bluuebunny/crossref_metadata_2025 huggingface dataset:
Responses of an abyssal meiobenthic community to short-term burial with crushed nodule particles in the south-east Pacific
Authors: Mevenkamp Lisa , Guilini Katja , Boetius Antje , De Grave Johan , Laforce Brecht , Vandenberghe Dimitri , Vincze Laszlo , Vanreusel Ann
Published: June 2019

Abstract. Increasing industrial metal demands due to rapid
technological developments may drive the prospection and exploitation of
deep-sea mineral resources such as polymetallic nodules. To date, the
potential environmental consequences of mining operations in the remote deep
sea are poorly known. Experimental studies are scarce, especially with
regard to the effect of sediment and nodule debris depositions as a
consequence of seabed mining. To elucidate the potential effects of the
deposition of crushed polymetallic nodule particles on abyssal meiobenthos
communities, a short (11 d) in situ experiment at the seafloor of the Peru Basin
in the south-east Pacific Ocean was conducted in 2015. We covered abyssal,
soft sediment with approx. 2 cm of crushed nodule particles and sampled the
sediment after 11 d of incubation at 4200 m water depth. Short-term
ecological effects on the meiobenthos community were studied including
changes in their composition and vertical distribution in the sediment as
well as nematode genus composition. Additionally, copper burden in a few
similar-sized but randomly selected nematodes was measured by means of
micro
X-ray fluorescence (µXRF). At the end of the experiment, 46±1 %
of the total meiobenthos occurred in the added crushed nodule layer, while
abundances decreased in the underlying 2 cm compared to the same
depth interval in undisturbed sediments. Densities and community composition
in the deeper 2–5 cm layers remained similar in covered and uncovered
sediments. The migratory response into the added nodule material was
particularly seen in polychaetes (73±14 %, relative abundance
across all depth layers) copepods (71±6 %), nauplii (61±9 %) and nematodes (43±1 %). While the dominant nematode genera
in the added nodule material did not differ from those in underlying layers
or the undisturbed sediments, feeding type proportions in this layer were
altered, with a 9 % decrease of non-selective deposit feeders and an
8 % increase in epistrate feeders. Nematode tissue copper burden did not
show elevated copper toxicity resulting from burial with crushed nodule
particles. Our results indicate that burial with a 2 cm layer of crushed
nodule particles induces changes in the vertical structure of meiobenthos
inside the sediment and an alteration of nematode feeding type proportions
within a short time frame of 11 d, while nematode tissue copper burden
remains unchanged. These findings considerably contribute to the
understanding of the short-term responses of meiobenthos to physical
disturbances in the deep sea.
The influence of tropical Indian Ocean warming and Indian Ocean Dipole on the surface chlorophyll concentration in the eastern Arabian Sea
Authors: Sankar Syam , Thondithala Ramachandran Anoop , Franck Eitel Kemgang Ghomsi , Kondrik Dmitry , Sen Radharani , Madipally Ramesh , Pettersson Lasse H.
Published: June 2019

Abstract. This study examines the role of increased Indian Ocean warming and positive Indian Ocean Dipole (IOD) events on the surface chlorophyll concentration in the Eastern Arabian Sea (EAS) during the period 1998 to 2014. Remotely sensed surface chlorophyll concentration – during the month of October when IOD strength is maximum – at three selected areas in the EAS, viz., the central eastern Arabian Sea (CEAS, 73° E–76° E, 13° N–18° N), south eastern Arabian Sea (SEAS, 74° E–77° E, 8° N–13° N) and the southern tip of India (TIP, 74° E–78° E, 5° N–8° N) shows a steady decreasing trend, though not statistically significant. The EAS also has a higher warming trend when compared to the western basin during the study period. Our analysis has shown that in the EAS, local surface winds, remote forcing by equatorial winds and the surface and sub-surface oceanic circulation features are less (respectively more) favorable for inducing coastal upwelling during positive (respectively negative) IOD years. The Dipole Mode Index (DMI) and surface chlorophyll concentration in the EAS is significantly and negatively correlated, pointing to the fact that in the event of occurrence of frequent positive IOD years under a global warming regime, the surface chlorophyll concentration is likely to decrease during fall.
EVALUATION OF DIGITAL ELEVATION MODELS FOR GEOMORPHOMETRIC ANALYSES ON DIFFERENT SCALES FOR NORTHERN CHILE
Authors: Kramm T. , Hoffmeister D.
Published: June 2019

