bluuebunny/crossref_metadata_2025 huggingface dataset:
New Semisolid Casting of an Al-25Wt.% Mg2Si Composite Using Vibrating Cooling Slope
Authors: Saffari Shaya , Akhlaghi Farshad
Published: September 2014

Al-Mg2Si composites have gained considerable attention because of their attractive properties such as low density, improved wear resistance and good castability. However, when in-situ routes are used for processing of these composites, the formation of coarse Mg2Si particles with sharp cornersis inevitable and is detrimental for the composite properties. This problem is intensified when a hypereutectic composition such as Al-25wt.% Mg2Si alloy is processed. In the present study, an innovative semisolid technique termed as the Vibrating Cooling Slope (VCS) has been applied to produce a sample of in-situ Al-25wt.% Mg2Si composite.This technique combines the conventional cooling slope and vibration casting methods into an integrated one for producing fine and globular structures in the as-cast condition. An inclined plate was prepared from a 10mm thickness copper plate and was coated by boron nitride. This platecould vibrate mechanically in the vertical direction at a predetermined frequency by the aid of four springs and an electric motor. The molten Al-16.5wt.%Mg-9.4%Sialloy with 100oC superheat was poured on the surface of this cooling slope (set at 45° inclined angle)while it was vibrating at the frequency of 40 Hzandamplitude of 400 μm.The semisolid alloy travelled the length of 40 cm on the slope before being poured into a steel mold (60 mm internal diameter and 35 mm in height). Also for the purpose of comparison, gravity casting (GC) and conventionally still cooling slope casting (CS)were carried outboth using the same mold and with the same superheat.The samples were sectioned, polished and subjected to metallographicstudies,porosity and hardness measurements. It was concluded that CS and VCS techniques resulted in a decrease in the size of Mg2Si particles by about 50%and 70% respectively when compared with the gravity casting. However, the increased shape factor of Mg2Si particles in the VCS and CS processed samples was insignificant as compared with GC. Although in comparison with GC, the VCS processed sample showed a higher porosity level, it exhibited a higher hardness value. These results were attributed to the finer and modified microstructure obtained via this newly developed technique.
Effect of Semi-Solid Processing on Iron-Bearing Intermetallic Compounds in A380 Aluminum Alloy
Authors: Shabestari S.G. , Tavakoli M.M. , Ghanbari M.
Published: September 2014

Al-Si-Fe alloys are a general purpose of die casting alloys, widely used to manufacture automotive parts. Forming this alloy in semi-solid state can eliminate important problems in die casting process. In the present work, low superheat melt was employed to produce modified microstructure and non-dendritic A380 alloy feed stocks. The melt was cast on a cooling slope plate at 615 °C to obtain ingots. Then, ingots are thixoformed using a hydraulic press after heating them at 570 °C for 15 minutes, yielding a microstructure with predominantly α–Al globules, Si particles, and modified β-phase intermetallic compounds. The effect of semi-solid processing on the morphology, size, and distribution of iron-bearing intermetallics was studied. The results of image analysis of the samples showed that by using semi-solid method, the shape factor of α-Al phase improved, and iron containing intermetallics were modified in size and distribution. These changes in the aspect ratio and redistribution of the intermetallics improved the mechanical properties such as hardness of the products.
Morphological Evolution of SCN Crystals in a Shear Flow
Authors: Reisi Mehdi , Niroumand Behzad , Shirani Ebrahim
Published: September 2014

Morphological evolution of a transparent model succinonitrile (SCN) material during solidification was investigated in an apparatus resembling a shearing-disc viscometer. The in situ microscopic observations showed that fragmentation decreased the average particles size, but did not result in transition of dendritic to spherical morphology. At low shear rates, the degenerated dendrites and at high shear rates, the pseudo-cluster morphology was observed. It was revealed that coarsening has the most important effect on the final morphology of solid particles. The quantitative influences of shearing rate and intensity on the size and morphology of solid crystals were also discussed based on the measurements on the microstructures.
Gayatri Chakravorty Spivak: Live Theory
Authors: Sanders Mark
Published: September 2014

Gayatri Chakravorty Spivak: Live Theory offers a concise, comprehensive and accessible introduction to the themes central to the thought of one of the world's most provocative and original theorists. The book concentrates on Spivak's engagement, in theory and practice, with deconstruction, Marxism, feminism, and issues of postcoloniality and globalization, and makes clear the extent of her impact in the fields of postcolonial and literary theory. Gayatri Chakravorty Spivak: Live Theory is a key resource for anyone studying this pioneering thinker.
Technical Note: The horizontal scale dependence of the cloud overlap parameter α
Authors: Astin I. , Di Girolamo L.
Published: September 2014

