bluuebunny/crossref_metadata_2025 huggingface dataset:
IMPLEMENTATION OF AN AGRICULTURAL ENVIRONMENTAL INFORMATION SYSTEM (AEIS) FOR THE SANJIANG PLAIN, NE-CHINA
Authors: Zhao Q. , Brocks S. , Lenz-Wiedemann V. , Miao Y. , Jiang R. , Chen X. , Zhang F. , Bareth G.
Published: August 2012

Abstract. The Sino-German Project between the China Agricultural University and the University of Cologne, Germany, focuses on regional agro-ecosystem modelling. One major focus of the cooperation activity is the establishment of joint rice field experiment research in Jiansanjiang, located in the Sanjiang Plain (Heilongjiang Province, north-eastern part of China), to investigate the different agricultural practices and their impact on yield and environment. An additional task is to set-up an Agricultural Environmental Information System (AEIS) for the Sanjiang Plain (SJP), which covers more than 100 000 km2. Research groups from Geography (e.g. GIS & Remote Sensing) and Plant Nutrition (e.g. Precision Agriculture) are involved in the project. The major aim of the AEIS for the SJP is to provide information about (i) agriculture in the region, (ii) the impact of agricultural practices on the environment, and (iii) simulation scenarios for sustainable strategies. Consequently, the AEIS for the SJP provides information for decision support and therefore could be regarded as a Spatial Decision Support System (SDSS), too. The investigation of agricultural and environmental issues has a spatial context, which requires the management, handling, and analysis of spatial data. The use of GIS enables the capture, storage, analysis and presentation of spatial data. Therefore, GIS is the major tool for the set-up of the AEIS for the SJP. This contribution presents the results of linking agricultural statistics with GIS to provide information about agriculture in the SJP and discusses the benefits of this method as well as the integration of methods to produce new data.
SPECIES-SPECIFIC FOREST VARIABLE ESTIMATION USING NON-PARAMETRIC MODELING OF MULTI-SPECTRAL PHOTOGRAMMETRIC POINT CLOUD DATA
Authors: Bohlin J. , Wallerman J. , Olsson H. , Fransson J. E. S.
Published: August 2012

Abstract. The recent development in software for automatic photogrammetric processing of multispectral aerial imagery, and the growing nation-wide availability of Digital Elevation Model (DEM) data, are about to revolutionize data capture for forest management planning in Scandinavia. Using only already available aerial imagery and ALS-assessed DEM data, raster estimates of the forest variables mean tree height, basal area, total stem volume, and species-specific stem volumes were produced and evaluated. The study was conducted at a coniferous hemi-boreal test site in southern Sweden (lat. 58° N, long. 13° E). Digital aerial images from the Zeiss/Intergraph Digital Mapping Camera system were used to produce 3D point-cloud data with spectral information. Metrics were calculated for 696 field plots (10 m radius) from point-cloud data and used in k-MSN to estimate forest variables. For these stands, the tree height ranged from 1.4 to 33.0 m (18.1 m mean), stem volume from 0 to 829 m3 ha-1 (249 m3 ha-1 mean) and basal area from 0 to 62.2 m2 ha-1 (26.1 m2 ha-1 mean), with mean stand size of 2.8 ha. Estimates made using digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet) showed RMSEs (in percent of the surveyed stand mean) of 7.5% for tree height, 11.4% for basal area, 13.2% for total stem volume, 90.6% for pine stem volume, 26.4 for spruce stem volume, and 72.6% for deciduous stem volume. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.
APPLICATION OF SPATIAL MODELLING APPROACHES, SAMPLING STRATEGIES AND 3S TECHNOLOGY WITHIN AN ECOLGOCIAL FRAMWORK
Authors: Chen H.-C. , Lo N.-J. , Chang W.-I. , Huang K.-Y.
Published: August 2012

Abstract. How to effectively describe ecological patterns in nature over broader spatial scales and build a modeling ecological framework has become an important issue in ecological research. We test four modeling methods (MAXENT, DOMAIN, GLM and ANN) to predict the potential habitat of Schima superba (Chinese guger tree, CGT) with different spatial scale in the Huisun study area in Taiwan. Then we created three sampling design (from small to large scales) for model development and validation by different combinations of CGT samples from aforementioned three sites (Tong-Feng watershed, Yo-Shan Mountain, and Kuan-Dau watershed). These models combine points of known occurrence and topographic variables to infer CGT potential spatial distribution. Our assessment revealed that the method performance from highest to lowest was: MAXENT, DOMAIN, GLM and ANN on small spatial scale. The MAXENT and DOMAIN two models were the most capable for predicting the tree's potential habitat. However, the outcome clearly indicated that the models merely based on topographic variables performed poorly on large spatial extrapolation from Tong-Feng to Kuan-Dau because the humidity and sun illumination of the two watersheds are affected by their microterrains and are quite different from each other. Thus, the models developed from topographic variables can only be applied within a limited geographical extent without a significant error. Future studies will attempt to use variables involving spectral information associated with species extracted from high spatial, spectral resolution remotely sensed data, especially hyperspectral image data, for building a model so that it can be applied on a large spatial scale.
DEVELOPING A 3D WAVEFORM LIDAR SIMULATOR FOR FOREST
Authors: Endo T. , Sawada Y. , Kobayashi T. , Sawada H.
Published: August 2012

