Rough Map Research Articles

Quantitative analysis of Mars surface radar reflectivity at 20 MHz

The radar surface echoes taken from SHARAD observations are extracted to obtain a reflectivity map covering almost half of the martian surface, and then compared to available roughness maps. Then, we used a 2-step method, based on a stochastic description of reflectivity, in order to (i) separate the coherent/incoherent components of the signal by means of a probability density function fitting of amplitude distributions, and (ii) express these components with respect to roughness/permittivity values by adapting common backscattering models to the nadir case. Scattering is found to be the most important process dominating reflectivity over the martian terrains. Reflectivity is best correlated with roughness maps derived from the slope parameter. The stochastic behavior of reflectivity is confirmed by the excellent agreement of our models and demonstrates the low probability of retrieving permittivity from scattering surfaces. The non-stationary nature of most martian terrains is consolidated by a very good fit to K-distributions, justifying the use of the fractal theory for describing surface roughness on Mars. A few slightly-rough regions exhibit both a coherent and incoherent component. When surface correlation length is non-significant within the resolution cell, we show that the RMS roughness at a decameters baseline can be derived with sub-decimeter sensitivity without prior signal calibration, improving the capabilities of SHARAD in determining surface roughness with a view to landing site selection. Sets of derived dielectric constants are obtained and analyzed with regard to the reference signal used for calibration. Given the very different implications of each set to the composition of martian terrains, we emphasize the importance of good signal calibration as a major issue for SHARAD and the next interplanetary radar missions.

Hybrid dimension based modeling of part surface topography and identification of its characteristic parameters

Since the complete description of complex part surface is difficult to achieve using the existing integral dimensional or fractal dimensional approaches, the novel concept of hybrid dimension and its modeling method of part surface topography are proposed in this paper. The hybrid dimensional model of part surface topography is established based on the deflection method of surface correlation coefficient, which associates the integral dimensional and fractal dimensional surface topographies. Superimposing the normalized fractal dimensional surface altitude field on the B-spline surface, the hybrid dimensional model can express the integral dimensional information of part surface in macro level, and the fractal dimensional detail in micro level. And the correlation of part surface topographies among different scales and different dimensions is established by the Hybrid Dimensional Surface Correlation Coefficient. Moreover, the characteristic parameter identification method for the hybrid dimensional model of part surface topography is proposed. The component information of integral dimension and fractal dimension is separated and extracted by wavelet analysis, and hybrid dimensional characteristic parameters are identified by the generalized surface structure function method and the roughness mapping method. Finally, the proposed method is applied to design and manufacture of turbo expander.

Real-time optical SLAM-based mosaicking for unmanned underwater vehicles

This article discusses the possibility of building in real-time a mosaic of the seafloor relying on a simultaneous localization and mapping (SLAM) framework. The goal is to provide an unmanned underwater vehicle with a relatively rough visual map of the seafloor to support basic navigation and context awareness. To achieve that goal, an accurate estimation of the location of the visual landmarks and, in particular, the correct data association when a visual landmark is re-visited by the vehicle are the crucial points. Instead of using a global mosaic, this work uses the combination of a set of local mosaics constructed in the vicinity of the SLAM visual landmarks. The contributions of this article are mainly the use of SURF features, the local mosaics approach and the real-time capability. The use of SURF features allows eliminating false positives in the data association of SLAM visual landmarks. The local mosaics approach is an effective way of correcting the effects of the drift on the mosaic in real time. The main contribution is the real-time capability as it will be seen. The algorithm was tested using a batch of experimental data in typical operating conditions and the results prove the effectiveness of the approach.

Advances in remote sensing of hydraulic roughness

Riparian vegetation plays a crucial role in affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. Systematic detection, identification and assessment of flow resistance factors using conventional field sampling is often unfeasible as these techniques are time-consuming and expensive. As in many other environmental monitoring problems, remote sensing may provide unprecedented mapping capabilities. In this article we present an overview focusing on the different methods that can be used to remotely derive floodplain hydraulic roughness. The overview is based on an extensive literature review on recent estimation techniques of riparian roughness using remote sensing data from different platforms. The outlined methods of floodplain roughness parameterization include: (1) classification-derived hydraulic roughness maps and (2) estimation of vegetation hydrodynamic properties. Possible directions for a multiscale analysis of riparian flow resistance are also described in a short section by focusing on the potential of data assimilation methods for the estimation of floodplain roughness. The literature reveals that many valuable remote-sensing techniques have been developed for riparian corridor parameterization. Methodologies based on the fusion of multispectral/temporal imagery with data of different origin, such as light detection and ranging (LiDAR) and radar/microwave, appear to be powerful tools for characterizing riparian ecosystems for hydraulic purposes.