Abstract. The resolution and accuracy of digital elevation models (DEMs) have direct influence on further geoscientific computations like landform classifications and hydrologic modelling results. Thus, it is crucial to analyse the accuracy of DEMs to select the most suitable elevation model regarding aim, accuracy and scale of the study. Nowadays several worldwide DEMs are available, as well as DEMs covering regional or local extents. In this study a variety of globally available elevation models were evaluated for an area of about 190,000 km2. Data from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30 m and 90 m, Advanced Land Observing Satellite (ALOS) World 3D 30 m and TanDEM-X WorldDEM™ – 12 m and 90 m resolution were obtained. Additionally, several very high resolution DEM data were derived from stereo satellite imagery from SPOT 6/7 and Pléiades for smaller areas of about 100–400 km2 for each dataset. All datasets were evaluated with height points of the Geoscience Laser Altimeter System (GLAS) instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite on a regional scale and with nine very high resolution elevation models from UAV-based photogrammetry on a very large scale. For all datasets the root mean square error (RMSE) and normalized median absolute deviation (NMAD) was calculated. Furthermore, the association of errors to specific terrain was conducted by assigning these errors to landforms from the topographic position index (TPI), topographic roughness index (TRI) and slope. For all datasets with a global availability the results show the highest overall accuracies for the TanDEM-X 12 m (RMSE: 2.3 m, NMAD: 0.8 m). The lowest accuracies were detected for the 30 m ASTER GDEM v3 (RMSE: 8.9 m, NMAD: 7.1 m). Depending on the landscape the accuracies are higher for all DEMs in flat landscapes and the errors rise significantly in rougher terrain. Local scale DEMs derived from stereo satellite imagery show a varying overall accuracy, mainly depending on the topography covered by the scene.
FEATURE SELECTION OF OPTICAL SATELLITE IMAGES FOR CHLOROPHYLL-A CONCENTRATION ESTIMATION
Authors: Nguyen M. V. , Chu H. J. , Lin C. H. , Lalu M. J.
Published: June 2019

Abstract. Healthy inland freshwater sources, such as lakes, reservoirs, rivers, and streams, play crucial roles in providing numerous benefits to surrounding societies. However, these inland water bodies have been severely polluted by human activities. Therefore, long-term monitoring and real-time measurements of water quality are essential to identify the changes of water quality for unexpected environmental incidents avoidance. The success of satellite-based water quality studies relies on three key components: precise atmospheric correction method, optimization algorithm, and regression model. Previous studies integrated various algorithms and regression models, including (semi-) empirical or (semi-) analytical algorithms, and (non-) linear regression models, to obtain satisfactory results. Nevertheless, the selection of appropriate algorithm is complex and challenging because of the fact that the changes in chemical and physical properties of water can lead to different method determination. To alleviate the aforementioned difficulties, this study proposed a potential integration which comprises an optimization method for efficient water-quality model selection, ordinary least squares regression, and an accurately atmospheric corrected dataset. Prime focus of this study is water-quality model selection which optimizes an objective function that aims to maximize prediction accuracy of regression models. According to the experiments, the performance of the selected water-quality model using proposed procedures, dominated that of the existing algorithms in terms of root-mean-square error (RMSE), the Pearson correlation coefficient (r), and slope of the regressed line (m) between measured and predicted chlorophyll-a.
QUALITY CHECK OF CRISIS MAPS PRODUCED OVER FIVE YEARS BY COPERNICUS EMS
Authors: Spasenovic K. , Carrion D.
Published: June 2019

Abstract. Crisis mapping is a widely used tool for the digital representation of a disaster situation. It provides stakeholders with spatial information of the crisis describing type and severity of damages, impact on the area and its population. The quality of crisis maps is of a great importance, since the disaster response depends on the provided information. In some cases, in order to deliver a map on time, its quality can be lower than expected. The evaluation of a big sample of rapid maps produced between 2013 and 2017 and collected from open source Copernicus service have been performed. The quality check has been performed by visual analysis, observing around 36 parameters defined in the validation protocol designed at the Joint Research Centre (JRC) of the European Commission. Overall conclusion is that crisis maps produced during the observed period have shown good level of the quality, that can satisfy the need of user. Still, there are some parameters that could be delivered with more details and precision. The results are analysed in details and remarks are presented.
INDOOR POSITIONING USING CONVOLUTION NEURAL NETWORK TO REGRESS CAMERA POSE
Authors: Ciou J.-M. , Lu E. H.-C.
Published: June 2019

Abstract. In recent years, the issue of indoor positioning has become more and more popular and attracted more attention. Under the absence of GNSS, how to more accurately position is one of the challenges on the positioning technology. Camera positioning can be calculated by image and objects. Therefore, this study focuses on locating the user's camera position, but how to calculate the camera position efficiently is a very challenging problem. With the rapid development of neural network in image recognition, computer can not only process images quickly, but also achieve good results. Convolution Neural Network (CNN) can sense the local area of the image and find some high-resolution local features. These basic features are likely to form the basis of human vision and become an effective means to improve the recognition rate. We use a 23-layer convolutional neural network architecture and set different sizes of input images to train the end-to-end task of location recognition to regress the camera's position and direction. We choose the sites where are the underground parking lot for the experiment. Compared with other indoor environments such as chess, office and kitchen, the condition of this place is very severe. Therefore, how to design algorithms to train and exclude dynamic objects using neural networks is very exploratory. The experimental results show that our proposed solution can effectively reduce the error of indoor positioning.
THE ROLES OF URBAN BUILDINGS AND VEGETATION IN ADJUSTING SEASONAL AND DAILY AIR TEMPERATURE
Authors: Lan Y. , Huang Z. , Guo R. , Zhan Q.
Published: June 2019