Abstract. Waveform LiDAR systems is widely used in several fields such as terrain survey, disaster monitoring and forest monitoring. Especially, in forest research, using an echo signal is expected for understanding structural characteristics of the forest. However, an echo signal highly depends on the sensor configuration, the footprint size, the canopy structure, and terrain condition. Therefore, it is not easy to understand the forest attributes from the echo signal. In this paper, we describe the development and application of model which to simulate laser intersections within ideal forest environments and to visualize intersections. The developed model has three components. The first component was a creation of the forest environment as full polygon in 3DCG software. Characteristics of the forest was decided by individual trees which were generated by the plant growth model using species and planting years as the initial parameter. The second component was a simulation using a ray tracing to calculate intersections between the forest object and the modelled laser beam. In this study, a laser beam with a specific footprint and a pulse width was defined by spatiotemporal features. In point of view of spatial feature, numerous sub laser beams were generated within a specific footprint to make the laser beam hit the target uniformly. Each sub laser beam had the intensity which was calculated by both the distance from the center of laser beam and the TEM00. On the other hand, in point of view of time feature, each sub laser beam was defined as several particles based on the sampling rate. Each particle had the intensity which was calculated by the pulse width and the sampling rate. The third component was a creation of an echo signal of a specific footprint using the calculated intersections and its intensity, reflectance of target at intersections and sampling rate. Moreover, the developed model had a view function that was able to show the calculated intersections on the surface of target object. As results of simulation of ideal forest environment scenarios, the developed model demonstrated that the model generated the echo signal of different environments well and the viewer function helped to understand the interactions between sub laser beams and target objects.
INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN)
Authors: Hoseini F. , Darvishsefat A. A. , Zargham N.
Published: August 2012

Abstract. In order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed in an area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectral transformations like NDVI, PVI and PCA were performed. A ground truth map included of 34 plots (each plot 1 ha) were prepared. Hard and soft supervised classifications were performed with 5 density classes (0–5%, 5–10%, 10–15%, 15–20% and > 20%). Because of low separability of classes, some classes were merged and classifications were repeated with 3 classes. Finally, the highest overall accuracy and kappa coefficient of 70% and 0.44, respectively, were obtained with three classes (0–5%, 5–20%, and > 20%) by fuzzy classifier. Considering the low kappa value obtained, it could be concluded that the result of the classification was not desirable. Therefore, this approach is not appropriate for operational mapping of these valuable Pistachio forests.
FOREST RESOURCE MANAGEMENT SYSTEM BY STANDING TREE VOLUME ESTIMATION USING AERIAL STEREO PHOTOS
Authors: Kamiya T. , Koizumi H. , Wang J. , Itaya A.
Published: August 2012

Abstract. Forest resource management usually requires much human labour for the field survey to keep the data up-to-date especially for the mountainous area. Furthermore, forest resources start to draw more and more attention not only as lumber resources but also as biomass resources in terms of alternative energy. This paper describes a novel system for forest resource management based on threedimensional data acquired from stereo matching of aerial photographs. The proposed system consists of image analysis of aerial photograph for forest resource estimation, and a GIS system aiming at better management of the forest resources. We have built a prototype GIS system and applied it to the experiment forest in Mie prefecture, Japan.
A CASE STUDY OF A FOREST CARBON STOCK MONITORING SYSTEM FOR REDD+ IN LAO P.D.R.
Authors: Nasu M. , Sano T. , Oono K. , Wada Y. , Nakada R. , Yamase T. , Tomimura S. , Furuya T. , Matteo G. , Kamusoko C. , Gomi Y. , Isobe T. , Iwata A. , Moriike H. , Hironaga S. , Hosokawa T. , Someya T. , Wachi A. , Homsysavath K.
Published: August 2012