Abstract. The cloud overlap parameter α relates the combined cloud fraction between two altitude levels in a grid box to the cloud fraction as derived under the maximum and random overlap assumptions. In a number of published studies in this and other journals, it is found that α tends to increase with an increasing scale. In this Technical Note, we investigate this analytically by considering what happens to α when two grid boxes are merged to give a grid box with twice the area. Assuming that α depends only on scale, then between any two fixed altitudes, there will be a linear relationship between the values of α on the two scales. We illustrate this by finding the relationship when cloud cover fractions are assumed to be uniformly distributed, but with varying degrees of horizontal and vertical correlation. Based on this, we conclude that α increases with scale if its value is less than the vertical correlation coefficient in cloud fraction between the two altitude levels. This occurs when the clouds are deeper than would be expected at random (i.e. for exponentially distributed cloud depths).
Aviation 2006 NOx-induced effects on atmospheric ozone and HOx in Community Earth System Model (CESM)
Authors: Khodayari A. , Tilmes S. , Olsen S. C. , Phoenix D. B. , Wuebbles D. J. , Lamarque J.-F. , Chen C.-C.
Published: September 2014

Abstract. The interaction between atmospheric chemistry and ozone (O3) in the upper troposphere–lower stratosphere (UTLS) presents a major uncertainty in understanding the effects of aviation on climate. In this study, two configurations of the atmospheric model from the Community Earth System Model (CESM), Community Atmosphere Model with Chemistry, Version 4 (CAM4) and Version 5 (CAM5), are used to evaluate the effects of aircraft nitrogen oxide (NOx = NO + NO2) emissions on ozone and the background chemistry in the UTLS. CAM4 and CAM5 simulations were both performed with extensive tropospheric and stratospheric chemistry including 133 species and 330 photochemical reactions. CAM5 includes direct and indirect aerosol effects on clouds using a modal aerosol module (MAM), whereby CAM4 uses a bulk aerosol module, which can only simulate the direct effect. To examine the accuracy of the aviation NOx-induced ozone distribution in the two models, results from the CAM5 and CAM4 simulations are compared to ozonesonde data. Aviation NOx emissions for 2006 were obtained from the AEDT (Aviation Environmental Design Tool) global commercial aircraft emissions inventory. Differences between simulated O3 concentrations and ozonesonde measurements averaged at representative levels in the troposphere and different regions are 13% in CAM5 and 18% in CAM4. Results show a localized increase in aviation-induced O3 concentrations at aviation cruise altitudes that stretches from 40° N to the North Pole. The results indicate a greater and more disperse production of aviation NOx-induced ozone in CAM5, with the annual tropospheric mean O3 perturbation of 1.2 ppb (2.4%) for CAM5 and 1.0 ppb (1.9%) for CAM4. The annual mean O3 perturbation peaks at about 8.2 ppb (6.4%) and 8.8 ppb (5.2%) in CAM5 and CAM4, respectively. Aviation emissions also result in increased hydroxyl radical (OH) concentrations and methane (CH4) loss rates, reducing the tropospheric methane lifetime in CAM5 and CAM4 by 1.69 and 1.40%, respectively. Aviation NOx emissions are associated with an instantaneous change in global mean short-term O3 radiative forcing (RF) of 40.3 and 36.5 mWm−2 in CAM5 and CAM4, respectively.
Large mixing ratios of atmospheric nitrous acid (HONO) at Concordia (East Antarctic Plateau) in summer: a strong source from surface snow?
Authors: Legrand M. , Preunkert S. , Frey M. , Bartels-Rausch Th. , Kukui A. , King M. D. , Savarino J. , Kerbrat M. , Jourdain B.
Published: September 2014

Abstract. During the austral summer 2011/2012 atmospheric nitrous acid (HONO) was investigated for the second time at the Concordia site (75°06' S, 123°33' E), located on the East Antarctic Plateau, by deploying a long-path absorption photometer (LOPAP). Hourly mixing ratios of HONO measured in December 2011/January 2012 (35 ± 5.0 pptv) were similar to those measured in December 2010/January 2011 (30.4 ± 3.5 pptv). The large value of the HONO mixing ratio at the remote Concordia site suggests a local source of HONO in addition to weak production from oxidation of NO by the OH radical. Laboratory experiments demonstrate that surface snow removed from Concordia can produce gas-phase HONO at mixing ratios half that of the NOx mixing ratio produced in the same experiment at typical temperatures encountered at Concordia in summer. Using these lab data and the emission flux of NOx from snow estimated from the vertical gradient of atmospheric concentrations measured during the campaign, a mean diurnal HONO snow emission ranging between 0.5 and 0.8 × 109 molecules cm−2 s−1 is calculated. Model calculations indicate that, in addition to around 1.2 pptv of HONO produced by the NO oxidation, these HONO snow emissions can only explain 6.5 to 10.5 pptv of HONO in the atmosphere at Concordia. To explain the difference between observed and simulated HONO mixing ratios, tests were done both in the field and at lab to explore the possibility that the presence of HNO4 had biased the measurements of HONO.
Aged boreal biomass burning aerosol size distributions from BORTAS 2011
Authors: Sakamoto K. M. , Allan J. D. , Coe H. , Taylor J. W. , Duck T. J. , Pierce J. R.
Published: September 2014