Abstract. Exploring the spatiotemporal patterns of the relationships between urban indicators and urban temperature is essential to improve the mitigation effectiveness when we intend to adjust built environment for moderating urban thermal environment. In this study, RS, GIS technology and statistical methods were involved to investigate the spatiotemporal patterns of the impacts of urban buildings and vegetation on Air Temperature (AT). Building Density (BD) and Normalized Difference Vegetation Index (NDVI) are the indicators for urban buildings and vegetation respectively. The objectives of this study are: 1) to determine an appropriate scale for examining the building-AT relationships and vegetation-AT relationships; 2) to explore the seasonal and daily characteristics of these relationships; and 3) to compare the effects of urban buildings and vegetation. The results show that, for both summer and winter, a scale of 200–250 m is optimal for examining building-AT relationships, and 960–1020 m is the desirable scale for studying vegetation-AT relationships. Based on the optimal scales, we find that for both buildings and vegetation, they only significantly impact night-time temperature in both summer and winter. For seasonal comparison, the building-AT relationships and vegetation-AT relationships are relatively stronger in summer than in winter, which are indicated by R-square of the regression results. When comparing the effects of urban building and vegetation, we find that increasing vegetation is more effective than reduce buildings to achieve the same air temperature reduction. Our findings are conducive to generating space-time targeted Urban Heat Island (UHI) mitigation strategies.
SEMANTIC VALIDATION OF SOCIAL MEDIA GEOGRAPHIC INFORMATION: A CASE STUDY ON INSTAGRAM DATA FOR EXPO MILANO 2015
Authors: Migliaccio F. , Carrion D. , Ferrario F.
Published: June 2019

Abstract. Social media data, such as Instagram posts, can be associated with spatial positions. This information can be exploited to perform spatial analyses, such as identifying distribution patterns of points representing the positions of social media users during an emergency or while attending a specific event or exhibition. However, the geolocation provided by Social Media Geographic Information (SMGI) needs to be validated, in order for the spatial data to be used in a meaningful way in subsequent spatial analyses or mapping procedures. In this paper, a case study is presented based on Instagram data collected during the first two months of the Expo Milano 2015 exhibition, where the spatial data have been validated by exploiting the semantic component of the posts.
UNBROKEN DIGITAL DATA FLOW IN THE BUILT ENVIRONMENT PROCESS – A CASE STUDY IN SWEDEN
Authors: Olsson P. O. , Johansson T. , Eriksson H. , Lithén T. , Bengtsson L.-H. , Axelsson J. , Roos U. , Neland K. , Rydén B. , Harrie L.
Published: June 2019

Abstract. An unbroken digital data flow would save substantial resources in the built environment process. In this study, which is part of a larger Swedish project, data delivery specifications and methods to integrate BIM and geodata are developed and tested with the aim to facilitate such an unbroken data flow. The main focus areas of the study are: (1) specifications that enables building permission applications based on BIM data to automate the building permission process, (2) reuse of as-built BIM models to update geodata when a building is constructed and (3) a national Swedish CityGML ADE for buildings. The study shows that building permission applications can be partly automated even though the delivery specifications were in the early stages of development at the time of a performed test case. With fully implemented delivery specifications more regulations can be checked. Furthermore, the study demonstrates how a BIM model can be georeferenced with a standard deviation of the transformation of 3 cm compared to field measurements performed with a total station. The georeferenced BIM model can then be converted to a LOD2 geodata building model to update existing geodata. Finally, a proposal for a national Swedish CityGML ADE for buildings is presented.
LOCAL MAXIMUM DENSITY APPROACH FOR SMALL-SCALE CLUSTERING OF URBAN TAXI STOPS
Authors: Wang H. , Chen X.-J. , Wang Y. , Shan J.
Published: June 2019

Abstract. Taxi trajectory data contains the detailed spatial and temporal traveling information of urban residents. By using a clustering algorithm, the hotspots’ distributions of pick-up and drop-off points can be extracted to explore the patterns of taxi traveling behaviors and its relationship with urban environment. Comparing with traditional methods that determine hotspots at a relatively large scale, we propose an approach to detect small-scale hotspots, so called docking points, to represent the local clusters in both sparse and dense stops areas. In this method, we divide the research area into grids and extract the docking points by finding local maximums of a certain range. The extracted docking points are classified into five levels for the subsequent analysis. Finally, to uncover detail characteristics of taxi mobility patterns, we analyze the distributions of docking points from three aspects – the overall, by day of the week, and by time of the day.
BUNDLE ADJUSTMENT OF SPACEBORNE DOUBLE-CAMERA PUSH-BROOM IMAGERS AND ITS APPLICATION TO LROC NAC IMAGERY
Authors: Haase I. , Gläser P. , Oberst J.
Published: June 2019

Abstract. The TU Berlin group of the Lunar Reconnaissance Orbiter Camera (LROC) team has implemented a Bundle Adjustment (BA) for spaceborne multi-lenses line scan imagers, by rigorously modeling the geometric properties of the image acquisition. The BA was applied to stereo image sets of the LROC Narrow Angle Camera (NAC) and first results show, that the overall geometry of the stereo models were significantly improved. Ray intersection accuracies of initially up to several meters were homogenized within the integrated stereo models and improved to 0.14 m on average. The mean point error of the adjusted 3D object points was estimated by the BA to be 0.95 m. The inclusion of available Lunar Orbiter Laser Altimeter (LOLA) shots as 3D ground control to the BA, accurately tied to the image space by an aforegoing co-registration, allowed to register the final adjusted NAC DTM to the currently most accurate global lunar reference frame. The BA also provides accuracy assessments of the individual LOLA tracks used for georeference during the adjustment, which will be useful to further assess LOLA derived products.
AUTOMATED DETECTION OF LUNAR RIDGES BASED ON DEM DATA
Authors: Peng M. , Wang Y. , Yue Z. , Di K.
Published: June 2019

