognitive radio (CR) systems can benefit from the knowledge of the activity statistics of primary channels, which can use this information to intelligently adapt their spectrum use to the operating environment. Particularly relevant statistics are the minimum, mean and variance of the on/off period durations, the channel duty cycle and the governing distribution. However, most DSA/CR systems have limited resources (power consumption, memory capacity, computational capability) and an important question arises of how many on/off period observations are required (i.e., the number of observed on/off periods, referred to as observation sample size in this paper) to estimate the statistics of the primary channel to a certain desired level of accuracy. In this paper, closed-form expressions to link such sample size with the accuracy of the observed primary activity statistics are proposed. A comprehensive theoretical analysis is performed on the required number of observed on/off periods to obtain a specific estimation accuracy. The accuracy of the obtained analytical results is validated and corroborated with both simulation and experimental results, showing a perfect agreement. The analytical results derived in this paper can be used in the design and dimensioning of DSA/CR systems in which the spectrum awareness function relies on spectrum sensing

Preregistration Classification of Mobile LIDAR Data Using Spatial Correlations

We explore a novel paradigm for light detection and ranging (LIDAR) point classification in mobile laser scanning (MLS). In contrast to the traditional scheme of performing classification for a 3-D point cloud after registration, our algorithm operates on the raw data stream classifying the points on-the-fly before registration. Hence, we call it preregistration classification (PRC). Specifically, this technique is based on spatial correlations, i.e., local range measurements supporting each other. The proposed method is general since exact scanner pose information is not required, nor is any radiometric calibration needed. Also, we show that the method can be applied in different environments by adjusting two control parameters, without the results being overly sensitive to this adjustment. As results, we present classification of points from an urban environment where noise, ground, buildings, and vegetation are distinguished from each other, and points from the forest where tree stems and ground are classified from the other points. As computations are efficient and done with a minimal cache, the proposed methods enable new on-chip deployable algorithmic solutions. Broader benefits from the spatial correlations and the computational efficiency of the PRC scheme are likely to be gained in several online and offline applications. These range from single robotic platform operations including simultaneous localization and mapping (SLAM) algorithms to wall-clock time savings in geoinformation industry. Finally, PRC is especially attractive for continuous-beam and solid-state LIDARs that are prone to output noisy data

GPAW: open Python package for electronic-structure calculations

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE) providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe-Salpeter Equation (BSE), variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn-Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support of GPU acceleration has been achieved with minor modifications of the GPAW code thanks to the CuPy library. We end the review with an outlook describing some future plans for GPAW

Resectability, conversion, metastasectomy and outcome according to RAS and BRAF status for metastatic colorectal cancer in the prospective RAXO study

Background Outcomes after metastasectomy for metastatic colorectal cancer (mCRC) vary with RAS and BRAF mutational status, but their effects on resectability and conversion rates have not been extensively studied. Methods This substudy of the prospective RAXO trial included 906 patients recruited between 2011 and 2018. We evaluated repeated centralised resectability assessment, conversion/resection rates and overall survival (OS), according to RAS and BRAF status. Results Patients included 289 with RAS and BRAF wild-type (RAS and BRAFwt), 529 with RAS mutated (RASmt) and 88 with BRAF mutated (BRAFmt) mCRC. Metastatic prevalence varied between the RAS and BRAFwt/RASmt/BRAFmt groups, for liver (78%/74%/61%), lung (24%/35%/28%) and peritoneal (15%/15%/32%) metastases, respectively. Upfront resectability (32%/29%/15%), conversion (16%/13%/7%) and resection/local ablative therapy (LAT) rates (45%/37%/17%) varied for RASa and BRAFwt/RASmt/BRAFmt, respectively. Median OS for patients treated with resection/LAT (n = 342) was 83/69/30 months, with 5-year OS-rates of 67%/60%/24%, while systemic therapy-only patients (n = 564) had OS of 29/21/15 months with 5-year OS-rates of 11%/6%/2% in RAS and BRAFwt/RASmt/BRAFmt, respectively. Resection/LAT was associated with improved OS in all subgroups. Conclusions There were significant differences in resectability, conversion and resection/LAT rates according to RAS and BRAF status. OS was also significantly longer for RAS and BRAFwt versus either mutant. Patients only receiving systemic therapy had poorer long-term survival, with variation according to molecular status.</p

Burden of disease attributable to risk factors in European countries: a scoping literature review

Objectives: Within the framework of the burden of disease (BoD) approach, disease, and injury burden estimates attributable to risk factors are a useful guide for policy formulation and priority setting in disease prevention. Considering the important differences in methods, and their impact on burden estimates, we conducted a scoping literature review to: (1) map the BoD assessments including risk factors performed across Europe, and (2) identify the methodological choices in comparative risk assessment (CRA) and risk assessment methods. Methods: We searched multiple literature databases, including grey literature websites, and targeted public health agencies' websites. Results: A total of 113 studies were included in the synthesis and further divided into independent BoD assessments (54 studies) and studies linked to the Global Burden of Disease (59 papers). Our results showed that the methods used to perform CRA varied substantially across independent European BoD studies. While there were some methodological choices that were more common than others, we did not observe patterns in terms of country, year, or risk factor. Each methodological choice can affect the comparability of estimates between and within countries and/or risk factors since they might significantly influence the quantification of the attributable burden. From our analysis, we observed that the use of CRA was less common for some types of risk factors and outcomes. These included environmental and occupational risk factors, which are more likely to use bottom-up approaches for health outcomes where disease envelopes may not be available. Conclusions: Our review also highlighted misreporting, the lack of uncertainty analysis, and the under-investigation of causal relationships in BoD studies. Development and use of guidelines for performing and reporting BoD studies will help understand differences, and avoid misinterpretations thus improving comparability among estimates.info:eu-repo/semantics/publishedVersio