bluuebunny/crossref_metadata_2025 huggingface dataset:
IMPLEMENTATION AND EVALUATION OF A MOBILE MAPPING SYSTEM BASED ON INTEGRATED RANGE AND INTENSITY IMAGES FOR TRAFFIC SIGNS LOCALIZATION
Authors: Shahbazi M. , Sattari M. , Homayouni S. , Saadatseresht M.
Published: August 2012

Abstract. Recent advances in positioning techniques have made it possible to develop Mobile Mapping Systems (MMS) for detection and 3D localization of various objects from a moving platform. On the other hand, automatic traffic sign recognition from an equipped mobile platform has recently been a challenging issue for both intelligent transportation and municipal database collection. However, there are several inevitable problems coherent to all the recognition methods completely relying on passive chromatic or grayscale images. This paper presents the implementation and evaluation of an operational MMS. Being distinct from the others, the developed MMS comprises one range camera based on Photonic Mixer Device (PMD) technology and one standard 2D digital camera. The system benefits from certain algorithms to detect, recognize and localize the traffic signs by fusing the shape, color and object information from both range and intensity images. As the calibrating stage, a self-calibration method based on integrated bundle adjustment via joint setup with the digital camera is applied in this study for PMD camera calibration. As the result, an improvement of 83% in RMS of range error and 72% in RMS of coordinates residuals for PMD camera, over that achieved with basic calibration is realized in independent accuracy assessments. Furthermore, conventional photogrammetric techniques based on controlled network adjustment are utilized for platform calibration. Likewise, the well-known Extended Kalman Filtering (EKF) is applied to integrate the navigation sensors, namely GPS and INS. The overall acquisition system along with the proposed techniques leads to 90% true positive recognition and the average of 12 centimetres 3D positioning accuracy.
DETECTION AND QUANTIFICATION OF ROCK GLACIER CREEP USING HIGH-RESOLUTION ORTHOIMAGES OF VIRTUAL GLOBES
Authors: Kaufmann V.
Published: August 2012

Abstract. Rock glaciers are creep phenomena of mountain permafrost and are composed of ice and rocks. Active rock glaciers move downslope by force of gravity. Maximum creep/flow velocities of individual rock glaciers may vary from a few centimeters up to several meters per year, depending on the underlying terrain, mechanical parameters of the material involved, etc. Inter-annual variation of rock glacier flow has been observed and attributed to various reasons, e.g., climate change. It is believed that the observed warming of the atmosphere accelerates rock glacier flow. This paper proposes a method for detecting active rock glaciers and, where applicable, quantifying their movement relatively or absolutely using multi-temporal image data (i.e., high-resolution orthoimages/orthophotos) of virtual globes, such as Google Maps and Microsoft Bing Maps. The present work was originally triggered by the task of detecting all active rock glaciers of a larger mountain region, i.e., the western part of the Schober Mountains located in the Austrian Hohe Tauern range. In support of this task the proposed method was additionally applied to two well-studied rock glaciers, i.e., Hinteres Langtalkar (eastern part of the Schober Mountains) and Äußeres Hochebenkar (Ötztal Alps, Austria). In this paper we present the results obtained from the two rock glaciers. It can be summarized that change detection and consequently the high-precision measurement of flow velocities of active rock glaciers using image data (screen shots) of virtual globes (geobrowsers) is possible. It must be admitted, however, that the proposed method has some obvious drawbacks: (a) limited availability of high-resolution image data in high mountain areas, (b) limited availability of multi-temporal image data, (c) lack of information about exact acquisition dates or source of image data, (d) lack of information about the accuracy of the image data (orthophotos), and (e) potential legal obstacles to using the image data.
PHOTOGRAMMETRIC AND LIDAR DOCUMENTATION OF THE ROYAL CHAPEL (CATHEDRAL-MOSQUE OF CORDOBA, SPAIN)
Authors: Cardenal J. , Perez-Garcia J. L. , Mata E. , Hernandez M. A. , Mozas A. , Delgado J. , Lopez-Arenas A. , Meroño J. E.
Published: August 2012