Abstract. Biomass-burning aerosols contribute to aerosol radiative forcing on the climate system. The magnitude of this effect is partially determined by aerosol size distributions, which are functions of source fire characteristics (e.g. fuel type, MCE) and in-plume microphysical processing. The uncertainties in biomass-burning emission number size-distributions in climate model inventories lead to uncertainties in the CCN concentrations and forcing estimates derived from these models. The BORTAS-B measurement campaign was designed to sample boreal biomass-burning outflow over Eastern Canada in the summer of 2011. Using these BORTAS-B data, we implement plume criteria to isolate the characteristic size-distribution of aged biomass-burning emissions (aged ∼1–2 days) from boreal wildfires in Northwestern Ontario. The composite median size-distribution yields a single dominant accumulation mode with Dpm = 230 nm (number-median diameter), σ = 1.7, which are comparable to literature values of other aged plumes of a similar type. The organic aerosol enhancement ratios (ΔOA / ΔCO) along the path of Flight b622 show values of 0.05–0.18 μg m−3 ppbv−1 with no significant trend with distance from the source. This lack of enhancement ratio increase/decrease with distance suggests no detectable net OA production/evaporation within the aged plume over the sampling period. A Lagrangian microphysical model was used to determine an estimate of the freshly emitted size distribution corresponding to the BORTAS-B aged size-distributions. The model was restricted to coagulation and dilution processes based on the insignificant net OA production/evaporation derived from the ΔOA / ΔCO enhancement ratios. We estimate that the fresh-plume median diameter was in the range of 59–94 nm with modal widths in the range of 1.7–2.8 (the ranges are due to uncertainty in the entrainment rate). Thus, the size of the freshly emitted particles is relatively unconstrained due to the uncertainties in the plume dilution rates.
Quality assessment of ozone total column amounts as monitored by ground-based solar absorption spectrometry in the near infrared (> 3000 cm−1)
Authors: García O. E. , Schneider M. , Hase F. , Blumenstock T. , Sepúlveda E. , González Y.
Published: September 2014

Abstract. This study examines the possibility of ground-based remote-sensing ozone total column amounts (OTC) from spectral signatures at 3040 and 4030 cm−1. These spectral regions are routinely measured by the NDACC (Network for the Detection of Atmospheric Composition Change) ground-based FTIR (Fourier transform infraRed) experiments. In addition, they are potentially detectable by the TCCON (Total Carbon Column Observing Network) FTIR instruments. The ozone retrieval strategy presented here estimates the OTC from NDACC FTIR high-resolution spectra with a theoretical precision of about 2 and 5% in the 3040 and 4030 cm−1 regions, respectively. Empirically, these OTC products are validated by inter-comparison to FTIR OTC reference retrievals in the 1000 cm−1 spectral region (standard reference for NDACC ozone products), using an 8-year FTIR time series (2005–2012) taken at the subtropical ozone supersite of the Izaña Atmospheric Observatory (Tenerife, Spain). Associated with the weaker ozone signatures at the higher wave number regions, the 3040 and 4030 cm−1 retrievals show lower vertical sensitivity than the 1000 cm−1 retrievals. Nevertheless, we observe that the rather consistent variations are detected: the variances of the 3040 cm−1 and the 4030 cm−1 retrievals agree within 90 and 75%, respectively, with the variance of the 1000 cm−1 standard retrieval. Furthermore, all three retrievals show very similar annual cycles. However, we observe a large systematic difference of about 7% between the OTC obtained at 1000 and 3040 cm−1, indicating a significant inconsistency between the spectroscopic ozone parameters (HITRAN, 2012) of both regions. Between the 1000 cm and the 4030 cm−1 retrieval the systematic difference is only 2–3%. Finally, the long-term stability of the OTC retrievals has also been examined, observing that both near-infrared retrievals can monitor the long-term OTC evolution, consistent with the 1000 cm−1 reference data. These findings demonstrate that recording the solar absorption spectra in the 3000 cm−1 spectral region at high spectral resolution (about 0.005 cm−1) might be useful for TCCON sites. Hence, both NDACC and TCCON ground-based FTIR experiments might contribute to global ozone databases.
Updated estimates of carbon accumulation rates in coastal marsh sediments
Authors: Ouyang X. , Lee S. Y.
Published: September 2014

Abstract. Studies on carbon stock in salt marsh sediments have increased since the review by Chmura et al. (2003). However, uncertainties exist in estimating global carbon storage in these vulnerable coastal habitats, thus hindering the assessment of their importance. Combining direct data and indirect estimation, this study compiled studies involving 143 sites across the Southern and Northern hemispheres, and provides an updated estimate of the global average carbon accumulation rate (CAR) at 244.7 g C m−2 yr−1 in salt marsh sediments. Based on region-specific CAR and estimates of salt marsh area in various geographic regions between 40° S to 69.7° N, total CAR in global salt marsh sediments is estimated at ~10.2 Tg C yr−1. Latitude, tidal range and elevation appear to be important drivers for CAR of salt marsh sediments, with considerable variation among different biogeographic regions. The data indicate that while the capacity for carbon sequestration by salt marsh sediments ranked the first amongst coastal wetland and forested terrestrial ecosystems, their carbon budget was the smallest due to their limited and declining global areal extent. However, some uncertainties remain for our global estimate owing to limited data availability.
Quantitative estimation and vertical partitioning of the soil carbon dioxide fluxes at the hillslope scale on a loess soil
Authors: Wiaux F. , Van Oost K. , Vanclooster M.
Published: September 2014

