bluuebunny/crossref_metadata_2025 huggingface dataset:
GEOGRAPHICALLY WEIGHTED REGRESSION APPROACH FOR SHALLOW WATER DEPTH ESTIMATION USING MULTISPECTRAL SATELLITE IMAGERIES
Authors: Lumban-Gaol Y. A. , Dewi R. S. , Oktaviani N. , Aditya S.
Published: August 2020

Abstract. Shallow water depth is essential for coastal planning, monitoring, and research. Bathymetry data is mostly produced from hydrographic survey using echosounder. The generic result from those measurements is discrete values while the desired output is a continuous depth model. To fill the gaps in the sounding data, we use Satellite Derived Bathymetry (SDB) approach with Geographically Weighted Regression (GWR). This study aims to investigate the feasibility of GWR to model bathymetry of shallow water in the eastern part of Indonesia. We explore the correlation between the number of training data and the predicted result. Two different satellites images are used, namely: Sentinel-2A and Landsat 8 OLI/TIRS with 10 and 30 m resolutions respectively. For the experiment, in-situ data are set into training and validation in three different ratios. The model is developed using adaptive GWR approach in which the parameter of regression would adapt the local data set within different kernel sizes. Finally, we compute RMSE (Root Mean Square Error), R2, and TVU (Total Vertical Uncertainty) to assess the quality of our model. In general, Sentinel-2A produces more detailed information due to higher resolution than Landsat 8 OLI/TIRS. Sentinel-2A also obtains more accurate results based on RMSE values. The percentage number of the estimated depth that fulfils TVU requirements is up to 83%. These assessment quality results give us an insight that the SDB approach using GWR is promising. Thus, the GWR method may be able to provide an estimate of bathymetry for many coastal areas in Indonesia.
RECURSIVE HIERARCHICAL CLUSTERING FOR HYPERSPECTRAL IMAGES
Authors: May S.
Published: August 2020

Abstract. Partition based clustering techniques are widely used in data mining and also to analyze hyperspectral images. Unsupervised clustering only depends on data, without any external knowledge. It creates a complete partition of the image with many classes. And so, sparse labeled samples may be used to label each cluster, and so simplify the supervised step. Each clustering algorithm has its own advantages, drawbacks (initialization, training complexity). We propose in this paper to use a recursive hierarchical clustering based on standard clustering strategies such as K-Means or Fuzzy-C-Means. The recursive hierarchical approach reduces the algorithm complexity, in order to process large amount of input pixels, and also to produce a clustering with a high number of clusters. Moreover, in hyperspectral images, a classical question is related to the high dimensionality and also to the distance that shall be used. Classical clustering algorithms usually use the Euclidean distance to compute distance between samples and centroids. We propose to implement the spectral angle distance instead and evaluate its performance. It better fits the pixel spectrums and is less sensitive to illumination change or spectrum variability inside a semantic class. Different scenes are processed with this method in order to demonstrate its potential.
MINIMAL LEARNING MACHINE IN ANOMALY DETECTION FROM HYPERSPECTRAL IMAGES
Authors: Pölönen I. , Riihiaho K. , Hakola A.-M. , Annala L.
Published: August 2020

Abstract. Anomaly detection from hyperspectral data needs computationally efficient methods to process the data when the data gathering platform is a drone or a cube satellite. In this study, we introduce a minimal learning machine for hyperspectral anomaly detection. Minimal learning machine is a novel distance-based classification algorithm, which is now modified to detect anomalies. Besides being computationally efficient, minimal learning machine is also easy to implement. Based on the results, we show that minimal learning machine is efficient in detecting global anomalies from the hyperspectral data with low false alarm rate.
LIDAR-BASED LANE MARKING EXTRACTION THROUGH INTENSITY THRESHOLDING AND DEEP LEARNING APPROACHES: A PAVEMENT-BASED ASSESSMENT
Authors: Cheng Y.-T. , Patel A. , Bullock D. , Habib A.
Published: August 2020

Abstract. With the rapid development of autonomous vehicles (AV) and high-definition (HD) maps, up-to-date lane marking information is necessary. Over the years, several lane marking extraction approaches have been proposed with many of them based on accurate and dense Light Detection and Ranging (LiDAR) point cloud data collected by mobile mapping systems (MMS). This study proposes a normalized intensity thresholding strategy and a deep learning strategy with automatically generated labels. The former extracts lane markings directly from LiDAR point clouds while the latter utilizes 2D intensity images generated from the LiDAR point cloud. Additionally, the proposed approaches are also compared with state-of-the-art strategies such as original intensity thresholding and a deep learning approach based on manually established labels. Finally, each strategy is evaluated in asphalt and concrete pavements separately to assess their sensitivity to the nature of pavement surface. The results show that the deep learning model trained with automatically generated labels performs the best in both asphalt and concrete pavement area with an F1-score of 84.9% and 85.1%. In asphalt pavement area, original intensity thresholding strategy shows a lane marking extraction performance comparable to the other strategies while in concrete pavement area, it is significantly poor with an F1-score of 65.1%. Between the proposed normalized intensity thresholding and deep learning model trained with manually labeled data, the former performs better in asphalt pavement area while the latter obtains better results in concrete pavements.
RELATION NETWORK FOR FULL-WAVEFORMS LIDAR CLASSIFICATION
Authors: Guiotte F. , Rao M. B. , Lefèvre S. , Tang P. , Corpetti T.
Published: August 2020