Abstract. Wrinkle ridges are a common feature in the lunar maria and record subsequent contraction of mare infill. Automatic detection of wrinkle ridges is challenging because the ridges are of irregular shapes and many ridges have been eroded and/or degraded over time. The proposed method consists of the following steps. First, as the slope can reflect the gradient changes of the ridge rims to a certain extent, the slope map is generated and converted to a grayscale (0–255) image. Then the phase symmetry of the slope map is calculated with filter wavelength and filter scales parameters, which reduce the regions into symmetry regions. Next, a regional threshold is applied to limit the ridge candidates. Candidates with values less than the threshold are rejected. Moreover, the images are processed using a series of morphological operations, such as close, open, edge linking and noise removal. Finally, after thresholding the ridge map can be obtained. An experiment was performed using Lunar Reconnaissance Orbiter Camera (LROC) WAC image and topographic data from LOLA, the results demonstrate promising performance with detection percentage from 73 to 90.
ASSESSMENT OF FEATURE DETECTORS AND DESCRIPTORS IN REMOTE IMAGES OF PLANETARY BODIES
Authors: Speyerer E. J.
Published: June 2019

Abstract. Algorithms to detect, describe, and match common features in image sets are expanding to new worlds with the integration of the OpenCV feature matching framework in a popular mapping tool for planetary images (ISIS3). These algorithms provide a new approach to register images and build image-based control networks. However, the natural landscape of the Moon and other planetary bodies pose new challenges such as numerous features that appear similar (i.e., impact craters and boulders). In addition, planetary image sets vary in scale, orientation, and noise properties, especially when conducting cross instrument and cross mission comparisons. This study assesses a collection of common feature detector and descriptor algorithms to examine how they adapt to these challenges. With our analysis, we did not identify an ideal detector and descriptor combination that exists for our diverse lunar dataset. However, we did identify where particular algorithms succeed and identify their shortcomings. By knowing these capabilities, users can identify the proper set of algorithms to apply to an image set given the presence of noise and variations to scale and orientation.
A SPATIAL DATABASE MODEL FOR MOBILITY MANAGEMENT
Authors: Ajmar A. , Arco E. , Boccardo P.
Published: June 2019

Abstract. In urban and metropolitan context, Traffic Operations Centres (TOCs) use technologies as Geographic Information Systems (GIS) and Intelligent Transport Systems (ITS) to tackling urban mobility issue. Usually in TOCs, various isolated systems are maintained in parallel (stored in different databases), and data comes from different sources: a challenge in transport management is to transfer disparate data into a unified data management system that preserves access to legacy data, allowing multi-thematic analysis. This need of integration between systems is important for a wise policy decision.This study aims to design a comprehensive and general spatial data model that could allow the integration and visualization of traffic components and measures. The activity is focused on the case study of 5T Agency in Turin, a TOC that manages traffic regulation, public transit fleets and information to users, in the metropolitan area of Turin and Piedmont Region.The idea is not to replace the existing implemented and efficient system, but to built-up on these systems a GIS that overpass the different software and DBMS platforms and that can demonstrate how a spatial and horizontal vision in tackling urban mobility issues may be useful for policy and strategies decisions. The modelling activity take reference from a review of transport standards and results in database general schema, which can be reused by other TOCs in their activities, helping the integration and coordination between different TOCs. The final output of the research is an ArcGIS geodatabase, which enable the customised representation of private traffic elements and measures.
K-NEAREST NEIGHBOUR QUERY PERFORMANCE ANALYSES ON A LARGE SCALE TAXI DATASET: POSTGRESQL VS. MONGODB
Authors: Coşkun İ. B. , Sertok S. , Anbaroğlu B.
Published: June 2019

Abstract. The increasing volume of transport network data necessitates the use of a DataBase Management System (DBMS) to store, query and analyse data. There are two main types of DBMS: relational and non-relational. Many different DBMS are available on the market but only some of them could handle spatial data. Therefore, determining which DBMS to use for operational purposes is of interest to researchers and analysts working in spatial information science. One of the commonly used spatial queries in GIS is the k-Nearest Neighbour (kNN) of a given point. This paper analyses the performance of the kNN query in PostgreSQL and MongoDB, both being a representative of relational and NoSQL DBMS respectively. Two different metrics have been investigated to determine the performance: i) spatial accuracy and ii) run time. Haversine and Vincenty formulas are used to calculate the distance between the point and the determined neighbours, which are then used to determine the spatial accuracy of the DBMS. Sensitivity analysis have been carried out by varying the k value and the execution times are recorded. The experiments are carried out on New York City’s openly available taxi dataset consisting of millions of taxi pickup and dropoff points. The results indicate that MongoDB outperforms Postgres both in terms of execution time and spatial accuracy regardless the value of k. In order to facilitate reproducibility of the results, the developed software is shared on GitHub.
ANALYSIS OF FREE ROAD DATA IN TANZANIA, UGANDA AND KENYA USING FREE AND OPEN SOURCE SOFTWARE
Authors: Jovanovic S. , Jovanovic D. , Bratic G. , Brovelli M. A.
Published: June 2019