Abstract. Both modelling and experimental approaches have been applied to assess C exchange fluxes at large spatial scales. Yet, these approaches are subjected to substantial limitations and uncertainties. Here, we aim to highlight two key mechanisms able to improve the estimation of the hillslope aggregated CO2 fluxes: (i) the persistence of soil organic carbon (OC) in deep colluvium deposits; and (ii) the physical controls on CO2 fluxes along soil profiles. This study focuses on a sloping cropland in the central loess belt of Belgium. On two contrasted soil types along the studied hillslope, we recorded time-series of CO2 concentration, water content and temperature along 1 m long soil profiles during two periods of 6 months. Then, we calculated profiles of CO2 fluxes using the gradient method. To extrapolate these fluxes to entire yearly periods (2011–2013), we performed simulation using the SOILCO2RothC model. The vertical partitioning of the soil CO2 fluxes shows that ca. 90 to ca. 95% of the surface CO2 fluxes originates from the 10 first centimeters of the soil profile at the footslope. We show that high water filled pore space at this slope position disables the transfer of biotic CO2 along the soil profile. However, the total annual flux averaged along 3 years of simulation show that the top soil layer (0–10 cm) of the footslope generates CO2 fluxes (870 ± 64 CO2-C m−2 year−1 which exceed those observed at the summit position (583 ± 61 CO2-C m−2 year−1. Hence, our results reconcile two seemingly contradictory hypotheses, i.e. (i) these support that soil OC at such a footslope is stored along the main part of the soil profile and submitted to a long-term stabilization, and (ii) at the same time these support that the depositional footslope profile emits more CO2 than the summit, due to its high amount and quality of OC. Our results support the need to consider slopes when modeling soil-atmosphere C exchanges. If landscapes dynamic processes are not accounted for, we pointed out a risk to under-estimate annual soil-atmosphere CO2 exchanges by ca. 20%.
Natural periodicities and Northern Hemisphere–Southern Hemisphere connection of fast temperature changes during the last glacial period: EPICA and NGRIP revisited
Authors: Alberti T. , Lepreti F. , Vecchio A. , Bevacqua E. , Capparelli V. , Carbone V.
Published: September 2014

Abstract. We investigate both the European Project for Ice Coring in Antarctica Dronning Maud Land (EDML) and North Greenland Ice-Core Project (NGRIP) data sets to study both the time evolution of the so-called Dansgaard–Oeschger events and the dynamics at longer timescales during the last glacial period. Empirical mode decomposition (EMD) is used to extract the proper modes of both the data sets. It is shown that the time behavior at the typical timescales of Dansgaard–Oeschger events is captured through signal reconstructions obtained by summing five EMD modes for NGRIP and four EMD modes for EDML. The reconstructions obtained by summing the successive modes can be used to describe the climate evolution at longer timescales, characterized by intervals in which Dansgaard–Oeschger events happen and intervals when these are not observed. Using EMD signal reconstructions and a simple model based on the one-dimensional Langevin equation, it is argued that the occurrence of a Dansgaard–Oeschger event can be described as an excitation of the climate system within the same state, while the longer timescale behavior appears to be due to transitions between different climate states. Finally, on the basis of a cross-correlation analysis performed on EMD reconstructions, evidence that the Antarctic climate changes lead those of Greenland by a lag of ≈ 3.05 kyr is presented.
Evaluation of vegetation indices for rangeland biomass estimation in the Kimberley area of Western Australia
Authors: Mundava C. , Helmholz P. , Schut A. G. T. , Corner R. , McAtee B. , Lamb D. W.
Published: September 2014

Abstract. The objective of this paper is to test the relationships between Above Ground Biomass (AGB) and remotely sensed vegetation indices for AGB assessments in the Kimberley area in Western Australia. For 19 different sites, vegetation indices were derived from eight Landsat ETM+ scenes over a period of two years (2011–2013). The sites were divided into three groups (Open plains, Bunch grasses and Spinifex) based on similarities in dominant vegetation types. Dry and green biomass fractions were measured at these sites. Single and multiple regression relationships between vegetation indices and green and total AGB were calibrated and validated using a "leave site out" cross validation. Four tests were compared: (1) relationships between AGB and vegetation indices combining all sites; (2) separate relationships per site group; (3) multiple regressions including selected vegetation indices per site group; and (4) as in 3 but including rainfall and elevation data. Results indicate that relationships based on single vegetation indices are moderately accurate for green biomass in wide open plains covered with annual grasses. The cross-validation results for green AGB improved for a combination of indices for the Open plains and Bunch grasses sites, but not for Spinifex sites. When rainfall and elevation data are included, cross validation improved slightly with a Q2 of 0.49–0.72 for Open plains and Bunch grasses sites respectively. Cross validation results for total AGB were moderately accurate (Q2 of 0.41) for Open plains but weak or absent for other site groups despite good calibration results, indicating strong influence of site-specific factors.
Incorporating uncertanity into Markov random field classification with the combine use of optical and SAR images and aduptive fuzzy mean vector
Authors: Welikanna D. R. , Tamura M. , Susaki J.
Published: September 2014