Abstract. At present, cultural heritage documentation projects use a variety of spatial data acquisition techniques such as conventional surveying, photogrammetry and terrestrial laser scanning. This paper deals with a full documentation project based on all those techniques in the Royal Chapel located in the Cathedral-Mosque of Cordoba in Spain, declared World Heritage Site by UNESCO. At present, the Royal Chapel is under study for a detailed diagnostic analysis in order to evaluate the actual state of the chapel, pathologies, construction phases, previous restoration works, material analysis, etc. So in order to assist the evaluation, a documentation project with photogrammetric and laser scanner techniques (TLS) has been carried out. With this purpose, accurate cartographic and 3D products, by means of the integration of both image and laser based techniques, were needed to register all data collected during the diagnostic analysis.
FROM POINT CLOUD TO 3D MODEL, MODELLING METHODS BASED ON ARCHITECTURAL KNOWLEDGE APPLIED TO FORTRESS OF CHÂTEL-SUR-MOSELLE (FRANCE)
Authors: Alby E. , Grussenmeyer P.
Published: August 2012

Abstract. 3D survey techniques applied to buildings such as photogrammetry and laser scanning produces a volume of data very important. Upon acquisition, the issue of data management greatly influences the acquisition parameters and production data. Contemporary tools usually allow acquiring data sets denser than necessary without taking a very long acquisition times. We are interested in modeling from 3D data. There is no question here of mesh from the point cloud, but to model space according to their constituent elements. Data having a high density provide a rich description of the object. The issue of simplification raises the problem of loss of means of describing the object of interest. The final model, to keep the quality of description of point clouds, must remain very close to the initial data. This constraint derives the inverse problem. It is to be faithful to the data without performing mesh. The purpose of the study must remain the goal of modeling. Assumptions used to derive simple geometric primitives, which are assembled together the simplified model. The resulting model consists of surface distance for 92% of them within 5 cm of the point cloud. The model thus created is faithful to the cloud but also the rules of construction of the building which he prefigures representation.
THE NEW THREE-DIMENSIONAL VISUALIZATION METHOD OF HERITAGE SITES BY LIDAR DATA
Authors: Fujii N. , Saito K. , Chiba T. , Sata I. , Yoshinaga T. , Tasaki K.
Published: August 2012

Abstract. We introduce a new visualization method for the three dimensional data with laser scanning from helicopter to express of the detailed landscape with "Red Relief Image Map (RRIM)"and "3D-Viewer". This RRIM and 3D-Viewer’s method effectively represent 3D topographic information without any additional devices and stereopsis ability for the audience only through two dimensional medium and shows an appropriate form of every feature in the site. Chapters present what the laser scanning from helicopter is and show some examples of mounded tombs with RRIM and 3D-Viewer. This visualization technique including detailed topographical information and geographical coordinates can be directly linked to CAD and GIS system, therefore the LiDAR can easily produce a contour line, a cross section and a bird's-eye view at any place as well as measure the height of trees. This is different from other 3D topographic image with a shadow effect. Vegetation on the site is no longer obstacle to get detailed topographical information. Therefore, in Japan, this method is useful for huge mounded tombs thickly covered with trees, especially "Ryo-bo (imperial tomb)"which are administrated by the Imperial Household Agency and common people can't enter. Also a cluster of small mounded tombs which extend in the vast area called "Gunshufun" is shown effectively for the location of each mounded tomb. This method is suitable for understanding the structure of the sites in any wide spread archaeological fields. Moreover, in the management of heritages it is important that these data present precise information of the surface of lands to understand the present situation of heritages. Detailed topographical information by "LiDAR and Red Relief Image Map and 3DViewer" will open a new gate for managing of cultural heritage sites in the future.
FEATURE ANALYSIS FOR MULTI-WINDOW MATCHING
Authors: Chang W. C. , Chen L. C.
Published: August 2012

Abstract. Image matching is a practical way to build up the relationship between point pairs. In remote sensing and photogrammetry applications, area-based matching algorithms are usually used under control environment, such as fixing exterior orientation parameters, to reach high matching precision. In order to improve the reliability of image matching, area-based matching algorithms are frequently performed with image pyramid and epipolar constraints. Thus, Central-Left-Right matching (CLR matching) is proposed to enhance the reliability. The method is designed to cope with unreliable matching when the objects are with surface discontinuity. The CLR matching puts a candidate point in the center, left and right windows. Thus, the elements of target window and search window may be corresponded to the same objects if the candidate point is located in a vertical edge. In addition, the directions of features in the image may be varied because of the object diversity. Thus, the CLR matching would be better to combine with multi-window operation in accordance with the feature direction. This paper analyzed the feature direction first followed by the multi-window matching. The major works in this investigation contain feature extraction, feature analysis, and image matching. The experiments compared the results of traditional image matching, CLR matching, and multi-window matching. The experimental results indicate that the proposed method improves the accuracy of image matching.
DETERMINATION OF THE UAV POSITION BY AUTOMATIC PROCESSING OF THERMAL IMAGES
Authors: Hartmann W. , Tilch S. , Eisenbeiss H. , Schindler K.
Published: August 2012