Abstract. Roads are one of the most important infrastructural objects for each country. Slow development of third world countries is partially influenced by missing roads. Therefore, United Nation (UN) enlisted them inside the ninth Sustainable Development Goal (SDG) whose achievement highly relies on geospatial data. Since the authoritative data for the majority of developing countries are incomplete and unavailable, the focus of this study is on free data. The conveyed research, explained in this paper, was divided in two parts. The first one refers to completeness and positional accuracy assessment of three different road data sets (freely available). The second part was focused only on OpenStreetMap (OSM) since it showed the best results in the previous stage. Thus, OSM was used to compute (in the second part of the research) and analyse the road accessibility rate within the buffer zone of two kilometers from human settlements. To locate human settlements, raster data, representing land covers were used. Results are pointing where the infrastructure is not mapped or is not present. The complete work was done using Free and Open Source Software, which is important, since the proposed procedure can be implemented by anyone.
DESIGN AND IMPLEMENTATION OF CROWDSOURCING BASED CHINA'S NATIONAL PUBLIC GEOSPATIAL INFORMATION COLLECTION SYSTEM
Authors: Zhang H. , Jiang J. , Huang W. , Yang L.
Published: June 2019

Abstract. As the basis of public geospatial information service, geospatial information data with wide coverage, strong timeliness, rich content and high positioning accuracy is the key infrastructure of geospatial infrastructure for building smart cities and digital China. How to collect and update massive geospatial information resources fast and efficiently has always been the bottleneck for the rapid development of surveying and mapping geospatial information science and technology and industries, and the construction of China's national spatial data infrastructure. At present, the mainstream of geospatial data collecting and updating in China is that the government and enterprise employ professional engineers to for this work, but the problems of professional and complex data processing process, data management level by level, closed and off-line data update mode lead to a relatively slow update rate and poor data actuality, which seriously restricted the applications of geospatial information service in the fields of government decision-making, planning and construction, resource and environment monitoring, and emergency response. The contributions to the geospatial information data from the public community has also been ignored. This paper addresses the issues of low efficiency on data collection and update occurring in China's national geospatial information service platform, proposing a solution for public geospatial data collection and update based on crowdsourcing. The key technologies of data collection, storage, reviews and publication are studied, and the basic technical process of online data update for the government and the public users is designed. In order to verify the effectiveness and practicality of the mode discussed above, a prototype system is developed by expanding China's national geospatial information service platform, which fulfilled data online collection and reviewing, such as POIs, roads, and residential areas. The system can provide new methods and reference ideas for the collection and update of spatial data for the national geospatial information public service platform. It is a useful supplement to the current spatial data collection and update, and has important significances.
PERFORMANCE EVALUATION OF SEQUENTIAL BAND ORIENTATION BY POLYNOMIAL MODELS IN HYPERSPECTRAL CUBES COLLECTED WITH UAV
Authors: Berveglieri A. , Tommaselli A. M. G. , Santos G. , Santos L. D. , Honkavaara E.
Published: June 2019

Abstract. A study on orientation of hyperspectral band cubes acquired with frame camera is presented in this paper. The camera technology is based on a tuneable Fabry-Perot Interferometer (FPI) and captures cubes of images sequentially using two sensors. However, the bands are not recorded at the same instant, which results different exterior orientation parameters (EOPs) for each image band. A technique based on polynomial model is assessed, which determines the EOPs within the hypercube from few sample bands, since a large number of bands are generated. Experiments were performed to assess the feasibility of using the polynomial technique. An analysis of the UAV trajectory was performed and the results of the polynomial technique were compared with those obtained by a conventional bundle adjustment. The trials showed that the results of both techniques were comparable, indicating that the time-dependent polynomial model can be used to estimate the EOPs of all spectral bands, without requiring a bundle adjustment including all bands. The accuracy of the block adjustment was analysed based on the discrepancies obtained from independent checkpoints. The root mean square error (RMSE) was calculated and showed an accuracy of approximately 1 GSD in planimetry and 1.5 GSD in altimetry. This accurate result is important because the proposed technique can significantly reduce the processing workload.
CALIBRATING PHOTOGRAMMETRIC AIRBORNE CAMERA SYSTEMS WITH DIFFRACTIVE OPTICAL ELEMENTS
Authors: Dahlke D. , Geßner M. , Meißner H. , Stebner K. , Grießbach D. , Berger R. , Börner A.
Published: June 2019

Abstract. This paper presents a laboratory approach for geometric calibration of airborne camera systems. The setup uses an incoming laser beam, which is split by Diffractive Optical Elements (DOE) into a number of beams with precisely-known propagation directions. Each point of the diffraction pattern represents a point at infinity and is invariant against translation. A single image is sufficient to allow a complete camera calibration in accordance with classical camera calibration methods using the pinhole camera model and a distortion model. The presented method is time saving, since complex bundle adjustment procedures with several images are not necessary. It is well suited for the use with frame camera systems, but it works in principle also for pushbroom scanners. In order to prove the reliability, a conventional test field calibration is compared against the presented approach, showing that all estimated camera parameters are just insignificantly different. Furthermore a test flight over the Zeche Zollern reference target has been conducted. The aerotriangulation results shows that calibrating an airborne camera system with DOE is a feasible solution.
AIRCRAFT BASED REAL TIME BUNDLE ADJUSTMENT AND DIGITAL SURFACE MODEL GENERATION
Authors: d’Angelo P. , Kurz F.
Published: June 2019