Rough terrain mapping and classification for foothold selection in a walking robot

AbstractAlthough legged locomotion over a moderately rugged terrain can be accomplished by employing simple reactions to the ground contact information, a more effective approach, which allows predictively avoiding obstacles, requires a model of the environment and a control algorithm that takes this model into account when planning footsteps and leg movements. This article addresses the issues of terrain perception and modeling and foothold selection in a walking robot. An integrated system is presented that allows a legged robot to traverse previously unseen, uneven terrain using only onboard perception, provided that a reasonable general path is known. An efficient method for real‐time building of a local elevation map from sparse two‐dimensional (2D) range measurements of a miniature 2D laser scanner is described. The terrain mapping module supports a foothold selection algorithm, which employs unsupervised learning to create an adaptive decision surface. The robot can learn from realistic simulations; therefore no a priori expert‐given rules or parameters are used. The usefulness of our approach is demonstrated in experiments with the six‐legged robot Messor. We discuss the lessons learned in field tests and the modifications to our system that turned out to be essential for successful operation under real‐world conditions. © 2011 Wiley Periodicals, Inc.

Marginal Winds Leading to Competitive Rates: A Case Study in Southern Tamaulipas

Wind velocity was monitored from two towers located along the shoreline in southern Tamaulipas during a year. The computed wind potential at 50 m ranges from 205 to 212 W/m2. The coastal sea breeze system on the study area is enforced by the synoptic surface flow along the year; it provides a permanency feature on the daily energy production and it also explains the higher power values in the evenings. Based on the topography and roughness maps, the database was extrapolated inland to an area of 234 km2 by solving the non-linear Navier-Stokes equations. From the estimated Annual Energy Production for several groups of turbines simulated in the area, a feasibility financial study indicates that a utility scale wind farm may produce competitive electricity rates compared to local prices, despite that wind power is merely above poor.

Roughness Mapping on Various Vertical Scales Based on Full-Waveform Airborne Laser Scanning Data

Roughness is an important input parameter for modeling of natural hazards such as floods, rock falls and avalanches, where it is basically assumed that flow velocities decrease with increasing roughness. Seeing roughness as a multi-scale level concept (i.e., ranging from fine-scale soil characteristics to description of understory and lower tree layer) various roughness raster products were derived from the original full-waveform airborne laser scanning (FWF-ALS) point cloud using two different types of roughness parameters, the surface roughness (SR) and the terrain roughness (TR). For the calculation of the SR, ALS terrain points within a defined height range to the terrain surface are considered. For the parameterization of the SR, two approaches are investigated. In the first approach, a geometric description by calculating the standard deviation of plane fitting residuals of terrain points is used. In the second one, the potential of the derived echo widths are analyzed for the parameterization of SR. The echo width is an indicator for roughness and the slope of the target. To achieve a comparable spatial resolution of both SR layers, the calculation of the standard deviation of detrended terrain points requires a higher terrain point density than the SR parameterization using the echo widths. The TR describes objects (i.e., point clusters) close but explicitly above the terrain surface, with 20 cm defined as threshold height value for delineation of the surface layer (i.e., forest floor layer). Two different empirically defined vegetation layers below the canopy layer were analyzed (TR I: 0.2 m to 1.0 m; TR II: 0.2 m to 3.0 m). A 1 m output grid cell size was chosen for all roughness parameters in order to provide consistency for further integration of high-resolution optical imagery. The derived roughness parameters were then jointly classified, together with a normalized Digital Surface Model (nDSM) showing the height of objects (i.e., trees) above ground. The presented approach enables the classification of forested areas in patches of different vegetation structure (e.g., varying soil roughness, understory, density of natural cover). For validation purposes in situ reference data were collected and cross-checked with the classification results, positively confirming the general feasibility of the proposed vertical concept of integrated roughness mapping on various vertical levels. Results can provide valuable input for forest mapping and monitoring, in particular with regard to natural hazard modeling.