Abstract. If images acquired from Unmanned Aerial Vehicles (UAVs) need to be accurately geo-referenced, the method of choice is classical aerotriangulation, since on-board sensors are usually not accurate enough for direct geo-referencing. For several different applications it has recently been proposed to mount thermal cameras on UAVs. Compared to optical images, thermal ones pose a number of challenges, in particular low resolution and weak local contrast. In this work we investigate the automatic orientation of thermal image blocks acquired from a UAV, using artificial ground control points. To that end we adapt the photogrammetric processing pipeline to thermal imagery. The pipeline achieves accuracies of about ±1 cm in planimetry and ±3 cm in height for the object points, respectively ±10 cm or better for the camera positions, compared to ±100 cm or worse for direct geo-referencing using on-board single-frequency GPS.
A STUDY ON AUTOMATIC UAV IMAGE MOSAIC METHOD FOR PAROXYSMAL DISASTER
Authors: Li M. , Li D. , Fan D.
Published: August 2012

Abstract. As everyone knows, some paroxysmal disasters, such as flood, can do a great damage in short time. Timely, accurate, and fast acquisition of sufficient disaster information is the prerequisite facing with disaster emergency. Due to UAV's superiority in acquiring disaster data, UAV, a rising remote sensed data has gradually become the first choice for departments of disaster prevention and mitigation to collect the disaster information at first hand. In this paper, a novel and fast strategy is proposed for registering and mosaicing UAV data. Firstly, the original images will not be zoomed in to be 2 times larger ones at the initial course of SIFT operator, and the total number of the pyramid octaves in scale space is reduced to speed up the matching process; sequentially, RANSAC(Random Sample Consensus) is used to eliminate the mismatching tie points. Then, bundle adjustment is introduced to solve all of the camera geometrical calibration parameters jointly. Finally, the best seamline searching strategy based on dynamic schedule is applied to solve the dodging problem arose by aeroplane's side-looking. Beside, a weighted fusion estimation algorithm is employed to eliminate the "fusion ghost" phenomenon.
DEVELOPMENT AND EVALUATION OF TECHNOLOGY EDUCATION USING EARTH OBSERVATION TECHNIQUE
Authors: Ito Y. , Teramoto Y. , Abe K.
Published: August 2012

Abstract. In the present study, we introduce to secondary education an Earth observation technique using synthetic aperture radar (SAR). The goal is to increase interest in and raise the awareness of students in the Earth observation technique through practical activities. A curriculum is developed based on the result of questionnaire surveys of school teachers. The curriculum is composed of 16 units. Teaching materials related to the Earth observation technique are researched and developed. We designed a visual SAR processor and a small corner reflector (CR) as a new teaching technique. In teaching sessions at secondary school, the developed teaching materials and software were used effectively. In observation experiments, students set up CRs that they had built, and ALOS PALSAR was able to clearly observe all of the CRs. The proposed curriculum helped all of the students to understand the usefulness of the Earth observation technique.
MODELING OF THE "PLAN DA MATTUN" ARCHAEOLOGICAL SITE USING A COMBINATION OF DIFFERENT SENSORS
Authors: Novák D. , Tokarczyk P. , Theiler P. W.
Published: August 2012