Abstract. LiDAR data are widely used in various domains related to geosciences (flow, erosion, rock deformations, etc.), computer graphics (3D reconstruction) or earth observation (detection of trees, roads, buildings, etc.). Because of the unstructured nature of remaining 3D points and because of the cost of acquisition, the LiDAR data processing is still challenging (few learning data, difficult spatial neighboring relationships, etc.). In practice, one can directly analyze the 3D points using feature extraction and then classify the points via machine learning techniques (Brodu, Lague, 2012, Niemeyer et al., 2014, Mallet et al., 2011). In addition, recent neural network developments have allowed precise point cloud segmentation, especially using the seminal pointnet network and its extensions (Qi et al., 2017a, Riegler et al., 2017). Other authors rather prefer to rasterize / voxelize the point cloud and use more conventional computers vision strategies to analyze structures (Lodha et al., 2006). In a recent work, we demonstrated that Digital Elevation Models (DEM) is reductive of the vertical component complexity describing objects in urban environments (Guiotte et al., 2020). These results highlighted the necessity to preserve the 3D structure of the point cloud as long as possible in the processing. In this paper, we therefore rely on ortho-waveforms to compute a land cover map. Ortho-waveforms are directly computed from the waveforms in a regular 3D grid. This method provides volumes somehow “similar” to hyperspectral data where each pixel is here associated with one ortho-waveform. Then, we exploit efficient neural networks adapted to the classification of hyperspectral data when few samples are available. Our results, obtained on the 2018 Data Fusion Contest dataset (DFC), demonstrate the efficiency of the approach.
IDENTIFICATION OF TEMPORARY SURFACE WATER USING SENTINEL-1 SAR DATA, CASE STUDY: SENTANI FLASH FLOODING, INDONESIA
Authors: Gasica T. A. , Bioresita F. , Murtiyoso A.
Published: August 2020

Abstract. Temporary surface water monitoring can provide accurate and reliable information about the spatio-temporal level of surface water. This is very important for various environmental applications, such as flood monitoring. Remote sensing data such as Synthetic Aperture Radar (SAR) is very useful for a large-scale flood monitoring. SAR sensors offer clear advantages by providing their own sources of illumination, thus being able to operate in nearly all-weather/day-night conditions. About 30% disasters which occurred in Indonesia are floods. This hazard has become a recurring disaster that takes place annually. A massive flash flood struck Sentani in the Jayapura Regency in the province of Papua, Indonesia on 16 March 2019, causing 104 deaths. The objective of this work is thus to map temporary surface water (flood) of the Sentani flash flooding event in Indonesia using Sentinel-1 SAR imagery. Sentinel-1 IW GRD and SLC (dual polarimetry) on the event period were used. With two types of Sentinel-1 data, this research produced temporary surface water map using rapid mapping method and SAR polarimetry method. Comparing the results, the similarity of SAR polarimetry method to rapid mapping method is about 39%. Based on reference data, rapid mapping result show better accuracy (82%) than SAR polarimetry method (62%). In addition, processing SLC data needs longer time and higher performance than processing GRD data. Thus, for rapid mapping, it is better to use only Sentinel-1 GRD data.
ROBUST MULTIMODAL IMAGE MATCHING BASED ON MAIN STRUCTURE FEATURE REPRESENTATION
Authors: Fu Y. , Ye Y. , Liu G. , Zhang B. , Zhang R.
Published: August 2020

Abstract. Image matching is a crucial procedure for multimodal remote sensing image processing. However, the performance of conventional methods is often degraded in matching multimodal images due to significant nonlinear intensity differences. To address this problem, this letter proposes a novel image feature representation named Main Structure with Histogram of Orientated Phase Congruency (M-HOPC). M-HOPC is able to precisely capture similar structure properties between multimodal images by reinforcing the main structure information for the construction of the phase congruency feature description. Specifically, each pixel of an image is assigned an independent weight for feature descriptor according to the main structure such as large contours and edges. Then M-HOPC is integrated as the similarity measure for correspondence detection by a template matching scheme. Three pairs of multimodal images including optical, LiDAR, and SAR data have been used to evaluate the proposed method. The results show that M-HOPC is robust to nonlinear intensity differences and achieves the superior matching performance compared with other state-of-the-art methods.
CLASSIFICATION OF TIME SERIES OF SENTINEL-2 IMAGES FOR LARGE SCALE MAPPING IN CAMEROON
Authors: Tagne H. , Le Bris A. , Monkam D. , Mallet C.
Published: August 2020