Abstract. A Markov Random Field (MRF) model accounting for the classification uncertainty using multisource satellite images and an adaptive fuzzy class mean vector is proposed in this study. The work also highlights the initialization of the class values for an MRF based classification for synthetic aperture radar (SAR) images using optical data. The model uses the contextual information from the optical image pixels and the SAR pixel intensity with corresponding fuzzy grade of memberships respectively, in the classification mechanism. Sub pixel class fractions estimated using Singular Value Decomposition (SVD) from the optical image initializes the class arrangement for the MRF process. Pair-site interactions of the pixels are used to model the prior energy from the initial class arrangement. Fuzzy class mean vector from the SAR intensity pixels is calculated using Fuzzy C-means (FCM) partitioning. Conditional probability for each class was determined by a Gamma distribution for the SAR image. Simulated annealing (SA) to minimize the global energy was executed using a logarithmic and power-law combined annealing schedule. Proposed technique was tested using an Advanced Land Observation Satellite (ALOS) phased array type L-band SAR (PALSAR) and Advanced Visible and Near-Infrared Radiometer-2 (AVNIR-2) data set over a disaster effected urban region in Japan. Proposed method and the conventional MRF results were evaluated with neural network (NN) and support vector machine (SVM) based classifications. The results suggest the possible integration of an adaptive fuzzy class mean vector and multisource data is promising for imprecise class discrimination using a MRF based classification.
Masked Correlation for Improvement of 2D Glacier Motion Estimation Based on Terrasar-x Imagery
Authors: Fang L. , Stilla U.
Published: September 2014

Abstract. In this paper, the impacts of the non-glacier information in the template window used in cross-correlation calculation for 2D motion estimation of glaciers are discussed and illustrated by the example of the Taku glacier, which is the biggest glacier in the Juneau Icefield, Alaska. For this, the glacier motion maps are extracted by the traditional normalized cross-correlation technique and the masked cross-correlation method, which uses a manually generated binary mask to threshold the non-glacier pixels, based on geocoded high resolution TerraSAR-X images. Based on the comparison of the different results, it was found that without the disturbing information (e.g., mountain, water) the accuracy of the cross-correlation of sequential patches in masked cross-correlation method is improved and the estimation results are much more reasonable, which respect the law that glacier flows like a river with higher velocity in the middle and than that in the sides.
Fusion of high resolution remote sensing images and terrestrial laser scanning for improved biomass estimation of maize
Authors: Hütt C. , Schiedung H. , Tilly N. , Bareth G.
Published: September 2014

Abstract. In this study, images from the satellite system WorldView-2 in combination with terrestrial laser scanning (TLS) over a maize field in Germany are investigated. Simultaneously to the measurements a biomass field campaigns was carried out. From the point clouds of the terrestrial laser scanning campaigns crop surface models (CSM) from each scanning date were calculate to model plant growth over time. These results were resampled to match the spatial resolution of the WorldView-2 images, which had to orthorectified using a high resolution digital elevation model and atmosphere corrected using the ATCOR Software package. A high direct correlation of the NDVI calculated from the WorldView-2 sensor and the dry biomass was found in the beginning of June. At the same date, the heights from laser scanning can also explain a certain amount of the biomass variation (r2 = 0.6). By combining the NDVI from WorldView-2 and the height from the laser scanner with a linear model, the R2 reaches higher values of 0.86. To further understand the relationship between CSM derived crop heights and reflection indices, a comparison on a pixel basis was performed. Interestingly, the correlation of the NDVI and the crop height is rather low at the beginning of June (r2 = 0,4, n = 1857) and increases significantly (R2 = 0,79, N = 1857) at a later stage.
Lidar Processing for Defining Sinkhole Characteristics under Dense Forest Cover: A Case Study in the Dinaric Mountains
Authors: Kobal M. , Bertoncelj I. , Pirotti F , Kutnar L.
Published: September 2014

Abstract. The traditional approach for defining sinkholes characteristics is based on topographic maps and air photographs with derived digital terrain models. This method is sometimes not accurate, requiring costly, time consuming and potentially dangerous fieldwork. Investigations have shown that airborne scanning laser data (lidar) is useful in detection of karst depressions due to the high density of ground points that can be obtained. This is especially important under dense forest canopy, where classical photogrammetric methods do not allow ground points to be measured. The objective of this work was to map and determine geomorphometric characteristics of a large number of sinkholes located in a diverse karst terrain under a dense forest tree-canopy using lidar data. We tested an algorithm described in previous literature which uses only information from the DTM. It is based on water flow simulations on a surface (DTM) and incorporates four phases: (i) watershed delineation, (ii) confining of sinkholes, (iii) confining of higher rank sinkholes and (iv) extraction of non-karstic sinkholes. Sinkholes were confined by effluent level with cells below the effluent level designated as part of the sinkhole. In the third step sinkholes were ranked according to their location and size – first rank sinkholes are the smallest and are located within a larger sinkhole. Results are that the sinkhole fraction of 1st, 2nd, 3rd, 4th and 5th rank in the study area was 3.25 %, 4.26 %, 5.68 %, 3.65 % and 3.14 %, respectively. Sinkhole distribution shows a peculiar directionality in their spatial distribution, which seems to be significantly towards a northwest – southeast direction. It was not possible to compare results with ground-truth data due to very low accessibility, nevertheless a statistical and visual assessment of the results shows that lidar is a very effective technique to model sinkholes under dense canopy.
The backscattering characteristics of thermokarst lake ice in the qinghai-tibet plateau from SAR
Authors: Li Z. , Tian B. , Tang P.
Published: September 2014