Abstract. Plan da Mattun is located at ~2200 metre above sea level in the Tasna valley in alpine south-eastern Switzerland. In this remote location, finds dating back to the time of Ötzi (3000 B.C.) were discovered by archaeologists from the University of Zurich. For detailed investigations of the site as well as for documentation and visualization purposes the archaeologists were interested in digital models of the terrain and of certain boulders. In the presented project a digital terrain model of the rock stream located at the beginning of the valley was created, as well as detailed models of four larger boulders. These boulders average to 15 metre in height and width. The roughness of terrain makes it difficult to access certain areas and requires using multiple surveying techniques in order to cover all objects of interest. Therefore the digital terrain model was acquired using a combination of terrestrial laser scanning (TLS) and photogrammetric recording from an unmanned aerial vehicle (UAV). The larger boulders were reconstructed with a combination of TLS, terrestrial and UAV-based photogrammetry. With this approach it was possible to acquire a highaccuracy dataset over an area of 0.12 km2 under difficult conditions. The dataset includes a digital terrain model with a ground sampling distance of 10 cm and a relative accuracy of 2 cm in moderately sloped terrain. The larger boulders feature a resolution of 1 cm and a relative accuracy of 0.5 cm. The 3D data is to be used both for archaeological visualization purposes and for geological analysis of the rock stream.
COMPARATIVE STUDY ON METHODS FOR 3D MODELLING OF URBAN AREAS
Authors: Oniga E.
Published: August 2012

Abstract. This article presents (comparatively) the methodology for creating a 3D model of the urban area, based on terrestrial laser scanner, traditional technologies of terrestrial photogrammetry and aerial images. We are reviewing the data sources, their preliminary processing to be brought in a common system and the software used for this purpose. The case study presents the comparative results obtained using the methods listed above. To obtain the 3D models with terrestrial laser scanner systems have been used the dates achieved with ScanStation 2. To obtain the 3D model drawn by traditional photogrammetric methods using the UMK terrestrial camera, have been used auxiliary dates from topographic measurements with GPS systems and total stations as well as the current topographic plans. For the 3D model creation based on the dates taken with aerial digital cameras, were used the aerial images, taken with the ADS40 photogrammetric aerial camera. The comparative study between the three methods was accomplished by analyzing the object space representation fidelity, the precision of the 3D models obtained by comparison of the distances, areas and volumes, comparing the execution time and execution costs. The article presents the conclusions, the advantages and disadvantages of the three technologies based on the criteria listed above.
E-LEARNING APPLICATIONS FOR URBAN MODELLING AND OGC STANDARDS USING HTML5 CAPABILITIES
Authors: Kaden R. , König G. , Malchow C. , Kolbe T. H.
Published: August 2012

Abstract. This article reports on the development of HTML5 based web-content related to urban modelling with special focus on GML and CityGML, allowing participants to access it regardless of the device platform. An essential part of the learning modules are short video lectures, supplemented by exercises and tests during the lecture to improve students' individual progress and success. The evaluation of the tests is used to guide students through the course content, depending on individual knowledge. With this approach, we provide learning applications on a wide range of devices, either mobile or desktop, fulfil the needs of just-in-time knowledge, and increase the emphasis on lifelong learning.
ISPRS STUDENT CONSORTIUM: THE NETWORK OF YOUTH IN GEOINFORMATION SOCIETY
Authors: Kivilcim C. O. , Sterenczak K. , Kanjir U. , Sengul A. , Stavbar G. , Pakdil M. E. , Lobo E. , Oo K. S.
Published: August 2012

Abstract. The ISPRS Student Consortium (SC) initiative started at the 20th ISPRS Congress in Istanbul, 2004.After four years of volunteer activity, an official structure for volunteers was needed. With the implementation of the SC Statutes in the ISPRS Beijing Congress in 2008, the first ISPRS Student Consortium Board Members were elected. Since this day, SC volunteers and supporters have continued to contribute through numerous activities in order to promote the Society and connect young people with a similar interest in the profession. So far, promotional activities have taken place in various places in Europe, North and Central America, Asia and Australia. SC members have not only participated in the events, but also organized activities, taken responsibilities and represented youth in ISPRS midterm symposiums and ISPRS Centenary Celebrations as well as other related events. Summer schools, as the main SC event, are organized with the help of ISPRS TC VI/5 and are focused on the needs and interests of scientific communities around the world. The SC community has been constantly growing with almost 750 members over 85 countries at present, registered through our self-developed website. The organization also publishes its own Newsletter four times per year, with the intention to transmit the messages and news from ISPRS and the SC. The Newsletter is a perfect platform for presenting useful technical, educational and informational material prepared by members and distributed freely among the supporters. Throughout time, the SC has received guiding, motivational and administrative support from WG VI/5 as well as TC VI and the ISPRS Council. Activities have been financially supported by foundations, commercial enterprises and academic organizations and many SC members have received grants to present their work in different scientific events. In addition, the SC has started and established permanent connections and signed agreements for better networking with the youth organizations of the sister Societies of ISPRS. This paper presents the achievements reached over the last four years, the experiences of the SC Board and Regional Representatives and the feedback from our members. It provides an insight for the youth organizations run under other scientific and technical societies. A vision for the continuum of the activities and establishing regional and national developments are suggested. A revised road-map for the future is outlined in the conclusion.
BUILDING INTERACTIVITY IN HIGHER EDUCATION TO SUPPORT STUDENT ENGAGEMENT IN SPATIAL PROBLEM SOLVING AND PROGRAMMING
Authors: Gulland E.-K. , Veenendaal B. , Schut A. G. T.
Published: August 2012