Abstract. Sentinel-2 satellites provide dense image time series exhibiting high spectral, spatial and temporal resolution. These images are in particular of utter interest to map Land-Cover (LC) at large scale. LC maps can now be computed on a yearly basis at the scale of a country with efficient supervised classifiers, assuming suitable training data are available. However, the efficient exploitation of large amount of Sentinel-2 imagery still remain challenging on unexplored areas where state-of-the-art classifiers are prone to fail. This paper focuses on Land-Cover mapping over Cameroon for the purpose of updating the national topographic geodatabase. The ι2 framework is adopted and tested for the specificity of the country. Here, experiments focus on generic classes (five) which enables providing robust focusing masks for higher resolution classifications. Two strategies are compared: (i) a LC map is calculated out of a year long time series and (ii) monthly LC maps are generated and merged into a single yearly map. Satisfactory accuracy scores are obtained, allowing to provide a first step towards finer-grained map retrieval.
A FUSION APPROACH FOR FLOOD MAPPING USING SENTINEL-1 AND SENTINEL-2 DATASETS
Authors: Tavus B. , Kocaman S. , Nefeslioglu H. A. , Gokceoglu C.
Published: August 2020

Abstract. The frequency of flood events has increased in recent years most probably due to the climate change. Flood mapping is thus essential for flood modelling, hazard and risk analyses and can be performed by using the data of optical and microwave satellite sensors. Although optical imagery-based flood analysis methods have been often used for the flood assessments before, during and after the event; they have the limitation of cloud coverage. With the increasing temporal availability and spatial resolution of SAR (Synthetic Aperture Radar) satellite sensors, they became popular in data provision for flood detection. On the other hand, their processing may require high level of expertise and visual interpretation of the data is also difficult. In this study, a fusion approach for Sentinel-1 SAR and Sentinel-2 optical data for flood extent mapping was applied for the flood event occurred on August 8th, 2018, in Ordu Province of Turkey. The features obtained from Sentinel-1 and Sentinel-2 processing results were fused in random forest supervised classifier. The results show that Sentinel-2 optical data ease the training sample selection for the flooded areas. In addition, the settlement areas can be extracted from the optical data better. However, the Sentinel-2 data suffer from clouds which prevent from mapping of the full flood extent, which can be carried out with the Sentinel-1 data. Different feature combinations were evaluated and the results were assessed visually. The results are provided in this paper.
SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYA
Authors: Aslan N. , Koc-San D.
Published: August 2020

Abstract. The objectives of this study are: to create land-use maps by 5-year interval from 1995 to 2015, to analyse the land use change and urban development, and to estimate future land-use pattern and urban growth for the years: 2030, 2045 and 2060. Antalya, which is the 5th biggest city of Turkey, was selected as study area. In this study, there are basically three stages: (i) preprocessing and preparing additional bands, (ii) spatiotemporal land use detection using image classification and (iii) land use simulation using urban growth models. Firstly, atmospheric correction was applied to the Landsat 5 TM and Landsat 8 OLI images and land-cover indices, ASTER Global Digital Elevation Model (GDEM), and Nighttime data were prepared to use them as additional bands during the classification process. Secondly, Landsat images were classified using Random Forest (RF) machine-learning algorithm. Thirdly, urban simulations were performed for the years 2005, 2010, and 2015 and land-use pattern and urban growth was estimated for the years 2030, 2045 and 2060. The RF classification accuracies range from 84.44% to 92.82%. The urban areas increased from 49.56 km2 to 96.25 km2 from 1995 to 2015. The simulation accuracies were computed above 80%. According to the 2030, 2045 and 2060 simulation results, the urban areas were computed as 133.61 km2, 148.27 km2 and 156.85 km2, respectively. As a result, it was seen that the urban area of Antalya has almost doubled between the years 1995–2015 and the urban expansion is expected to continue increasing up to 1960.
HIERARCHICAL CLASSIFICATION FOR ASSESSMENT OF HORTICULTURAL CROPS IN MIXED CROPPING PATTERN USING UAV-BORNE MULTI-SPECTRAL SENSOR
Authors: Handique B. K. , Goswami C. , Gupta C. , Pandit S. , Gogoi S. , Jadi R. , Jena P. , Borah G. , Raju P. L. N.
Published: August 2020

Abstract. Assessment of horticultural crops under mixed cropping system has been a challenge, both for horticulturists and also to the remote sensing communities. But the recent developments in wide range of sensors onboard Unmanned Aerial Vehicles (UAVs) has opened up new possibilities in identification, mapping and monitoring of horticultural crops. This paper presents the results made from a pilot exercise on horticultural crop discrimination using Parrot Sequoia multi-spectral sensor onboard a UAV. This exercise was carried out in Nongkhrah village, Ri-Bhoi district of Meghalaya state located in the north eastern part of India having mixed horticultural crops. A two level hierarchical classification system was followed for identification and delineation of the major horticultural crops in the village. Parrot Sequoia multi-spectral sensor having four bands has been found to be effective in discrimination of horticultural crops based on variation in spectral response of six horticultural crops viz., pineapple, banana, orange, papaya, ginger and turmeric using three commonly used indices viz., Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge Index (NDRE) and Green Normalized Difference Vegetation Index (GNDVI). NDVI and GNDVI showed nearly similar spectral response, whereas separability among the horticultural crops significantly improved with the use of NDRE. The first level of classification involving the five broad land cover classes has resulted an overall accuracy of about 91%, whereas the second level of classification for delineating the five selected horticultural crops has provided an overall accuracy of 79.8%.
MULTI-SCALE ANALYSIS OF JACK PINE SAPLINGS AFTER FIRE ACROSS BURN SEVERITIES
Authors: Bomber M. , Portelli R.
Published: August 2020