Abstract. This paper introduces a system for real-time generation of digital surface models (DSM) based on an optical multi-camera system flown on board of a manned airplane or helicopter. The system consists of high end consumer cameras, GNSS/IMU system, and on-board computers for real-time data processing. Usually, generation of digital surface models from aerial imagery is done in an off-line process, leading to delayed availability of height data. The proposed system processes data in real time on board of the aircraft and downlinks the generated DSM to a ground station. This paper evaluates the GNSS/IMU on-line solution quality and its impact on dense stereo matching. The proposed real time sliding window based bundle adjustment significantly improves image orientations and DSM quality, allowing generation of detailed digital surface models with a resolution of 2*GSD. Experiments using two flight patterns are conducted over the city of Landsberg and the resulting DSMs are evaluated against a LiDAR generated reference point cloud. The online bundle adjustment is shown to minimize the effect of systematic GNSS/IMU offsets while adding only a limited delay.
CAMERA CALIBRATION WITH IRRATIONAL RADIAL DISTORTION MODEL WITH ANALYTICAL SOLUTIONS
Authors: Ikokou G. B. , Smit J.
Published: June 2019

Abstract. Consumer grade digital cameras are widely used in many applications including Photogrammetric mapping and 3D modelling. One common limitation found in such cameras is radial lens distortions. To produce wide angle lenses camera manufacturers reduce the amount of barrel distortion by minimizing both the central and edge distortion profiles, resulting in a mixture of pincushion and barrel distortions for a single lens. These lenses also lack symmetry, making some of the existing distortion models almost ineffective. The mostly used model for radial distortion corrections is the polynomial model which is difficult to solve analytically especially when the model possesses many quadratic terms. Suggestions were made for division models but such models are not suitable when the lens field of view exceeds 180 degrees and exhibit some instabilities when dealing with large magnitude of distortion coefficients. Moreover mathematical formulations of some models cannot handle negative distortion coefficients. Attempts to improve the division models were made with proposals for rational models which present the advantage of handling larger distortion magnitude with fewer terms. However some of these models do not account for all the distortion coefficients in their solutions, limiting the potential of the techniques. This study presents an irrational distortion model with analytical solutions. The proposed model was tested with imagery captured by wide angle lenses and the experimental results reveal that the technique produced the best estimates of radial distortion coefficients. The proposed model was also able to capture image distortions originating from projection errors by the wide angles lenses used in this study.
MONITORING SUB-WEEKLY EVOLUTION OF SURFACE VELOCITY AND ELEVATION FOR A HIGH-LATITUDE SURGING GLACIER USING SENTINEL-2
Authors: Altena B. , Haga O. N. , Nuth C. , Kääb A.
Published: June 2019

Abstract. Currently, the Sentinel-2 twin satellite constellation of the Copernicus program is in operational mode and generates high repeat acquisitions at high-latitudes during polar day. These pushbroom satellites have a large field-of-view and are therefore ideal for simultaneous extraction of glacier displacement and elevation data. In this study we showcase the capabilities of this system set-up by generating time-series of glacier flow and elevation change over Negribreen, a tidewater glacier in Svalbard which nowadays is in its surge phase.
REMOTE SENSING OF GLOBAL MONTHLY EVAPOTRANSPIRATION WITH AN ENERGY BALANCE (EB) MODEL
Authors: Chen X. , Su Z. , Ma Y.
Published: June 2019

Abstract. A global monthly evapotranspiration (ET) product without spatial-temporal gaps for 2000–2017 is delivered by using an energy balance (EB) algorithm and MODIS satellite data. It provides us with a moderate resolution estimate of ET without spatial-temporal gaps on a global scale. The model is driven by monthly remote sensing land surface temperature and ERA-Interim meteorological data. A global turbulent exchange parameterization scheme was developed for global momentum and heat roughness length calculation with remote sensing information. The global roughness length was used in the energy balance model, which uses monthly land-air temperature gradient to estimate the turbulent sensible heat, and take the latent heat flux as a residual of the available energy. This study produced an ET product for global landmass, at a monthly time step and 0.05-degree spatial resolution. The performance of ET data has been evaluated in comparison to hundreds flux sites measurements representing a broad range of land covers and climates. The ET product has a mean bias of 3.3 mm/month, RMSE value of 36.9 mm/month. The monthly ET product can be used to study the global energy and hydrological cycles at either seasonal or inter-annual temporal resolution.
ICE FLOW VELOCITY MAPPING OF EAST ANTARCTICA FROM 1963 TO 1989
Authors: Cheng Y. , Li X. , Qiao G. , Ye W. , Huang Y. , Li Y. , Wang K. , Tian Y. , Tong X. , Li R.
Published: June 2019