A rice mutant displaying a heterochronically elongated internode carries a 100 kb deletion

We have isolated a recessive rice mutant, designated as indeterminate growth (ing), which displays creeping and apparent heterochronic phenotypes in the vegetative period with lanky and winding culms. Rough mapping and subsequent molecular characterization revealed that the ing mutant carries a large deletion, which corresponds to a 103 kb region in the Nipponbare genome, containing nine annotated genes on chromosome 3. Of these annotated genes, the SLR1 gene encoding a DELLA protein is the only one that is well characterized in its function, and its null mutation, which is caused by a single base deletion in the middle of the intronless SLR1 gene, confers a slender phenotype that bears close resemblance to the ing mutant phenotype. The primary cause of the ing mutant phenotype is the deletion of the SLR1 gene, and the ing mutant appears to be the first characterized mutant having the entire SLR1 sequence deleted. Our results also suggest that the deleted region of 103 kb does not contain an indispensable gene, whose dysfunction must result in a lethal phenotype.

AUV-based bed roughness mapping over a tropical reef

Identifying fixed bed roughness scales of hydrodynamic relevance to waves and currents is challenging around coral reefs due to their highly inhomogeneous bathymetry. In order to characterize the spatial variability in reef roughness, a quantitative analysis of high-resolution sidescan sonar backscatter is performed for the identification of distinct substrates around a tropical reef and is related to echo sounder-based roughness measurements. Data were collected in the vicinity of the Kilo Nalu Observatory on the south shore of Oahu using sidescan sonar and a narrow beam echo sounder incorporated in a REMUS-100 (Remote Environmental Monitoring UnitS) autonomous underwater vehicle (AUV). With basic statistics and principal component analysis of variables derived from the backscatter data, it is possible to discriminate between areas of rough reef, bare reef, and rippled sand. Echo sounder-derived spectral analysis did not reveal dominant length scales. However, by combining the seabed classification obtained from sidescan measurements with echo sounder data, spectral root mean square (RMS) height values of approximately 3.3 cm and 7.3 cm are assigned to the bare reef and rough reef areas, respectively, for roughness with wavelengths between 0.2 and 6 m.

Towards an urban roughness parameterisation using interferometric SAR data taking the Metropolitan Region of Hamburg as an example

Increased surface roughness and the enhanced drag effect of the urban surface are important alterations in urban boundary layer dynamics. An enhanced roughness mapping would be beneficial for several modelling applications since state of the art roughness parameters derived from land use data do not represent the heterogeneity of urban surfaces at higher resolutions. Today most morphometric methods of urban roughness estimation are based on empirically derived functions of obstacle geometry parameters, which have conceptual and practical shortcomings. In this study we propose a new approach based on the topology, statistics and texture of overall roughness elements as represented by a Digital Height Model generated from side-looking Interferometric Synthetic Aperture Radar. These state of the art remotely sensed high resolution data are readily available for Western Europe, the US, as well as parts of Asia and the Caribbean. A set of new angular dependent urban morphology parameters is developed and tested for suitability for the mapping of roughness characteristics by way of an improved methodology. The results are very convincing and consistent over a wide range of surface characteristics.

Rough center mining algorithm of rough cognitive map

For the large-scale systems with complex causal connection in practical problems, fusion rough cognitive maps and graph mining methods, designed a rough central area mining algorithm of rough cognitive maps to complete the pruning problem of rough cognitive map, simplified the structure of rough cognitive map to facilitate the further relations. First of all, from the perspective of the arc, give another definition of rough cognitive map, introduce the concept of rough centrality R accuracy; second, define certainty -possible class road, according to the given threshold to determine the rough central area. Finally, design an effective rough central area mining algorithm for further analysis and forecast the rough cognitive map.