Abstract. Fire serves as a successional initiation in jack pine (Pinus banksiana) forests of North America, as jack pine reproduce using seratonous cones that open only in intense heat. Jack pine seedling resilience after fire is characterized by high numbers of mortality. The estimation of sapling survivability and density is useful for understanding dynamics of carbon sequestration, forest structure and dynamic, and supporting management of the landscape. Most studies concerning the interaction of forest disturbances occurs at moderate spatial resolution. These moderate resolution data analyses do not adequately capture the fine scale spatial variation of the landscape after fire for understanding sapling survival. Thus, high-resolution data, such as aerial photography may provide more detailed information to support decision-making. A key to the types of spatial patterns that emerge in these early years is the pre-fire stand condition. In heavily managed areas, the mosaic of forest patches may include extensive variety in disturbance conditions. In this current research we address the problem of scale in relation to understanding the influence of pre-fire condition on post-fire early recovery patterns. To do this, we combine data output from the LandTrendr algorithm in Google Earth Engine with spectral data from aerial photography collected by airplane and Unmanned Aerial System to perform a random forest classification. The result is a finer scale resolution map of forest conditions of varying sapling density.
REMOTE SENSING EVALUATION OF ECOLOGICAL ENVIRONMENT OF ANQING CITY BASED ON REMOTE SENSING ECOLOGICAL INDEX
Authors: Niu X. , Li Y.
Published: August 2020

Abstract. Figuring out the regional ecological environment quality and ecological change is critical for ecological environment monitoring and management and urban construction planning. Based on the remote sensing ecological index (RESI), we evaluate the ecological quality and ecological change from 1999 to 2019 of Anqing city. Multi-temporal Landsat images are used to extract the four indicators of humidity, vegetation, heat and dryness, respectively. Then the RSEI is calculated by principal component analysis. The results show that the ecological quality of Anqing city declined from 1999 to 2019 and then grew slowly from 2009 to 2019. The eco-environmental quality of Anqing city dropped slightly from 1999 to 2019, and the regions with worse quality grades exceeded those becoming better. Particularly, we find that from 1999 to 2009, the area where the ecological quality became better made up 18.31% of the urban area, while the worse ecological area accounted for 29.68% of the urban area; from 2009 to 2019, the area of improved ecological environment reached 24.35%, while the area of degraded quality constituted 41.36%. Land-use changes dominated eco-environmental quality. The areas of poor eco-environmental quality expanded in residential regions and eco-environmental quality of mountainous area improved since returning cultivated land in steep hills into forest. The RSEI results are expected to provide a quantitative foundation for planning sustainable development and the rational use of resources in Anqing city.
MONITORING TEMPORAL AND SPATIAL CHANGES OF LAND USE AND LAND COVER BASED ON REMOTE SENSING IN THE HILLY REGION OF CENTRAL SICHUAN BETWEEN 1989 AND 2009
Authors: Zeng Z. , Fan J.
Published: August 2020

Abstract. In recent years, under the background of government policy and the development of social economy, land use in hilly region of central Sichuan has changed drastically. Especially the Changzhi soil erosion control project that has been carried out since 1989 and the policy of converting from farm land to forest which has been carried out after flooding disaster in 1998, have seriously affected the land use in hilly region of central Sichuan between 1989 and 2009. In order to detect these changes and acquire the land use information, this study was conducted in Lizixi basin which is the typical area in hilly region of central Sichuan. Supervised classification was applied to the processing procedure of TM, SPOT data in 1989, 1999 and Rapideye data in 2009. The results were further improved by visual interpretation. The overall classification accuracy reaches 88.33% and the kappa is 0.8350. The elevation was classified into five grades to detect the land use distribution in different elevation gradients in 2009. Post-classification comparisons of the classified images indicated that the major change consists that the cultivated land is decreasing and forest is increasing. The force factor of these changes may be the policy of converting from farmland to forest. Because of the labor shortage, 53.29% of the decreased cultivated land has changed to abandoned arable land which is covered by lush grass and mainly distribute on the halfway up to the hill. The urban area has enlarged 7 times due to the large number of migrants from rural to urban. Overall these changes reflect the regional policies and human activities are the major and important force factors of changes in the hilly region of central Sichuan during last two decades.
TEMPORAL-SPATIAL CHANGES IN AEROSOLS DURING WINTER HAZE OF WUHAN： A TYPICAL HIGH-HUMID INLAND CITY IN CENTRAL CHINA
Authors: Jin S. , Ma Y. , Gong W. , Zhang M.
Published: August 2020

Abstract. Temporal and spatial changes of aerosols characteristics was investigated to improve understandings of haze in winters of Wuhan, based on measurements of a CIMEL sun-sky radiometer and a modified Dark Target (DT) method. A large increase in no-absorbing and fine-mode particle is the main characteristic of aerosol during winter haze periods. From no-haze to haze conditions, aerosol optical depth (AOD), fine-mode peak value of size distribution, and single scattering albedo increased respectively from 0.46, 0.47 µm3/µm2, and 0.84 to 0.93, 0.91 µm3/µm2, and 0.87. Based on above aerosol optical and microphysical properties, we re-calculated aerosol models and improved the DT method. Results showed that our improvement increased the expect error (%) from 17.9 to 70.9. Spatial distributions revealed that heavy aerosol loading often occurred in rural and suburban areas rather than city centre. With the haze developing, the AOD increased by ∼0.3 over north of Wuhan and showed a downward trend from north to south.
LONG TERM AIR QUALITY ANALYSIS IN REFERENCE TO THERMAL POWER PLANTS USING SATELLITE DATA IN SINGRAULI REGION, INDIA
Authors: Romana H. K. , Singh R. P. , Shukla D. P.
Published: August 2020