Abstract. Various technical studies for building forest monitoring system for MRV system of REDD+ has been implemented utilizing satellite remote sensing technology and ground survey upon configuring two pilot study areas, at whole Louangphabang (LPB) province (approximately 20,000 km2) and in Bolikhmxai(BLK) province (approximately 4,400 km2) in Lao PDR. Multi-temporal land use/cover data were prepared for making analyses of deforestation and forest degradation caused by various driving factors, and to establish reference scenario for REDD+. In addition to ordinary method of forest carbon stock estimation based on the forest plot surveys, land use/cover maps and IPCC's emission factors (GOFC-GOLD, 2010), improved methods were studied introducing a concept of biomass classing derived from multispectral data and tree height measurement utilizing ALOS/PRIS stereo images, in order to reduce difficulty of field surveys at high altitude and steep mountain forest, especially in natural forest areas. First, multi-temporal land use/cover maps were prepared for two pilot study areas for analyzing deforestation and forest degradation of the subjected area. Then, the biomass level of "Current Forest" area of the land use/cover maps were classified into three classes as high, medium, and low applying spectral analyses of LANDSAT/TM and SPOT images, and based on visual interpretation results of pan-sharpened ALOS/AVNIR2 images in addition to limited number of field surveys as references. Matching accuracies were around 60% at this stage of study (This number improved to 85% at the later stage). Based on the field survey data, the forest carbon stock vs. tree height model was established, and furthermore it was related to the forest biomass classes. ALOS/PRISM images were used to measure heights at about 1,500 forest stands selected at 2 – 4 km grid intervals. Accuracy analyses showed that the standard deviation of the tree height measurement errors was approximately 4 – 5 m, but the mean value of the measured data were within 1– 2 m comparing to the field survey data. Finally, wall-to-wall, above-ground forest carbon stock estimation maps which would be useful for forest management and REDD+ were prepared. As a conclusion, it can be said that 3D measurement, in addition to multi-spectral information, of the forest provides useful information for monitoring forest carbon stock for REDD+ although further refinement of technologies is to be needed. And, the results and experiences obtained from the studies will provide useful data for establishing actual MRVsystem.
SUSCEPTIBILITY EVALUATION AND MAPPING OF CHINA'S LANDSLIDE DISASTER BASED ON MULTI-TEMPORAL GROUND AND REMOTE SENSING SATELLITE DATA
Authors: Liu C. , Li W. , Lu P. , Sang K. , Hong Y. , Li R.
Published: August 2012

Abstract. Under the circumstances of global climate change, nowadays landslide occurs in China more frequently than ever before. The landslide hazard and risk assessment remains an international focus on disaster prevention and mitigation. It is also an important approach for compiling and quantitatively characterizing landslide damages. By integrating empirical models for landslide disasters, and through multi-temporal ground data and remote sensing data, this paper will perform a landslide susceptibility assessment throughout China. A landslide susceptibility (LS) map will then be produced, which can be used for disaster evaluation, and provide basis for analyzing China's major landslide-affected regions. Firstly, based on previous research of landslide susceptibility assessment, this paper collects and analyzes the historical landslide event data (location, quantity and distribution) of past sixty years in China as a reference for late-stage studies. Secondly, this paper will make use of regional GIS data of the whole country provided by the National Geomatics Centre and China Meteorological Administration, including regional precipitation data, and satellite remote sensing data such as from TRMM and MODIS. By referring to historical landslide data of past sixty years, it is possible to develop models for assessing LS, including producing empirical models for prediction, and discovering both static and dynamic key factors, such as topography and landforms (elevation, curvature and slope), geologic conditions (lithology of the strata), soil type, vegetation cover, hydrological conditions (flow distribution). In addition, by analyzing historical data and combining empirical models, it is possible to synthesize a regional statistical model and perform a LS assessment. Finally, based on the 1km×1km grid, the LS map is then produced by ANN learning and multiplying the weighted factor layers. The validation is performed with reference to the frequency and distribution of historical data. This research reveals the spatiotemporal distribution of landslide disasters in China. The study develops a complete algorithm of data collecting, processing, modelling and synthesizing, which fulfils the assessment of landslide susceptibility, and provides theoretical basis for prediction and forecast of landslide disasters throughout China.
AN INTERCOMPARISON OF PASSIVE TERRESTRIAL REMOTE SENSING TECHNOLOGIES TO DERIVE LAI AND CANOPY COVER METRICS
Authors: Woodgate W. L.
Published: August 2012

Abstract. Forest indicators such as Leaf Area Index (LAI) and vegetation cover type are recognised as Essential Climate Variables (ECVs) which support the '…research, modelling, analysis, and capacity-building activities…' requirements of the United Nations Framework Convention on Climate Change. This research compares the use of passive terrestrial remote sensing technologies for LAI and canopy cover metrics. The passive sensors used are the LAI-2200 and Digital Hemispherical Photography (DHP). The research was conducted at a Victorian reference site containing tree species with predominantly erectophile leaf angle distributions, which are significantly under-represented in the literature. The reference site contributes to a network of sites representative of Victorian land systems and is considered to be in good condition. Preliminary results indicate a low correlation (R2=0.46) between the LAI-2200 and DHP. Further comparisons to be conducted include adding a passive CI-110 plant canopy analyser and an active Terrestrial Laser Scanner. The future objective is to scale the in situ data to aerial and satellite remotely sensed datasets. The aerial remotely sensed data include LiDAR flown by a Riegl LMS Q560, and high resolution multispectral and hyperspectral imagery flown by the ASIA Eagle and Hawk system. The in situ data can be utilised for both calibration and validation of the coincident aerial imagery and LiDAR. Finally, the derived datasets are intended for use to validate the global MODIS LAI product.
CLASSIFICATION AND MODELLING OF URBAN MICRO-CLIMATES USING MULTISENSORAL AND MULTITEMPORAL REMOTE SENSING DATA
Authors: Bechtel B. , Langkamp T. , Böhner J. , Daneke C. , Oßenbrügge J. , Schempp S.
Published: August 2012