Diverse traversability mapping using hybrid vision system for lunar rover

Autonomous functions including mapping and path planning are very important to ensure efficient exploration and safe navigation of unmanned rover. Conventional navigation schemes based on equipments such as GPS and magnetic sensors have been proven to be ineffective on lunar surface, while sophisticated dead reckoning approach lacks accuracy in loose soil due to slippage. In this paper, we propose a hybrid vision system (HVS) which consists of one stereo and one omnidirectional vision sensor, attempting to integrate the advantages of diverse vision systems. The hierarchical mapping reconstructs environment through HVS in different resolutions and structures, named qualitative, rough and detailed map. These maps are employed for path planning which navigates the rover towards specified destinations autonomously, avoiding obstacles in its way. The HVS aims at providing more efficient and safe navigation. Simulations and experiments demonstrate the functionality and advantage of our approach.

TecDEM: A MATLAB based toolbox for tectonic geomorphology, Part 2: Surface dynamics and basin analysis

We present the analytical capability of TecDEM, a MATLAB toolbox used in conjunction with Global DEMs for the extraction of tectonic geomorphologic information. TecDEM includes a suite of algorithms to analyze topography, extracted drainage networks and sub-basins. The aim of part 2 of this paper series is the generation of morphometric maps for surface dynamics and basin analysis. TecDEM therefore allows the extraction of parameters such as isobase, incision, drainage density and surface roughness maps. We also provide tools for basin asymmetry and hypsometric analysis. These are efficient graphical user interfaces (GUIs) for mapping drainage deviation from basin mid-line and basin hypsometry. A morphotectonic interpretation of the Kaghan Valley (Northern Pakistan) is performed with TecDEM and the findings indicate a high correlation between surface dynamics and basin analysis parameters with neotectonic features in the study area.

Procedure for zoning land in Moscow for construction of deep-seated entities

It is demonstrated that construction utilization of the geologic medium of metropolitan Moscow is restricted by complex geologic-engineering conditions and in-service entities of the underground infrastructure. A procedure for zoning of land, which is based on analysis of geologic and hydrogeologic conditions within the city, is developed. Criteria are proposed for the separation of sections favorable, conditionally favorable, and unfavorable for the erection of structures. The procedure has been approved for the zoning of land for construction of the Moscow International Business Center (MIBC) “City of Moscow.” Rough maps, which make it possible to compare the economic effectiveness of the opening of pits of various depth, are drawn.

Shop talk: Annual Drosophila Research Conference, 2010

Shop talk: Annual Drosophila Research Conference, 2010

Tsunami inundation modelling based on detailed roughness maps of densely populated areas

Abstract. An important part within the German-Indonesian Tsunami Early Warning System (GITEWS) project was the detailed numerical investigation of the impact of tsunamis in densely populated coastal areas of Indonesia. This work, carried out by the German Research Centre Geesthacht (GKSS), in co-operation with DHI-WASY, also provides the basis for the preparation of high resolution hazard and risk maps by the German Aerospace Center (DLR). In this paper a method is described of how to prepare very detailed roughness maps for scenario computations performed with the MIKE 21 Flow Model FM in three highly resolved (~10 m) priority regions, namely Kuta (Bali), Padang (West-Sumatra), and Cilacap (southern coast of Java). Roughness values are assigned to 43 land use classes, e.g. different types of buildings, rural and urban sub-areas, by using equivalent coefficients found in literature or by performing numerical experiments. Comparisons of simulations using differentiated roughness maps with simulations using constant values (a widely used approach) are presented and it is demonstrated that roughness takes considerable influence on run-up and inundation. Out of all simulations, the results of the worst case scenarios for each of the three priority areas are discussed. Earthquakes with magnitudes of MW=8.5 or higher lead to considerable inundation in all study sites. A spatially distinguished consideration of roughness has been found to be necessary for detailed modelling onshore.

Application of Plasmons to the Determination of Surface Profile and Contact Strain Distribution

Abstract: Free electrons in the surface of metals can produce surface plasmons if they are excited by evanescent waves. The surface plasmons are electromagnetic waves that by decaying can generate photons. These photons produce propagating waves that feed energy to an oscillating cavity. From this effect a Fabry–Perot like interferometer is generated. In view of this basic knowledge a truly novel application on how these plasmons can be used experimentally is introduced in this article. Essentially, by using the transformation of evanescent waves into propagating waves via the plasmon generation it is possible to perform high accuracy contouring of any metal surface as well as the determination of its contact stresses. A laser beam illuminates a glass‐air‐metal interface and through a proper optical setup it will produce double evanescent illumination. This illumination generates interference fringes that contain surface depth information as well as in‐plane strain information. In order to show the robustness of the proposed technique, three different applications are presented in the paper. First, the surface roughness mapping of a copper plate is determined and the obtained values are in statistical agreement with the data measured by a mechanical profilometer. Second, the surface profiles of nickel alloy surfaces used as calibrated standards for the determination of Ra values are obtained. The measured Ra values statistically agree with the values of the different standards. Finally, the contact strains of a copper cylinder on glass are also measured. The contact strains follow the trend predicted by the K.L. Johnson’s model of contact. Local regions (asperities) experiment large plastic deformations.