Abstract. Long-time serial observation of surface ice flow velocity in Antarctic is a crucial component in estimating the mass balance of Antarctic ice sheet. However, there is a lack of historical continental scale velocity maps of Antarctica before the 1990s. Historical optical images such as ARGON and Landsat images before 1990s are difficult to be used for ice flow velocity mapping, due to the fact that they are mostly not strictly geo-processed (e.g., ortho-rectified) and the image quality is lower than those of recent sensors. This paper presents a systematic framework for developing a surface velocity map of East Antarctica from 1963 to 1989 based on historical ARGON and Landsat images, followed by analysis of spatial-temporal changes of the ice flow velocity in some major glaciers, as well as the dynamic changes. The preliminary comparison with existing products suggests that the glaciers in Wilkes Land experienced an increasing trend with obvious fluctuations during the past ∼50 years, while the glaciers near Transantarctic Mountains tended to be stable or slightly fluctuating to a certain degree.
EXTRACTION OF RIVERS AND LAKES ON TIBETAN PLATEAU BASED ON GOOGLE EARTH ENGINE
Authors: Xu R. G. , Qiao G. , Wu Y. J. , Cao Y. J.
Published: June 2019

Abstract. Tibetan Plateau (TP) is the most abundant area of water resources and water energy resources in China. It is also the birthplace of the main rivers in Southeast Asia and plays an important strategic role. However, due to its remote location and complex topography, the observation of surface hydrometeorological elements is extremely scarce, which seriously restricts the understanding of the water cycle in this area. Using remote sensing images to extract rivers and lakes on TP can obtain a lot of valuable water resources information. However, the downloading and processing of remote sensing images is very time-consuming, especially the processing of remote sensing images with large-scale and long time series often involves hundreds of gigabytes of data, which requires a high level of personal computers and is inefficient. As a cloud platform dedicated to data processing and analysis of geoscience, Google Earth Engine(GEE) integrates many excellent remote sensing image processing algorithms. It does not need to download images and supports online remote sensing image processing, which greatly improves the output efficiency. Based on GEE, the monthly data of Yarlung Zangbo River at Nuxia Hydrological Station and the annual data of typical lakes were extracted and vectorized from the pre-processed Landsat series images. It was found that the area of Yarlung Zangbo River at Nuxia Hydrological Station varies periodically. The changing trend of typical lakes is also revealed.
INVESTIGATION OF MOUNTAIN GLACIER STORAGE AND ITS CHANGES DURING 2000–2016 IN THE WESTERN TIBETAN PLATEAU USING COMBINED GROUND AND SATELLITE OBSERVATIONS
Authors: Zhang Y. , Zou X. , Gao H.
Published: June 2019

Abstract. The Upper Indus River Basin (UIB) has developed the largest midlatitude mountain glaciers worldwide. Ice thickness and volume distribution are important prerequisites for glaciological and hydrological investigations. In this paper, we presented detailed estimates of ice thickness in UIB region. Using ground penetrating radar, we measured glacier ice thickness on six typical glaciers; we obtained the parameters of the GlabTOP2 from these measurements and analyzed its uncertainty. Using the verified GlabTOP2 model, we simulated glacier ice thickness and volume in UIB subcatchments. The simulated results indicated that the UIB glacier thickness distribution was not uniform, ranging from 0 to 488 m, with an average thickness of 78 m. Total volume was defined as 1269.70 km3 in 2000, which corresponded to 1142.73 km3 water volume. According to the calculated discharge data from the Besham hydrological station, the total glacier volume of UIB generally can supply water resources for the downstream area for at least 15 years. And the glacier surface elevations generally decreased from 2000 to 2016 in UIB subbasins, although there was significant spatial heterogeneity in the seven subcatchments. The annual glacier surface elevation change rate of the Hindu Kush area was the smallest, followed by that of the Karakoram. The greatest glacier elevation change rate was observed in the Western Himalaya, indicating rapid glacial melting.
SPECTRAL PREPROCESSING FOR HYPERSPECTRAL REMOTE SENSING OF HEAVY METALS IN WATER
Authors: Lee M. , Chen X.-Y. , Lee H.-C.
Published: June 2019

Abstract. This study aims to investigate the feasibility of using hyperspectral remote sensing technique by visible-near infrared spectroradiometer (VNIR, FieldSpec HandHeld 2) for rapid water monitoring of heavy metal, followed by comparison of different spectral preprocessing methods for the development of quantitative predictive model. The water samples evaluated in this study were prepared in our laboratory by dilution of stock solutions. Heavy metals of lead (Pb), zinc (Zn) and copper (Cu) in the range of concentration between 100 to 2000 mg/L were selected as the target samples in this study. The sensitive bands for the target metals were characterized in the range from 800 nm to 1075 nm, based on the reflectance spectral data. Spectral data for developing of the quantitative predictive model was first preprocessed with first derivative and logarithm transformation, followed by establishing of the prediction model using multivariate linear regression (MLR). It was observed that increase in the number of sensitive bands for the MLR can significantly improve the adjusted R2 for the model. The prediction model for Cu was found to have the highest adjusted R2 of 0.92 and least normalized root mean square error (NRMSE) of 0.065, while using the reflectance values of 7 sensitive bands. This result could be attributed to the blue color characteristic of the solution, whereas the others remain clear. Additionally, the first derivative transformation was determined as the best method for predicting Pb, whereas the logarithm transformation provided the best outcomes for predicting Cu and Zn.
DETECTING CITRUS HUANGLONGBING IN BRAZILIAN ORCHARDS USING HYPERSPECTRAL AERIAL IMAGES
Authors: Moriya É. A. S. , Imai N. N. , Tommaselli A. M. G. , Berveglieri A. , Honkavaara E. , Soares M. A. , Marino M.
Published: June 2019