Abstract. Remote sensing has widely been used in urban climatology since it has the advantage of a simultaneous synoptic view of the full urban surface. Methods include the analysis of surface temperature patterns, spatial (biophysical) indicators for urban heat island modelling, and flux measurements. Another approach is the automated classification of urban morphologies or structural types. In this study it was tested, whether Local Climate Zones (a new typology of thermally 'rather' homogenous urban morphologies) can be automatically classified from multisensor and multitemporal earth observation data. Therefore, a large number of parameters were derived from different datasets, including multitemporal Landsat data and morphological profiles as well as windowed multiband signatures from an airborne IFSAR-DHM. The results for Hamburg, Germany, show that different datasets have high potential for the differentiation of urban morphologies. Multitemporal thermal data performed very well with up to 96.3 % overall classification accuracy with a neuronal network classifier. The multispectral data reached 95.1 % and the morphological profiles 83.2 %.The multisensor feature sets reached up to 97.4 % with 100 selected features, but also small multisensoral feature sets reached good results. This shows that microclimatic meaningful urban structures can be classified from different remote sensing datasets. Further, the potential of the parameters for spatiotemporal modelling of the mean urban heat island was tested. Therefore, a comprehensive mobile measurement campaign with GPS loggers and temperature sensors on public buses was conducted in order to gain in situ data in high spatial and temporal resolution.
SPECTRAL UNMIXING OF BLENDED REFLECTANCE FOR DENSER TIME-SERIES MAPPING OF WETLANDS
Authors: Michishita R. , Jiang Z. , Xu B.
Published: August 2012

Abstract. The orbiting cycle and frequent cloud contamination have limited the applications of the moderate-resolution remotely sensed data for detecting rapid land cover changes that are critical to the monitoring of wetlands. It is necessary to use multiple remotely sensed data sources that have different spatial resolution and temporal frequency, because both spatial and temporal details are important in understanding the mechanisms in wetland cover changes. This study examined the applicability of linear spectral mixture analysis to the blended reflectance that was generated by incorporating the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). Nine TM and MODIS images of the Poyang Lake area, China acquired in 2004 and 2005 were used to blend the reflectance. In order to account for the spectral variations in materials, we incorporated the multiple endmember spectral mixture analysis (MESMA) in unmixing the blended reflectance. The average absolute differences between the land cover fractions derived from the blended image and those from the observed image were calculated as well as correlation coefficients. Our results demonstrated that MESMA could unmix the blended reflectance generated by ESTARFM. However, due to the existence of the blended pixels with large difference in reflectance from the observed reflectance, the land cover fractions derived from the blended reflectance did not match with those derived from the observed reflectance as well as expected. It is also suggested that the comprehensiveness of the endmember spectral libraries was another factor influencing the agreement.
GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS
Authors: Shimoda H. , Fukue K.
Published: August 2012

Abstract. The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year) SR(Surface Reflectance 8-Day L3) and NBAR(Nadir BRDF-Adjusted Reflectance 16-Day L3) products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR product and NBAR product showed similar classification accuracy of 99%.
FLUORESCENT ANALYSIS OF PHOTOSYNTHETIC MICROBES AND POLYCYCLIC AROMATIC HYDROCARBONS LINKED TO OPTICAL REMOTE SENSING
Authors: Zhang D. , Muller J.-P. , Lavender S. , Walton D. , Dartnell L. R.
Published: August 2012

Abstract. Fluorescence analysis, being a non-invasive technique, has become one of the most powerful and widely used techniques for microbiologists and chemists to study various types of sample from photosynthetic microbes to hydrocarbons. The work reported here focuses on experimental results of fluorescent features of photosynthetic microbial species (cyanobacteria) and also five different crude oil samples. The cyanobacteria samples were collected from the Baltic Sea at the end of July 2011 and were associated with cyanobacterial bloom events, and the crude oil samples were from various oil spill events. The aim of the study was to find fluorescent biosignatures of cyanobacteria (initially a species specific to the Baltic Sea) and the fingerprints of crude oil; oil spills can be difficult to differentiate from biogenic films when using Synthetic Aperture Radar (SAR) or sunglint contaminated optical imagery. All samples were measured using a Perkin Elmer LS55 Luminescence spectrometer over a broad range of excitation and emission wavelength from ultraviolet (UV) to near infrared (NIR). The results are presented in Excitation Emission Matrices (EEMs) that exhibit the fluorescent features of each sample. In the EEM of the seawater sample containing cyanobacteria, there is an intense emission peak from tryptophan with fluorescent excitation and emission peaks at 285 and 345 nm respectively. In addition, fluorescent signatures of phycocyanin and chlorophyll-a are present with excitation and emission centre wavelengths at 555 nm, 645 nm and 390 nm, 685 nm, respectively. Additionally, the fluorescence signatures of Polycyclic Aromatic Hydrocarbons (PAHs) are present in the EEMs of crude oil samples with excitation and emission peaks at 285 nm and 425 nm. This study underpins further research on how to distinguish cyanobacteria species by their fluorescence signatures and the potential role that PAHs play in detection of cyanobacteria fluorescence features.
A STUDY ON EXTRACTING THIN SEA ICE AREA FROM SPACE
Authors: Cho K. , Mochizuki Y. , Yoshida Y. , Shimoda H. , Chen C.-F.
Published: August 2012