Rapid identification of heterozygous mutations in Drosophila melanogaster using genomic capture sequencing

One of the key advantages of using Drosophila melanogaster as a genetic model organism is the ability to conduct saturation mutagenesis screens to identify genes and pathways underlying a given phenotype. Despite the large number of genetic tools developed to facilitate downstream cloning of mutations obtained from such screens, the current procedure remains labor intensive, time consuming, and costly. To address this issue, we designed an efficient strategy for rapid identification of heterozygous mutations in the fly genome by combining rough genetic mapping, targeted DNA capture, and second generation sequencing technology. We first tested this method on heterozygous flies carrying either a previously characterized dac(5) or sens(E2) mutation. Targeted amplification of genomic regions near these two loci was used to enrich DNA for sequencing, and both point mutations were successfully identified. When this method was applied to uncharacterized twr mutant flies, the underlying mutation was identified as a single-base mutation in the gene Spase18-21. This targeted-genome-sequencing method reduces time and effort required for mutation cloning by up to 80% compared with the current approach and lowers the cost to <$1000 for each mutant. Introduction of this and other sequencing-based methods for mutation cloning will enable broader usage of forward genetics screens and have significant impacts in the field of model organisms such as Drosophila.

Riparian Vegetation Mapping for Hydraulic Roughness Estimation Using Very High Resolution Remote Sensing Data Fusion

For detailed hydraulic modeling, accurate spatial information of riparian vegetation patterns needs to be derived in automatic fashion. We propose a supervised classification for heterogeneous riparian corridors with a low number of spectrally separate classes using data fusion of a Quickbird image and LIDAR data. The approach considers nine land cover classes including three woody riparian species, brush, cultivated areas, grassland, urban infrastructures, bare soil and water. The classical stacked vector approach is adopted for data fusion, while the nonparametric weighted feature-extraction method and the pixel-oriented maximum likelihood algorithm are used for feature-reduction and classification purposes, respectively. We test the approach over a 14-km stretch of the Sieve River (Tuscany Region, Italy). A one-dimensional river modeling is applied over the study reach comparing the results of a classification-derived hydraulic roughness map and a traditional ground-based approach. Despite the complex study reach, the classification method produced encouraging accuracies (OKS=0.77) and represents a useful tool to delineate application domains of flow resistance models suited to different hydrodynamic patterns (e.g., stiff/flexible vegetation). Hydraulic modeling results showed that the remotely derived floodplain roughness parameterization captures the equivalent Manning coefficient over 20 test cross sections with uncertainty distributions described by low mean and standard deviation values.

An expert system using rough sets theory and self-organizing maps to design space exploration of complex products

In complex product design, product performance driving design is a new and innovative research in the engineering field. For realizing the product performance driving design, an elaborated expert system, Expert Systems for Assisting Mapping from Performance Space to Design Space (ESMPD) is proposed, which have two main modules for mapping from product performance space to interesting design space by two layers mapping method. In Rough Sets Theory Analysis Module, Rough Sets Theory (RST) is used to calculate configuration rules in incomplete configuration information system to assist product designers in mapping performance space to configuration space. In self-organizing maps Analysis Module, SOM is employed to analyze design variables and objective function based on preliminary optimization, to mapping from the fixed configuration space to smaller interesting regions in design space. The contribution of this research is utilizing the product design knowledge to guide engineer to partition and reduce the design space, which can save product design time and promote the design efficiency. Finally, a new bulk carrier design is taken as a case study to prove the validity and necessity of this expert system. The detailed analysis testifies ESMPD can effectively facilitate rapid and intelligent design, and reduce the cost of complex product design.