Abstract. Problem-solving knowledge and skills are an important attribute of spatial sciences graduates. The challenge of higher education is to build a teaching and learning environment that enables students to acquire these skills in relevant and authentic applications. This study investigates the effectiveness of traditional face-to-face teaching and online learning technologies in supporting the student learning of problem-solving and computer programming skills, techniques and solutions. The student cohort considered for this study involves students in the surveying as well as geographic information science (GISc) disciplines. Also, students studying across a range of learning modes including on-campus, distance and blended, are considered in this study. Student feedback and past studies reveal a lack of student interest and engagement in problem solving and computer programming. Many students do not see such skills as directly relevant and applicable to their perceptions of what future spatial careers hold. A range of teaching and learning methods for both face-to-face teaching and distance learning were introduced to address some of the perceived weaknesses of the learning environment. These included initiating greater student interaction in lectures, modifying assessments to provide greater feedback and student accountability, and the provision of more interactive and engaging online learning resources. The paper presents and evaluates the teaching methods used to support the student learning environment. Responses of students in relation to their learning experiences were collected via two anonymous, online surveys and these results were analysed with respect to student pass and retention rates. The study found a clear distinction between expectations and engagement of surveying students in comparison to GISc students. A further outcome revealed that students who were already engaged in their learning benefited the most from the interactive learning resources and opportunities provided.
SPECTRAL ANALYSIS OF DIFFERENT VEGETATION COVER USING THE HYPERION SENSOR – A CASE STUDY IN THE STATE OF RIO DE JANEIRO – BRAZIL
Authors: de Souza E. M. F. R. , Vicens R. S. , Rosa A. E. P. , Cruz C. B. M.
Published: August 2012

Abstract. The knowledge about of land use and current status of vegetation represent important steps in understanding the spatial dynamics in areas with increased removal of vegetation and human disturbance. This feature is very common in its Brazil considering the biophysical diversity observed. In this sense, interest in patterns and processes that lead to environmental changes has been receiving great support from geoprocessing and remote sensing for monitoring, environmental and planning of natural resources. Following this trend, the study uses products from hyperspectral geotechnology to identify new methods of analysis of the landscape, in areas with vegetation remnants of Atlantic Forest in the State of the Rio de Janeiro.
ANALYSIS OF CONCRETE REFLECTANCE CHARACTERISTICS USING SPECTROMETER AND VNIR HYPERSPECTRAL CAMERA
Authors: Lee J.-D. , Dewitt B. A. , Lee S.-S. , Bhang K.-J. , Sim J.-B.
Published: August 2012

Abstract. The purpose of this research is to extract spectral reflectance characteristics of concretes through basic experiment on concrete specimens and site experiment on actual concrete structures using a field portable spectrometer and a VNIR hyperspectral sensor. A spectrometer (GER-3700) and a VNIR hyperspectral camera (AisaEagle VNIR Hyperspectral Camera) were utilized for extracting spectral characteristics of concrete specimens and actual concrete structures. General concretes show similar pattern with correlation more than 80%, while super high strength concrete shows very different aspect from general concretes. The GER-3700 spectrometer and the VNIR camera were applied to extracting spectral characteristics of the actual concrete structures such as a bridge slab and pier in road construction site. We also made certain in not only interior experiment on concrete specimens but also site experiment on actual concrete structures that both the spectrometer and the VNIR camera vary in spectral reflectance depending on concrete strength. Afterwards if the studies on hyperspectral characteristics of worn-out concretes, concrete aggregate condition diversity, super high-strength concretes are performed in depth, it is helpful in stability evaluation and maintenance management of concrete-based structures or facilities using airborne or satellite hyperspectral images for a wide area.
HYPERSPECTRAL DATA CLASSIFICATION USING FACTOR GRAPHS
Authors: Makarau A. , Müller R. , Palubinskas G. , Reinartz P.
Published: August 2012