Abstract. Global warming is one of the most serious problems the earth is facing in the 21st Century. In order to detect the sign of global warming, the importance of sea ice monitoring is increasing. Especially, sea ice thickness is an key parameter for understanding the heat flux of sea ice area. However, estimation of sea ice thickness with satellite remote sensing is not easy. In this study authors have examined the possibility of extracting thin sea ice area from remotely sensed data from space. The study was performed in the Sea of Okhotsk. Firstly, the possibility of estimating thin ice thickness with high resolution optical sensor RSI(IFOV = 8 m) on FORMOSAT- 2 satellite was examined. The comparison of RSI data with in situ measurement of ice thickness suggested the possibility of estimating sea ice thickness with RSI data for less than 20 cm under the cloudless and snow free condition. The correlation between RSI data and MODIS data(IFOV = 250 m) was also examined for the thin ice area. The result also suggested the possibility of extracting thin sea ice area from MODIS data. Based on these results, the authors have examined possibility of extracting thin sea ice area with passive microwave sensor AMSR-E by using thin ice area estimated with MODIS data as truth data. Since the horizontal polarization of 19 GHz are more sensitive to water than the vertical polarization of 19 GHz, the authors have utilized the polarization difference of 19 GHz for extracting thin sea ice area from AMSR-E data. The detailed study result will be presented in this paper.
MONITORING GLACIER VARIATIONS IN THE SOUTHERN PATAGONIA ICEFIELD UTILIZING IMAGES LANDSAT 7 ETM+
Authors: Ferreira de Mendonça L. F.
Published: August 2012

Abstract. The monitoring of the variation in glacier areas is increasingly important with the apparent trend of global warming. One of the major ice sheets on the planet, the main glaciers of Southern Patagonia Icefield were mapped using a set of images obtained in 1973, 1976, 1979, 1986, 2005 and 2009 by the ETM + sensor onboard the Landsat 7 satellite. The images were calibrated to planetary radiance and reflectance, where the supervised classification of each image sought to obtain the physical limit of the snow with each glacier. Maps were generated with the terminal position of the glacier tongue for the dates analyzed. The results were compared with previous publications and showed peculiar behavior of each glacier, especially from the images of 1986, where there was a pattern of decrease in surface area of glaciers. And the temporal analysis will show the behavior of glaciers to the present day.
COMPARISON OF MICROWAVE BACKSCATTER ANISOTROPY PARAMETERISATIONS OVER THE ANTARCTIC ICE SHEET
Authors: Fraser A. D. , Young N. W. , Adams N.
Published: August 2012

Abstract. The Antarctic Ice Sheet exhibits a strong anisotropy in microwave backscatter, both as a function of azimuth angle and incidence angle. This anisotropy arises as a result of i) the alignment of roughness elements and other wind-related surface and sub-surface features, as well as ii) internal layers and snow grain size gradient within the snowpack. As a result of its antenna configuration, the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Advanced SCATterometer (ASCAT) satellite instrument is able to observe much of the continent with a large azimuth and incidence angle diversity. A lack of azimuth and incidence diversity has restricted previous backscatter parameterisations to relatively simple bi-sinusoidal (azimuth angle) and linear (incidence angle) parameterisations. Using ASCAT, we show that a better fit can be obtained using a cubic incidence angle function and a Fourier series of up to four terms for parameterisation of the azimuth angle anisotropy. Scatterometer instruments have previously been used in Greenland to retrieve accumulation rate by observing the change in backscatter as a function of incidence angle. Here we present preliminary results of an empirical study linking the isotropic component and incidence angle dependence to snow accumulation rate in Antarctica, using snow stake measurements as ground truthing.
APPLICATION OF SURFACE MATCHING FOR IMPROVED MEASUREMENTS OF HISTORIC GLACIER VOLUME CHANGE IN THE ANTARCTIC PENINSULA
Authors: Kunz M. , Mills J. P. , Miller P. E. , King M. A. , Fox A. J. , Marsh S.
Published: August 2012

Abstract. Climate records show that the Antarctic Peninsula is rapidly warming. Dramatic changes in ice shelf and glacier extent have been recorded over the last few decades. Mapping recent changes in the Antarctic Peninsula is relatively straightforward, as increased amounts of earth observation data become readily available for scientific purposes. However, long term measurements of volumetric changes within the region are rare and less is known of changes which have occurred over the second half of the 20th Century. Nonetheless, historical observations are available in the form of archival aerial stereo-photography. However, extracting information from historical data, i.e. to compare it to recent data, is not trivial, and to-date, this data source remains largely untapped, despite its rich potential. Often such imagery is stored in non-digital format and may have degraded over time. Other problems relate to insufficient metadata or ground control. Typically these difficulties result in poor registration of multi-temporal DEMs, which degrade subsequent measurements of surface change. This is one of the fundamental limitations of accessing archival datasets. In this research a least squares surface matching technique is introduced to overcome these challenges and achieve reliable registration of multi-temporal DEMs. Historical imagery acquired in the 1960s for two Antarctic Peninsula glaciers is processed to extract DEMs, which are subsequently compared to DEMs derived from modern ASTER satellite data and aerial photography. Through the surface matching approach, it is shown that the registration accuracy of the historical and modern-day datasets can be improved significantly. This enables precise quantification of glacier elevation changes on a multi-decadal time scale. Frontal glacier surface lowering of up to 50 m was observed over the last ~4 decades. Results of this study allow a better understanding of historical volumetric glacier changes of the Antarctic Peninsula and provide an efficient and automated method for improved DEM co-registration.
ASSESSMENT OF SEA ICE FREEBOARD AND THICKNESS IN MCMURDO SOUND, ANTARCTICA, DERIVED BY GROUND VALIDATED SATELLITE ALTIMETER DATA
Authors: Price D. , Rack W. , Haas C. , Langhorne P. , Marsh O.
Published: August 2012