Abstract. A thermokarst lake is an important indicator of changes in climate, which cause considerable thermal distribution to the surrounding permafrost. The imaging radar has demonstrated the capability to determine when and which lakes freeze or do not freeze. In this paper, the temporal variability of C-band backscattering of thermokarst lakes at Beiluhe test area, is located on the central Qinghai- Tibet Plateau (QTP), were examined by 45 ENVISAT-ASAR imageries acquired in freeze up, ice duration and break-up stages. The SAR behaviour response for lake ice change are analysed with ASAR observation in experiments area. The results showed that the ice layer volume scattering and ice-water surface scattering were the two major scattering components in C-band VV polarization, which is also affected by the increase of bubble size, ice density and roughness of ice-water interface. According to this study, the timing of lake ice-on in fall and ice-off in spring for this geographic region can be identified in radar images by comparing radar backscatter from lake ice to its surrounding alpine meadow. When ice duration, the radar signature proved to be able to monitor the ice thickness over lake and deformation around the lake.
GeoEtrim, SharpQ and Epix: Trio of Tools for Geospatial Image Analysis
Authors: Topan H. , Özendi M. , Cam A. , Oruç M.
Published: September 2014

Abstract. This paper presents an overview of three approaches developed in Matlab for geospatial analysis of images. GeoEtrim has two subpackages, GeoSpot and GeoFigcon. GeoSpot aims to perform bundle adjustment of stereo linear array remotely sensed images considering their interior and exterior orientation parameters. The correlation among orientation parameters, their validation and efficiency on the final accuracy can be estimated. The current version is available for SPOT-5 HRG level 1A stereoimages, reaching ±1 pixel accuracy at ICPs (Independent Check Points). GeoFigcon is the other sub-package of GeoEtrim, developed for estimation of georeferencing accuracy of orthoimages generated by various sensor-independent mathematical models and RFM (Rational Function Model). Using GeoFigcon, one can estimate the combined effect of the accuracy of transformation parameters estimated/updated by GCPs and DEM accuracy on the georeferencing accuracy of orthoimages. The experiments with IKONOS Geo, QuickBird OrthoReady Standard, OrbView-3 Basic and Pléiades-1A Primary prove that using RFM produces higher accuracy than using sensor-independent transformation models. Moreover, accuracy varies reducing from geometric centre of GCPs accommodating the high profile of topography. SharpQ generates pan-sharp images using the methods PCA (Principal Component Analysis), Brovey, and IHS (Intensity Hue Saturation), validates their quality with quantitative analysis by the methods CC (Correlation Coefficient), RMSE (Root Mean Square Error), RASE (Relative Average Spectral Error), SAM (Spectral Angle Mapper) and ERGAS (Erreur Relative Globale Adimensionnelle de Synthése). epix, the last member of the trio, can be used for estimation of effective GSD (Ground Sampling Distance) value of original or generated (such as pan-sharp) images, depending the principle of ESF (Edge Spread Function). So the real geometric resolution can be estimated for any kind of image. This trio is being still developed with the continuous research.
Investigating Performance Of Airborne Lidar Data Filtering With Triangular Irregular Network (TIN) Algorithm
Authors: Uysal M. , Polat N.
Published: September 2014

Abstract. Digital Elevation Model (DEM) is an important topographic product and essential demand for many applications. Traditional methods for creating DEM are very costly and time consuming because of land surveying. In time, Photogrammetry has become one of the major methods to generate DEM. Recently, airborne Light Detection and Ranging (LIDAR) system has become a powerful way to produce a DEM due to advantage of collecting three-dimensional information very effectively over a large area by means of precision and time. Airborne LIDAR system collects information not only from land surface but also from every object between plane and terrain that can reflect the laser beam. So filtering out nonground points from raw point clouds is the major step of DEM generation. There are many filtering algorithm due to several factors that affect the filtering prosedures. The performanses of these filters change based on the topographic features of area.One of these algorithm is called Triangular Irregular Network (TIN). In this study the TIN algorithm is used to filter Lidar point cloud that are collected from two different sites. While one of these sites is a rural area, the other site is an urban area; therefore these sites have different topographic features. In addition, the reference DEMs are available for these sites. In order to test the performance of TIN algorithm, the Lidar point clouds are filtered and used to generate DEM for the sites. Finally, the generated DEM are compared with the reference DEM for each site. The comparison results show that the TIN filtering algorithm perform more effectively in urban area than rural area in terms of correlations with reference DEMs.
Analysis on light quantity and quality based on diverse cloud conditions
Authors: Yamashita M. , Yoshimura M.
Published: September 2014