Abstract. The exponentially growing population and related anthropogenic activities have led to modifications in local environment. The change in local environment, evolving pattern of land use, concentrations of greenhouse gases and aerosols alter the energy balance of our climate system. This alteration in climate is leading to premature deaths worldwide. This study analyses the air quality of Singrauli region, Madhya Pradesh, India for the past 15 years. Otherwise known as Urjanchal “the energy capital” of India has been declared as critically polluted by CPCB. The study provides an updated list of thermal power plants in the study area and their emission effects on the local environment. The pollutants analyzed in the study are carbon dioxide, methane, nitrogen dioxide, Sulphur dioxide and particulate matter. Long term remotely sensed data was obtained from NASA Giovanni for past 15 years. Statistical analysis is used to characterize seasonal and annual variations of trace gases in the study area. The study concluded that Methane, Carbon dioxide, Nitrogen dioxide and Sulphur dioxide are on an increasing trend with an average rate of 1.03, 0.99, 2.15 and 1.09 annually. Secondly, Methane & SO2, PM2.5 & NO2, PM10 & NO2, CO2 & Methane and PM2.5 & PM10 have strong correlations with a 95% significance. Furthermore, Methane, SO2 and CO2 exhibit cyclic variation with change in season. The study also indicated that maximum aerosols present in the study area are a result of anthropogenic activities.
EXPLORING SENTINEL-2 FOR LAND COVER AND CROP MAPPING IN PORTUGAL
Authors: Hernandez I. , Benevides P. , Costa H. , Caetano M.
Published: August 2020

Abstract. Land cover information is fundamental for a wide range of fields, such as research and policymaking. Remote sensing has historically been a source of data on land cover and recognized as the only practical systematic and wall-to-wall source for crop mapping. The European Copernicus programme and its free data policy for Sentinel-2 made accessible large volumes of imagery for frequent mapping and updating, generating new challenges. One such challenge is timely mapping through supervised image classification. The need for a prompt classification workflow requires training to become automatic, which typically relies on samples collected manually via fieldwork or image interpretation. Another challenge is to map land cover classes that traditionally have been troublesome to identify when satellite observations were sparse. For instance, crops have a spectral response that changes substantially throughout the year or during narrow time windows, which cannot be observed with few image acquisitions. This paper presents research ongoing in Portugal to develop a methodology for automatic image classification using training samples labelling with no human intervention. Rather, auxiliary datasets are used to randomly extract labelled points from large training samples to produce a land cover and crop map in raster format at 10 m spatial resolution using 2018 Sentinel-2 images. The proposed methodology was tested with the Random Forest classifier achieving an overall accuracy of 76%. These results are promising and support the idea of refining the methodology to move towards an annual land cover map production at the national scale.
A NEW CLOUD SHADOW DETECTION ALGORITHM BASED ON PRIOR LAND TYPE DATABASE SUPPORT
Authors: Zhou X. Y. , Sun L.
Published: August 2020

Abstract. Cloud shadow detection is one of the basic step for remote sensing image processing. The threshold method is commonly used currently because of its easy implementation and good accuracy. Aiming at the problems that common threshold settings are difficult to meet the complex surface conditions and the results is two-value, this paper proposes a detection method of cloud shadow pixels based on land cover data support by calculating shadow probabilities using Landsat 8 data as an example. Then, a validation with visual interpretation is used to verify the accuracy. The results show that the method can achieve high cloud shadow detection results.
RADAR-DERIVED INTERNAL LAYERING AND BASAL ROUGHNESS CHARACTERIZATION ALONG A TRAVERSE FROM ZHONGSHAN STATION TO DOME A, EAST ANTARCTICA
Authors: Tang X. , Luo K. , Guo J.
Published: August 2020

Abstract. The internal layers of ice sheets from ice-penetrating radar (IPR) investigation preserve critical information about the englacial conditions and ice-flow field. This paper presents a new detailed analysis of the spatial distribution characteristics of internal layers and subglacial topography of East Antarctic ice sheet (EAIS) from Zhongshan station to Dome A. Taking the internal layering continuity index (ILCI) and basal roughness as indicators, it provides an opportunity to evaluate the past internal environment and dynamics of ice sheet. The radar data of 1244 km along a traverse between Zhongshan Station and Dome A of EAIS was collected during the 29th Chinese National Antarctic Research Expedition (CHINARE 29, 2012/2013). Except for the upstream of Lambert Glacier, the patterns of the folds in the internal layers are basically similar to the bed topography. The relatively flat basal topography and the decrease of ILCI with the deepening of the depth provide evidence for identifying previous rapid ice flow areas that the satellite cannot obtain, especially in the upstream of Lambert Glacier. Well continuous internal layers of Dome A almost extend to the bed, with high ILCI and high roughness characteristics. There are three kinds of basal roughness patterns in the whole traverse. The characteristics of the internal layer and basal topography of the traverse between Zhongshan Station and Dome A provide new information for understanding the ancient ice-flow activity and the historical evolution of EAIS.
PARAMETER ESTIMATION AND MOTION TRACKING OF PACK ICE FROM FY-3/MERSI IMAGES
Authors: Zhou Y. , Du J. , Zhang Y. , Gong C. , Hu Y.
Published: August 2020