Abstract. This investigation employs the use of ICESat to derive freeboard measurements in McMurdo Sound in the western Ross Sea, Antarctica, for the time period 2003-2009. Methods closely follow those previously presented in the literature but are complemented by a good understanding of general sea ice characteristics in the study region from extensive temporal ground investigations but with limited spatial coverage. The aim of remote sensing applications in this area is to expand the good knowledge of sea ice characteristics within these limited areas to the wider McMurdo Sound and western Ross Sea region. The seven year Austral Spring (September, October, and November) investigation is presented for sea ice freeboard alone. An interannual comparison of mean freeboard indicates an increase in multiyear sea ice freeboard from 1.08 m in 2003 to 1.15 m in 2009 with positive and negative variation in between. No significant trend was detected for first year sea ice freeboard. Further, an Envisat imagery investigation complements the freeboard assessment. The multiyear sea ice was observed to increase by 254 % of its original 2003 area, as firstyear sea ice persisted through the 2004 melt season into 2005. This maximum coverage then gradually diminished by 2009 to 20 % above the original 2003 value. The mid study period increase is likely attributed to the passage of iceberg B-15A minimising oceanic pressures and preventing sea ice breakout in the region.
RISK ZONE MODELLING AND EARLY WARNING SYSTEM FOR VISCERAL LEISHMANIASIS (KALA-AZAR) DISEASE IN BIHAR, INDIA USING REMOTE SENSING AND GIS
Authors: Jeyaram A. , Kesari S. , Bajpai A. , Bhunia G. S. , Krishna Murthy Y. V. N.
Published: August 2012

Abstract. Visceral Leishmaniasis (VL) commonly known as Kala-azar is one of the most neglected tropical disease affecting approximately 200 million poorest populations 'at risk in 109 districts of three endemic countries namely Bangladesh, India and Nepal at different levels. This tropical disease is caused by the protozoan parasite Leishmania donovani and transmitted by female Phlebotomus argentipes sand flies. The analysis of disease dynamics indicate the periodicity at seasonal and inter-annual temporal scale which forms the basis for development of advanced early warning system. Study area of highly endemic Vaishali district, Bihar, India has been taken for model development. A Systematic study of geo-environmental parameters derived from satellite data in conjunction with ground intelligence enabled modelling of infectious disease and risk villages. High resolution Indian satellites data of IRS LISS IV (multi-spectral) and Cartosat-1 (Pan) have been used for studying environmentally risk parameters viz. peri-domestic vegetation, dwelling condition, wetland ecosystem, cropping pattern, Normalised Difference Vegetation Index (NDVI), detailed land use etc towards risk assessment. Univariate analysis of the relationship between vector density and various land cover categories and climatic variables suggested that all the variables are significantly correlated. Using the significantly correlated variables with vector density, a seasonal multivariate regression model has been carried out incorporating geo-environmental parameters, climate variables and seasonal time series disease parameters. Linear and non-linear models have been applied for periodicity and interannual temporal scale to predict Man-hour-density (MHD) and 'out-of-fit' data set used for validating the model with reasonable accuracy. To improve the MHD predictive approach, fuzzy model has also been incorporated in GIS environment combining spatial geo-environmental and climatic variables using fuzzy membership logic. Based on the perceived importance of the geoenvironmental parameters assigned by epidemiology expert, combined fuzzy membership has been calculated. The combined fuzzy membership indicate the predictive measure of vector density in each village. A γ factor has been introduced to have increasing effect in the higher side and decreasing effect in the lower side which facilitated for prioritisation of the villages. This approach is not only to predict vector density but also to prioritise the villages for effective control measures. A software package for modelling the risk villages integrating multivariate regression and fuzzy membership analysis models have been developed to estimate MHD (vector density) as part of the early warning system.
MAPPING THE RISKS OF MALARIA, DENGUE AND INFLUENZA USING SATELLITE DATA
Authors: Kiang R. K. , Soebiyanto R. P.
Published: August 2012

Abstract. It has long been recognized that environment and climate may affect the transmission of infectious diseases. The effects are most obvious for vector-borne infectious diseases, such as malaria and dengue, but less so for airborne and contact diseases, such as seasonal influenza. In this paper, we examined the meteorological and environmental parameters that influence the transmission of malaria, dengue and seasonal influenza. Remotely sensed parameters that provide such parameters were discussed. Both statistical and biologically inspired, processed based models can be used to model the transmission of these diseases utilizing the remotely sensed parameters as input. Examples were given for modelling malaria in Thailand, dengue in Indonesia, and seasonal influenza in Hong Kong.
Effects of Stone Dust Exposure on Some Liver and Kidney Related Serum Parameters of Stone Crush Plant Workers
Authors: Ilahi Ikram , Khan Asghar , Ali Mehboob , Ullah Ubaid , Ali Jawad , Khan Murad
Published: August 2012