Abstract. Photosynthetic active radiation (PAR) is the source of incident light energy for the photosynthetic activity of plants. PAR additionally characterizes the light environment on the surface of the Earth. The light environment is an important factor for estimating quantities such as carbon exchange and the productivities of forests and agriculture. The incident PAR on the ground surface has the characteristics of light quantity consists of direct and diffuse components, and of light quality consists of spectral components such blue, green and red lights. These light quantity and quality are also important light environmental factors in the photosynthetic activities of plants under the natural environment. However, the light environment including direct and diffuse components and spectral components is easily affected by cloud conditions especially cloud cover and its movements. In this paper, we focus on the characteristics of the light quantity and quality under diverse cloud conditions, and analyse the observational data, which are the global- and diffuse- spectral irradiances from 400 to 700 nm with quantum and energy units and the cloud conditions derived from whole-sky images taken during summer in Kyoto city. As for the comparisons with light quality and cloud conditions, we use the Normalized Difference PAR Spectral Index (NDPSI) which shows the difference of red- and blue-light components and we use cloud cover and the Sun appearance ratio derived from the wholesky images to define the cloud conditions. As the results of these analyses, we confirmed that there are the clear relationships between cloud cover and diffuse ratio, between the Sun appearance ratio and the normalized global PAR as the light quantity, between cloud cover and NDPSI in diffuse component, and between the Sun appearance ratio and NDPSI in direct component as the light quality.
Rapid Disaster Analysis based on Remote Sensing: A Case Study about the Tohoku Tsunami Disaster 2011
Authors: Yang C.H. , Soergel U. , Lanaras Ch. , Baltsavias E. , Cho K. , Remondino F. , Wakabayashi H.
Published: September 2014

Abstract. In this study, we present first results of RAPIDMAP, a project funded by European Union in a framework aiming to foster the cooperation of European countries with Japan in R&D. The main objective of RAPIDMAP is to construct a Decision Support System (DSS) based on remote sensing data and WebGIS technologies, where users can easily access real-time information assisting with disaster analysis. In this paper, we present a case study of the Tohoku Tsunami Disaster 2011. We address two approaches namely change detection based on SAR data and co-registration of optical and SAR satellite images. With respect to SAR data, our efforts are subdivided into three parts: (1) initial coarse change detection for entire area, (2) flood area detection, and (3) linearfeature change detection. The investigations are based on pre- and post-event TerraSAR-X images. In (1), two pre- and post-event TerraSAR-X images are accurately co-registered and radiometrically calibrated. Data are fused in a false-color image that provides a quick and rough overview of potential changes, which is useful for initial decision making and identifying areas worthwhile to be analysed further in more depth. However, a bunch of inevitable false alarms appear within the scene caused by speckle, temporal decorrelation, co-registration inaccuracy and so on. In (2), the post-event TerraSAR-X data are used to extract the flood area by using thresholding and morphological approaches. The validated result indicates that using SAR data combining with suitable morphological approaches is a quick and effective way to detect flood area. Except for usage of SAR data, the false-color image composed of optical images are also used to detect flood area for further exploration in this part. In (3), Curvelet filtering is applied in the difference image of pre- and post-event TerraSAR-X images not only to suppress false alarms of irregular-features, but also to enhance the change signals of linear-features (e.g. buildings) in settlements. Afterwards, thresholding is exploited to extract the linear-feature changes. In rapid mapping of disasters various sensors are often employed, including optical and SAR, since they provide complementary information. Such data needs to be analyzed in an integrated fashion and the results from each dataset should be integrated in a GIS with a common coordinate reference system. Thus, if no orthoimages can be generated, the images should be co-registered employing matching of common features. We present results of co-registration between optical (FORMOSAT-2) and TerraSAR-X images based on different matching methods, and also techniques for detecting and eliminating matching errors.
A Consideration for the Light Environmental Modeling under Tropical Rainforest Canopies
Authors: Yoshimura M. , Yamashita M.
Published: September 2014

Abstract. Photosynthetic Active Radiation (PAR) is the most important light source for plant photosynthesis. It is known that most of PAR from solar radiation is well absorbed by the surface. The canopy is the surface in forest region, consists an aboveground portion of plant community and formed by plant crowns. On the other hand, incident solar radiation is fluctuating at all times because of fluctuating sky conditions. Therefore, qualitative light environmental measurements in forest are recommended to execute under stable cloudy condition. In fact, it is quite a few opportunities to do under this sky condition. It means that the diffuse light condition without the direct light is only suitable for this measurement. In this study, we challenged the characterization the forest light environment as its representativeness under no consideration of sky conditions through analysis huge quantities of instantaneous data which obtained under the different sky conditions. All examined data were obtained under the different sky conditions at the tropical rainforest canopy as one of the typical fluctuating sky conditions regions. An incident PAR is transmitted and scattered by different forest layers at different heights. Various PAR data were measured with quantum units as Photosynthetic Photon Flux Density (PPFD) at different forest heights by the quantum sensors. By comparing PPFDs at different heights with an incident PPFD, relative PPFDs were calculated, which indicate the degree of PPFD decrease from the canopy top to lower levels. As the results of these considerations, daily averaging is confirmed to be cancelled sky fluctuating influences.
New SAR Interferogram denoising method via sparse recovery based on L0 norm
Authors: Ben Abdallah W. , Abdelfattah R.
Published: September 2014