Abstract. A method to estimate the shape parameters and track the motion velocity of pack ice is presented. The method consists of sea ice recognition, pack ice extraction, parameters estimation and motion tracking. We try to estimate the shape parameters and track the motion velocity from FY-3/MERSI images of Fram strait, which were covered by cloud less than 30%. It found that the pack ice concentration significantly decreases faster than sea ice concentration. The two parameters indicate the distribution difference between sea ices and pack ices. The change of the perimeter and mean clamp diameter are obvious owing to they were sensitive to the edge of the pack ices. But the small change of roundness, convexity and width-height ratio indicate the shape similarity of pack ices in various size. More than 80% of the pack ices in the study region are tracked successfully by the proposed method. The resulting motion vectors in the overlapping zones are found to match well with the polar daily grid sea ice motion vectors provided by the National Snow and Ice Data Centre. The method can provide the actual motion vector of pack ices to improve the distribution and details of the grid-to-grid motion vectors.
OVERVIEW ON THE DEVELOPMENT AND EVOLUTION OF EARTH OBSERVATION RESEARCH AND APPLICATIONS PROGRAMMES FOR AGRICULTURE AND ENVIRONMENT DURING THE LAST THREE DECADES IN ROMANIA
Authors: Badea A. , Moise C. , Dana Negula I. , Poenaru V. D. , Iordan D. , Ortan A. , Burghila D.
Published: August 2020

Abstract. Following the fall of communism in 1989, the R&D sector started a modernization process. By establishing in 1995 a structure dedicated to the space activities – Romanian Space Agency (ROSA) – the Government recognized the importance of this innovative strategic domain. The National Space Strategy defined by means of the RTD policy, with effects on both academia and industry, had three objectives since the 90’s: Participation to international space missions and programmes, Development of specific national projects and Capacity building at national level. In time, the experience acquired in the implementation of CIS, LCCS and LPIS/IACS projects offered the possibility to establish new certitudes for the evolution of the domain. The main development directions had been oriented towards the implementation of dedicated applications to answer problematics concerning smart agriculture, traceability, better agro-environmental practices and the relation with other scientific domains (e.g. cultural heritage). The partnership between a strong Governmental R&D structure – ROSA – and the University of Agronomic Sciences and Veterinary Medicine of Bucharest (USAMVB) demonstrates the capacity to find solutions for promoting space EO technologies and adapt the higher education curricula in synergy with the development of the ambitious European space programme evolution.
ESTIMATION OF SOIL LOSSES BY THE IMPROVED TILLAGE HOMOGENIZATION MODEL AND RUSLE MODEL
Authors: Bouhlassa S. , Bouhsane N.
Published: August 2020

Abstract. Soil erosion by water is a major environmental problem in the Mediterranean areas. It results in land degradation and soil losses, decreases soil structural stability, and increases soil erodibility. Hence, the need for reliable scientific methods for obtaining soil erosion data becomes crucial. The study aims to estimate soil loss in the Moroccan watershed using two soil erosion estimation models and to discuss the differences between those models. The first model used in this study is the improved tillage homogenization model (T-H) which permits to predict the magnetic susceptibility values after erosion, the second one is the empirical model based on the Revised Universal Soil Loss Equation RUSLE. The results showed that: i) higher soil losses using tillage homogenization (T-H) model have occurred in the upper and lower slopes in the cultivated transect, and in the middleslopes and lower slopes in the forested transect; ii) the average of annual soil loss obtained by RUSLE model is about 20.21 t/ha/yr; iii) T-H model allows us to estimate the total cumulative soil erosion during the past and, while RUSLE model is designed for predicting annual soil loss resulting from sheet erosion under given conditions.
Shifting Definitions of Hazardous Wastes
Authors: Colten Craig
Published: August 2020

This paper addresses the emergence of concern with hazardous wastes and the legal liabilities attached to them long before the first federal legislation in the U.S. explicitly using the term; a simultaneous search for marketable by-products during the first three quarters of the twentieth century as a means to decrease the volume of wastes while also diminishing the perceived threat; and the eventual adoption of a legal tactic that asserted absence of liability before formal federal definitions of hazardous wastes. Based on a review of industry and waste management literature, it exposes deliberate efforts on the part of major industry trade organizations to dampen public calls for litigation by making the case that wastes were manageable, recoverable, and non-threatening. These steps sought to offset potential disruptions to their operations by imposing additional costs on waste treatment. When federal legislation became a reality in the 1970s, defenders of industrial practices that created hundreds of hazardous waste sites made the arguments that hazardous properties of wastes were unknown at the time of their disposal. The litigation that swirled around the federal laws proved disruptive and reflect a issue delayed not eliminated.
Mal-estar docente na escolarização: reflexões a partir do relatório escolar.
Authors: Nascimento Rafaela Amaral Cunha do , Carneiro Cristiana
Published: August 2020