In the present study the effects of stone dust exposure on liver and kidney related serum parameters were assessed in workers of stone crush plants in various localities of Swat and Dir (L) districts of Khyber Pakhtunkhwa, Pakistan. The liver and kidney related serum parameters included Glutamate Pyruvate Transaminase (GPT), Alkaline Phosphatase (ALP), bilirubin and creatinine. Blood samples were collected from 66 exposed workers and 66 unexposed persons (control). The mean values of liver related parameters i.e. serum GPT, ALP and bilirubin of workers were significantly higher than control persons (P<0.05). The mean value of kidney related parameter i.e. creatinine of workers   was significantly higher as compared to control persons (P<0.05).  From the present survey it was concluded that continuous exposure to stone dust can cause abnormal alterations in the normal levels of serum GPT, ALP, bilirubin and creatinine.
Magnetic Resonance Arthrography for Labral Tears and Chondral Wear in Femoroacetabular Impingement
Authors: Banks Daniel B.A. , Boden Richard A. , Mehan Rakesh , Fehily Max J.
Published: August 2012

Magnetic resonance arthrography (MRA) is a useful pre-operative investigation for patients with clinical signs and symptoms of femoroacetabular impingement. Our aim was to assess the diagnostic accuracy of MRA in detecting labral tears and chondral wear in this context.

Sixty nine hips were included in the study after exclusions. All patients underwent pre-operative MRA and then subsequent hip arthroscopy. The findings at MRA were compared to those found intraoperatively.

For labral tears, sensitivity, specificity and accuracy were 81%, 51% and 58% respectively. For chondral wear these figures were 17%, 100%, and 55% respectively.

In our institution, MRA was therefore not as accurate as previously published work suggests.
Do We Medialise the Hip Centre of Rotation in Total Hip Arthroplasty? Influence of Acetabular Offset and Surgical Technique
Authors: Bonnin Michel P. , Archbold Pooler H.A. , Basiglini Lucas , Fessy Michel H. , Beverland David E.
Published: August 2012

Acetabular offset (AO) is the distance between the centre of the femoral head and the true floor of the acetabulum. We quantified the AO in normal hips and compared the displacement of the centre of rotation of the hip (CRH) after conventional and anatomical cup implantation during THA. 100 CT-scans of normal hips were analysed before and after simulating implantation of the acetabular component.

Mean AO was 30.8 mm ± 3. The medial shift of the CRH was 1.6 mm ± 1.2 with the anatomical and 4.8 mm ± 1.9 with the conventional technique (p<0.0001). Medialisation was greater than 5 mm in 44% of the cases when the conventional technique was used, but occurred in no case when using the anatomical technique. Differences between men and women were significant: 5.6 mm ± 1.6 and 3.5 mm ± 1.7 with the conventional technique; 2.0 mm ± 1.1 and 0.9 mm ± 0.9 with the anatomical technique (p<0.0001 for both measurements).

The concept of hip offset cannot be limited to that of the femoral offset. AO widely varies and cannot be neglected. In patients with significant AO, surgeons should pay close attention to the preparation of the acetabulum. This should be done conservatively so that the acetabular cup can be placed anatomically in order to restore the native hip biomechanics.
Femoral Torsion: Reliability and Validity of the Trochanteric Prominence Angle Test
Authors: Maier Claudia , Zingg Patrick , Seifert Burkhardt , Sutter Reto , Dora Claudio
Published: August 2012

Influence of femoral torsion on femoroacetabular impingement and other hip conditions is not well documented and its assessment by imaging methods during clinical work-up is not routinely performed. We studied whether physical examination could reliably measure or at least screen for gross anomalies of femoral torsion or if appropriate imaging should routinely be performed. Assessing femoral torsion of 45 volunteers using the “trochanteric prominence angle test” and magnetic resonance imaging (MRI), inter- and intra-observer reliability ranged from poor to moderate and agreement with MRI values was only fair. Considering a 5° to 10° difference of femoral torsion as clinically relevant, physical examination failed to match MRI values within ±10° in more than 50%. Arbitrarily defining thresholds for pathological femoral torsion, the “trochanteric prominence angle test” could not recognise torsions outside the >30°/<0° range and diagnosed torsions outside the >20°/<10° range with a sensitivity of 18%-75% and a specificity of 58%-98% only.