Abstract. The goal of this paper is to estimate a denoised phase image from the observed noisy SAR interferogram. We proposed a linear model to obtain a sparse representation of the interferomteric phase image. The main idea is based on the smoothness property of the phases inside interferometric fringes which leads to get a sparse image when applying the gradient operator twice, along x or y direction, on the interferogram. The new sparse representation of the interferometric phase image allows to transform the denoising problem to an optimization one. So the estimated interferogram is achieved using the approximate message passing algorithm. The proposed approach is validated on different cases of simulated and real interferograms.
Evaluating the potential of consumer-grade smart cameras for low-cost stereo-photogrammetric Crop-Surface Monitoring
Authors: Brocks S. , Bareth G.
Published: September 2014

Abstract. Crop-Surface-Models (CSMs) are a useful tool for monitoring in-field crop growth variability, thus enabling precision agriculture which is necessary for achieving higher agricultural yields. This contribution provides a first assessment on the suitability of using consumer-grade smart cameras as sensors for the stereoscopic creation of crop-surface models using oblique imagery acquired from ground-based positions. An application that automates image acquisition and transmission was developed. Automated image acquisition took place throughout the growing period of barley in 2013. For three dates where both automated image acquisition and manual measurements of plant height were available, CSMs were generated using a combination of AgiSoft PhotoScan and Esri ArcGIS. The coefficient of determination R2 between the average of the manually measured plant heights per plots and the average height of the developed crop surface models was 0.61 (n = 24). The overall correlation between the manually measured heights and the CSM-derived heights is 0.78. The average per plot of the manually measured plant heights in the timeframe covered by the generated CSMs range from 19 to 95 cm, while the average plant height per plot of the generated CSMs range from 2.1 to 69 cm. These first results show that the presented approach is feasible.
Automatic Training Sample Selection for a Multi-Evidence Based Crop Classification Approach
Authors: Chellasamy M. , Ty Ferre P. A. , Humlekrog Greve M.
Published: September 2014

Abstract. An approach to use the available agricultural parcel information to automatically select training samples for crop classification is investigated. Previous research addressed the multi-evidence crop classification approach using an ensemble classifier. This first produced confidence measures using three Multi-Layer Perceptron (MLP) neural networks trained separately with spectral, texture and vegetation indices; classification labels were then assigned based on Endorsement Theory. The present study proposes an approach to feed this ensemble classifier with automatically selected training samples. The available vector data representing crop boundaries with corresponding crop codes are used as a source for training samples. These vector data are created by farmers to support subsidy claims and are, therefore, prone to errors such as mislabeling of crop codes and boundary digitization errors. The proposed approach is named as ECRA (Ensemble based Cluster Refinement Approach). ECRA first automatically removes mislabeled samples and then selects the refined training samples in an iterative training-reclassification scheme. Mislabel removal is based on the expectation that mislabels in each class will be far from cluster centroid. However, this must be a soft constraint, especially when working with a hypothesis space that does not contain a good approximation of the targets classes. Difficulty in finding a good approximation often exists either due to less informative data or a large hypothesis space. Thus this approach uses the spectral, texture and indices domains in an ensemble framework to iteratively remove the mislabeled pixels from the crop clusters declared by the farmers. Once the clusters are refined, the selected border samples are used for final learning and the unknown samples are classified using the multi-evidence approach. The study is implemented with WorldView-2 multispectral imagery acquired for a study area containing 10 crop classes. The proposed approach is compared with the multi-evidence approach based on training samples selected randomly and border samples based on initial cluster centroids within agricultural parcels without any refinement. The results clarify the improvement in overall classification accuracy to 82.3 % based on the proposed approach from 74.9 % based on random selection and 71.4% on non-refined border samples.
Performance Comparison Of Evolutionary Algorithms For Image Clustering
Authors: Civicioglu P. , Atasever U. H. , Ozkan C. , Besdok E. , Karkinli A. E. , Kesikoglu A.
Published: September 2014

Abstract. Evolutionary computation tools are able to process real valued numerical sets in order to extract suboptimal solution of designed problem. Data clustering algorithms have been intensively used for image segmentation in remote sensing applications. Despite of wide usage of evolutionary algorithms on data clustering, their clustering performances have been scarcely studied by using clustering validation indexes. In this paper, the recently proposed evolutionary algorithms (i.e., Artificial Bee Colony Algorithm (ABC), Gravitational Search Algorithm (GSA), Cuckoo Search Algorithm (CS), Adaptive Differential Evolution Algorithm (JADE), Differential Search Algorithm (DSA) and Backtracking Search Optimization Algorithm (BSA)) and some classical image clustering techniques (i.e., k-means, fcm, som networks) have been used to cluster images and their performances have been compared by using four clustering validation indexes. Experimental test results exposed that evolutionary algorithms give more reliable cluster-centers than classical clustering techniques, but their convergence time is quite long.