Abstract. Brazil is one of the world leaders in citrus plantation, and the production of orange juice is economically important in the export scenario, being regarded as a fundamental agricultural commodity in Brazil. The worst citrus disease is Greening, or Huanglongbing (HLB), a bacterial disease which cannot be cured and to which no plant variety is immune or resistant. Currently, control of HLB is through the inspection of orchards and the immediate elimination of plants displaying HLB symptoms, plus chemical or biological control of the insect vector (psyllid). The HLB disease has high economic impact on Brazilian and world citriculture, due to the extreme damage to crops. Based on remote sensing techniques, the mapping of diseased and healthy citrus plants from hyperspectral images was carried out, generating a product that could help in the monitoring and control of HLB in Brazilian citrus orchards. The methodology to produce a health map goes through the following stages: aerial image acquisition, radiometric field measurements, hyperspectral cube orientation, and data analysis for detection of HLB in citrus. The field survey was performed in Guacho Farm- Brazil and hyperspectral images were acquired by a Rikola camera onboard a light aircraft, obtaining images with 0.50 m of Ground Sample Distance (GSD). The hyperspectral cubes were classified with Spectral Angle Mapper (SAM) algorithm to produce the health map. Plants infected with HLB were detected with an accuracy 61.2%, the validation of the health map was verified by samples were analysed in the laboratory to confirm HLB.
MONITORING THE SURFACE SUBSIDENCE OF HANDAN CITY USING SENTINEL-1A IMAGES AND SBAS-INSAR TECHNOLOGY
Authors: Huang G. , Chen H. , Li X. , Cheng G. , Yu Z. , Gu H.
Published: June 2019

Abstract. The Sentinel-1 data is currently the latest free SAR data and is well suited for land subsidence monitoring based on InSAR technology due to its 6-day revisit cycle. In this paper, the urban area and surrounding areas of Handan City are used as research areas, and 29 scences of S1A data (December 2017 – December 2018) was used for time series SBAS processing. The results shows that the surface cumulative deformation ranged from -42 to 30 mm in most regions of Handan City. The maximum settlement is 69 mm, which is near the Hankuang Group Julong Company. The areas where the settlement is obvious include Wu'an City, Daishan Village, Dashe Town, Zhangxibao Town, Baijia Street, Dongxingtai Village, Gaonan Village and Hankuang Group Julong Company. Slightly elevated in the southeast of Handan City.
RADAR REMOTE SENSING APPLICATIONS IN LANDSLIDE MONITORING WITH MULTI-PLATFORM INSAR OBSERVATIONS: A CASE STUDY FROM CHINA
Authors: Qu T. , Xu Q. , Liu C. , Li Z. , Chen B. , Dai K.
Published: June 2019

Abstract. In China, landslides are widely distributed in the mountainous areas of western regions. Especially after the Wenchuan Earthquake in 2008, a large number of landslides were triggered. This work focuses on the deformation monitoring of Xishancun Landslide based on multi-platform spaceborne radar remote sensing techniques. The spatio-temporal deformation characteristics of landslide could be retrieved from time series InSAR processing with joint use of Sentinel-1 and TerraSAR-X datasets. Eventually, the deformation and evolution histories are cultivated thoroughly to realize an effective and comprehensive monitoring and research of Xishancun Landslide. This work concludes that spaceborne radar remote sensing applications could demonstrate great potentials to identify the spatio-temporal characteristics and investigate the kinematics for hazardous landslides, especially combined with in situ measurements and other remote sensing observations.
Slab Break-offs in the Alpine Subduction Zone
Authors: Kästle Emanuel D. , Rosenberg Claudio , Boschi Lapo , Bellahsen Nicolas , Meier Thomas , El-Sharkawy Amr
Published: June 2019

Abstract. After the onset of plate collision in the Alps, at 32–34 Ma, the deep structure of the orogen is inferred to have changed dramatically: European plate break-offs in various places of the Alpine arc, as well as a possible reversal of subduction polarity in the eastern Alps have been proposed. We review body-wave tomographic studies, compare them to our surface-wave-derived model for the uppermost 200 km, and reinterpret them in terms of slab geometries. We infer that the shallow subducting portion of the European plate is likely detached under both the western and eastern (but not the central) Alps. The Alps-Dinarides transition may be explained by a combination of European and Adriatic subduction. This would imply that the deep, high-velocity anomaly (> 200 km depth) mapped by tomographers under the eastern Alps is a detached segment of the European plate. The shallower fast anomaly (100–200 km depth) can be ascribed to European or Adriatic subduction, or both. These findings are compared to previously proposed models for the eastern Alps in terms of slab geometry, but also integrated in a new, alternative geodynamic scenario that best fits both tomographic images and geological constraints.