Physical assessment of femoral torsion using the “trochanteric prominence angle test” does not allow reliable measurement or screening for gross anomalies. We therefore integrate an adapted MRI protocol allowing measurement of femoral torsion within our clinical work up.
A Large Aneurysm in an Arterio-Venous Fistula for Renal Access in a Pregnant Young Woman
Authors: Stephenson Matthew A. , Neate Emily CM. , Mistry Hiren , Valenti Domenico
Published: August 2012

Pregnancy is known to increase the risk of aneurysm formation, likely by a combination of histological changes in vessel walls associated with the hormones of pregnancy and the haemodynamic changes to the circulation. To our knowledge this is the first case of a pregnant woman with a brachial-cephalic arterio-venous fistula (AVF) that had never been needled for haemodialysis, yet became hugely aneurysmal during her pregnancy.
Producción de biomasa anual de dos acrídidos (Orthoptera: Acrididae) como alimento alternativo para aves de corral
Authors: Das M. , Ganguly A. , Haldar P.
Published: August 2012

Los acrídidos podrían ser una fuente de proteínas no convencional alternativa para las granjas de aves de corral. Para una producción masiva de biomasa de acrídidos, es esencial seleccionar las especies adecuadas, junto con las plantas que los alimenten adecuadamente. Se llevó a cabo un experimento para criar dos acrídidos comunes en la India, Oxya hyla y Spathosternum prasiniferum y estimar cuál de ellos puede producir una mayor biomasa anual cuando se alimentan de tres plantas, Dactyloctenium aegyptium, Brachiaria mutica y Cynodon dactylon, determinando cual de ellas es el alimento más favorable. Para la producción anual de biomasa, en términos de número, se estimaron las tasas de fecundidad, fertilidad, mortalidad de ninfas y el sexo de ambas especies de acrídidos alimentados con las tres diferentes plantas. También se estimaron la producción de biomasa anual, en términos de peso húmedo y seco, y el contenido de energía. Entre las dos especies, O. hyla mostró valores más altos de fecundidad, fertilidad y peso corporal, tanto húmedo como seco, y valores más bajos de mortalidad de ninfas para las tres plantas. Entre las tres plantas utilizadas como alimento, B. mutica fue la más adecuada para la producción anual de biomasa para ambos acrídidos. Se concluye que la cría masiva de O. hyla alimentándose de B. mutica puede producir una gran biomasa anual en las granjas de acrídidos.
Physicochemical and sensorial characteristics of four muscles from commercial crossbred pigs slaughtered at 130 kg body weight
Authors: Calvo S. , Rodríguez-Sánchez J. A. , Panea B. , Latorre M. A.
Published: August 2012

In Spain, a sizeable proportion of pigs are slaughtered above 100 kg of body weight because are mainly intended for dry-cured ham elaboration. The chance of finding pork cuts differentiated by quality, which might be intended for fresh meat consumption, would optimize the production of heavy carcasses. The aim of this work was to evaluate the physicochemical and sensory characteristics of four muscles from heavy pigs. A total of 14 Duroc × (Landrace × Large White) gilts were slaughtered at 130 kg of body weight. From each carcass, the following muscles (two per carcass) were excised: Longissimus thoracis (LT), Psoas major (PM), Lattissimus dorsi (LD) and Serratus ventralis (SV). Several physical (color, moisture losses and resistance to cutting), chemical (intramuscular fat content and its fatty acid profile) and sensorial (attributes related to aroma, flavor, texture and acceptability) characteristics were evaluated. The LT had the highest fibrousness and the lowest water holding capacity indicators, tenderness and juiciness. The PM showed the lowest intramuscular fat and monounsaturated fatty acid contents and fibrousness, and the highest moisture, C18:2n6 and polyunsaturated fatty acid proportions. The LD had the highest yellowness and intensity of fat odor and flavor. The SV provided the highest intramuscular fat content and red color, and the lowest resistance to cutting. All muscles had similar score in global acceptability. There were several interesting physicochemical and sensory differences among the muscles studied which suggest that they might be commercialized individually as meat cuts of differentiated quality optimizing the use of heavy pig carcasses.
Effects of paratuberculosis on Friesian cattle carcass weight and age at culling
Authors: Vázquez P. , Garrido J. M. , Juste R. A.
Published: August 2012

Bovine paratuberculosis (PTB) causes major economic losses to dairy farmers because of decreased milk production, poor body condition, weight loss and early culling. The aim of this study was to evaluate the effect of Mycobacterium avium subspecies paratuberculosis (MAP) infection on carcass weight and age at slaughter in Friesian cattle. A total of 1,014 adult cows slaughtered at two local abattoirs in the Basque Country were included in this study. MAP infection was determined by different methods: indirect ELISA on blood samples, detection of MAP in tissues by culture and real time PCR (rtPCR), and histopathological examination. Serial and parallel interpretations of these methods were also considered for setting the upper and lower infection rates. MAP infection was confirmed by at least one test in 58.9% of animals. Most infected cows were detected by histopathology (46.9%) and rtPCR (29.6%). Overall estimates of carcass mean weight losses ranged from 3.7% for cases identified by the presence of microscopic specific PTB inflammatory lesions to 12.4% for cases with positive results in the paratuberculosis antibody ELISA test. Isolation of high bacterial loads in tissues and occurrence of diffuse granulomatous enteritis were associated with the highest weight loses, 22.2% and 26.0% respectively. The life expectancy of seropositive cows and those showing diffuse lesions was reduced by nearly one year compared to that of non-infected ones. Our results provide consistent evidences of PTB effect on the reduction of slaughter weight and lifespan of dairy cows, which could be considered as surrogates of clinical disease.