Compreendendo o mal-estar como consequência dos conflitos inevitáveis entre o individual e o coletivo (Freud, 1930/1995), o presente trabalho tem como proposta contribuir para a investigação do mal-estar e sua expressão em professores. Partindo do entendimento que a expressão do mal-estar se constitui em um crivo de compreensão para o descontentamento frente às exigências da cultura sobre o sujeito, pergunta-se como o mal-estarse apresenta referido à relação professor-aluno. O estudo surgiu a partir da experiência de um grupo de pesquisa feito em parceria entre as faculdades de Educação da UFRJ e da UFF e também o Instituto de Psiquiatria da UFRJ com o SPIA, Serviço de Psiquiatria da Infância e Adolescência, que objetivou questionar como o mal-estar é vivenciado pelos diversos agentes envolvidos no processo educacional. Neste trabalho, especificamente, através de uma análise documental da escrita do relatório escolar, temos como objeto odiscurso de educadores através de 12 relatórios escolares encaminhados aos pais e/ou à saúde mental. O estudo compreende que o mal-estar como ferramenta teórico-conceitual para pensar o relatório, contribui para uma reflexão sobre possíveis atravessamentos subjetivos no cotidiano de educadores e alunos.
Information and Communication Technology and Growth in the Dominican Republic Microbusinesses
Authors: Ortiz-Medina Marina , Maldonado-Guzmán Gonzalo
Published: August 2020

There is a growing concern on the part of researchers, academics and professionals in business and management sciences, to find those variables that have a greater degree of influence on the level of growth of microenterprises, and within the various existing variables In current literature, information and communication technologies (ICTs) seem to be the variable that generates the most positive effects on microenterprises, both in developed and developing countries. Therefore, the essential objective of this empirical study is to analyze the relationship between the adoption and use of ICTs of microenterprises located in the Dominican Republic and their level of growth, for which a sample of 1,199 microenterprises was considered. The results obtained show that ICTs have a significant positive relationship in the level of microbusiness growth.
Basic serum biochemical parameters in the assessment of calcium-phosphate metabolism in children
Authors: Litwin Anna , Bugajska Jolanta , Berska Joanna , Sztefko Krystyna
Published: August 2020

Introduction: The calcium-phosphate homeostasis is important for proper child growth and development and vitamin D plays a crucial role in this process. Aim: The aim of the study was to assess the relationship between total calcium (Ca), phosphates (Pi), parathyroid hormone (PTH) and the concentration of 25-hydroxycholecalciferol (25 (OH) D3) in children. Materials and methods: 164 serum samples were collected from children (1 day to 18 years) hospitalized in University Children’s Hospital in Krakow. Concentrations of Ca, Pi (dry chemistry-method), PTH (immunoradiometric-method) and 25(OH)D3 (HPLC) were determined. The results were analysed for all children, regardless of the age and for children under and above the age of four. Results: Analyzing all results, the mean of Ca concentration was significantly higher in the children with optimal 25(OH)D3 concentration compared to the children, who had 25(OH)D3 deficiency (p < 0.05). In samples from children ≤4 years of age, the significantly higher mean concentrations of Ca and Pi in the children with optimal 25(OH)D3 concentration compared to the children, who had suboptimal levels of 25(OH)D3 were found (p = 0.04; p = 0.002; respectively). For all results and for results from children ≤ 4 years of age, Ca and Pi concentrations were positively correlated with 25(OH)D3 concentration (p < 0.002, p < 0.01; p < 0.003, p < 0.004; respectively), there were no relationship between PTH and 25(OH)D3 concentrations. Conclusion: Comparing the results of calcium and phosphate concentration only to the appropriate reference ranges may not be sufficient to evaluate calcium-phosphate metabolism. Probably the reference values for total calcium and phosphates should be established depending on vitamin D levels, especially for young children.
Concentration of 25-hydroxyvitamin D in 246 men’s blood serum population on Wroclaw
Authors: Stacherzak-Pawlik Jolanta , Najmrocka Marlena
Published: August 2020

The aim of the study was to analyze vitamin D concentrations in the blood of 246 men aged 16–89 in the period from September 2017 to February 2018. As the material for research used the results of 25(OH)D concentration determinations from the Laboratory of the Lower Silesian Medical Center DOLMED S.A. The assays were performed using the Roche Diagnostics – Cobas e410 immunochemical analyzer. Vitamin D test was used. It is the competence assay, which is based on the phenomenon of ectrochemiluminescence (ECLI). The analysis showed that the average concentration of vitamin D in the body of the studied patients was 27.7 ng/ml. 6% of men tested had a deficit, 26% had a deficiency, and 27% had hypovitaminosis. The concentration of the housing in the reference range were observed in 41% of research. The relationship between age and 25 (OH) D concentration was demonstrated. With increasing age, the concentration of vitamin D increases. In the population studied, there were no concentrations higher than 80 ng/ml. The relationship between calcidiol concentration and the month in which the study was performed was also demonstrated. The statistical analysis of the obtained data was made using Statistica version 13 and Microsoft Excel 2016.
Assessment of the usefulness of macroenzyme determination in the situation of
increased plasma enzyme activity in the absence of clinical symptoms
Authors: Marczak-Karpina Beata , Jasińska Maria , Poniewierka Elżbieta , Frączkowski Marek , Dudkowiak Robert , Kempiński Radosław
Published: August 2020

Introduction: The increased activity of serum enzymes is usually a reason of multiple, often expensive and invasive diagnostic procedures.
However, there are situations in which abnormal enzyme activity persists for many months or years, and detailed studies do
not confirm the existence of anatomic disease. Such is the case when enzymes form complexes with immunoglobulins on the basis
of the immune antigen-antibody reaction. This phenomenon is usually benign condition, is transient and does not require treatment.
Aim of study: Detection of the macroenzymes in patients with elevated serum enzyme activity. Evaluation of the relationship between
the presence of macroenzymes and the age of patients, body mass index, lipid profile, chronic and autoimmune diseases.
Material and methods: Macroenzymes were examined by polyethylene glycol precipitation (PEG) in 121 patients with elevated values
of liver or pancreatic enzymes.
Results: In the study group, a statistically significant difference was found comparing the BMI of men and women. BMI was significantly
higher in men with macroenzymes (p = 0.006). It was shown that the BMI of people with serum macroenzymes is significantly higher
(p = 0.049) than those without macroenzymes. A statistically significant correlation was observed between the presence of macroamylase
and body weight, r = 0.33, p = 0.039. A positive correlation of triglycerides and macrogenzofacts in the serum was found. Macroamylase
was observed the most frequently in the healthy group and those suffering from chronic diseases (45.83% and 42.86%). In the group of
autoimmune diseases (autos) the most common was macro-GGTP (42.86%). In patients with inflammatory bowel disease, 80% of the
confirmed macroenzymes in serum were macro-CK.
HCH-Contaminated Soils and Remediation Technologies
Authors: Santos López Aurora , M. Dominguez Torre Carmen , Lorenzo Fernández David
Published: August 2020

The production of lindane (gamma isomer of hexachlorocyclohexane, γ-HCH) in the second half of the twentieth century was an inefficient process that generated vast amounts of residues of other HCH isomers, without any pesticide activity. These residues were often dumped in an uncontrolled way or unsecured landfills in points near the production sites, causing hot spots of soil and groundwater contamination on all continents. Given the persistence and hydrophobicity of these pollutants, the problem generated decades ago is still a challenge to be solved. Several technologies, based on physical, chemical, and biological treatments, have been proposed for the remediation of HCH-contaminated soils. This chapter reviews the particularities of this kind of contamination and critically examines the bases and results of the technologies applied, paying special attention to the physicochemical remediation processes.
Consumers’ Resistance and Continued Use Intention of Self-service Kiosk
Authors: Kim Hyo-Jung , Lee Jin-Myong
Published: August 2020

Service providers have introduced interactive devices such as self-service kiosks to provide convenient and efficient services to consumers. Self-service kiosks are one of the most diverse technological forms of self-service technologies that provide control and freedom to consumers as well as reduce the frustration of line-ups. This study explores the predictors of consumer resistance and continued use intention with regard to self-service kiosks. It adopts three constructs on the following variables: perceived innovation characteristics, consumer characteristics, and gamification. An online self-administered survey was conducted, and 343 users of self-service kiosk services, aged between 20 and 59, were included in the analysis. The study used the SPSS 23.0 program to perform a descriptive analysis along with, t-test, ANOVA, correlation analysis, and regression analysis. First, convenience, controllability, and gamification negatively influenced consumer resistance to self-service kiosks. Second, human alienation and sociability positively influenced consumer resistance to self-service kiosks. Third, convenience and gamification positively influenced the continued use intention with regard to self-service kiosks. Last, the risk of functionality, human alienation, and sociability negatively influenced continued use intention with regard to selfservice kiosks. The results contribute to the literature because few studies have examined what drives the resistance of users and continued use intention with regard to self-service kiosks. It also provides service providers and practitioners with insights and strategies on how to overcome consumer resistance.
Influence of Subsystem between Parent-in-law and Children-in-law on Marital Adjustment in Marital Subsystem
Authors: Jeon Sesong
Published: August 2020

This study investigates the effect of in-law relationship on the marital adjustment of married couples by considering family-oriented Korean culture. Previous in-law studies did not consider the influence of another party who did not attend the survey due to sampling limitations. However, the marital adjustment of married couple and the satisfaction of the relationship with parents-in-law are two-way relationships that affect each other and are not one-sided relationships. By considering the non-independence of the couple’s data, Actor-Partner Interdependence Model (APIM) was utilized to examine the structural relationship between marital adjustment (marital satisfaction and marital stability) and in-law relationship quality (relationship satisfaction between mother-in-law and daughter-in-law for wives, relationship satisfaction between mother-in-law and son-in-law for husbands) of 203 married couples. Results indicated that a high satisfaction of wives’ in-law relationship increased personal marital adjustment as well as husbands’ marital adjustment. The husbands’ positive relationship with in-laws also increased personal marital adjustment and their wives’ marital adjustment. The results of this study can be used as basic data for program development and counseling for healthy in-law relationship as well as educational data for couples intending to marry.