Abstract. Accurate classification of hyperspectral data is still a competitive task and new classification methods are developed to achieve desired tasks of hyperspectral data use. The objective of this paper is to develop a new method for hyperspectral data classification ensuring the classification model properties like transferability, generalization, probabilistic interpretation, etc. While factor graphs (undirected graphical models) are unfortunately not widely employed in remote sensing tasks, these models possess important properties such as representation of complex systems to model estimation/decision making tasks. In this paper we present a new method for hyperspectral data classification using factor graphs. Factor graph (a bipartite graph consisting of variables and factor vertices) allows factorization of a more complex function leading to definition of variables (employed to store input data), latent variables (allow to bridge abstract class to data), and factors (defining prior probabilities for spectral features and abstract classes; input data mapping to spectral features mixture and further bridging of the mixture to an abstract class). Latent variables play an important role by defining two-level mapping of the input spectral features to a class. Configuration (learning) on training data of the model allows calculating a parameter set for the model to bridge the input data to a class. The classification algorithm is as follows. Spectral bands are separately pre-processed (unsupervised clustering is used) to be defined on a finite domain (alphabet) leading to a representation of the data on multinomial distribution. The represented hyperspectral data is used as input evidence (evidence vector is selected pixelwise) in a configured factor graph and an inference is run resulting in the posterior probability. Variational inference (Mean field) allows to obtain plausible results with a low calculation time. Calculating the posterior probability for each class and comparison of the probabilities leads to classification. Since the factor graphs operate on input data represented on an alphabet (the represented data transferred into multinomial distribution) the number of training samples can be relatively low. Classification assessment on Salinas hyperspectral data benchmark allowed to obtain a competitive accuracy of classification. Employment of training data consisting of 20 randomly selected points for a class allowed to obtain the overall classification accuracy equal to 85.32% and Kappa equal to 0.8358. Representation of input data on a finite domain discards the curse of dimensionality problem allowing to use large hyperspectral data with a moderately high number of bands.
DEFINING DENSITIES FOR URBAN RESIDENTIAL TEXTURE, THROUGH LAND USE CLASSIFICATION, FROM LANDSAT TM IMAGERY: CASE STUDY OF SPANISH MEDITERRANEAN COAST
Authors: Colaninno N. , Roca J. , Burns M. , Alhaddad B.
Published: August 2012

Abstract. In the recent epoch, there has been considerable debate about the urban development along the European Mediterranean area, also undertaken by the European Authorities, and in particular regarding the role of spatial planning in order to improve sustainable trends of land use. Great transformations along the Spanish Mediterranean coast have generated considerable changes in the traditional structure of the landscape, far from the typical model of Mediterranean cities, and the rapidity of these modern dynamics has been a significant impact on the spatial patterns, also associated with the expansion of urban connections through the whole territory. The increase of large peri-urban areas, sprawled on the territory, and caused by uncontrolled, uncoordinated and unplanned growth, inevitably has brought the cancellation of clearly identifiable boundaries between the city and the rural areas. Spatial analysis, within quantitative geography and linked to the emerging field of regional science, represents a synthesis of urban and regional economics that is consistent with the complex sciences which dominate the simulation of urban form and functions. Most urban models deal with the city in terms of the location of its economic and demographic activities, but there is also a move to link such models to urban morphologies (Batty 2008). According with these concepts, the investigation, also supported by the use of technologies such as remote sensing and GIS, aims to complement the spatial analysis of regional development dynamics by classifying urban structures and quantifying some of main characteristics based on morphological features.
SUPPORT VECTOR MACHINE CLASSIFICATION OF OBJECT-BASED DATA FOR CROP MAPPING, USING MULTI-TEMPORAL LANDSAT IMAGERY
Authors: Devadas R. , Denham R. J. , Pringle M.
Published: August 2012

Abstract. Crop mapping and time series analysis of agronomic cycles are critical for monitoring land use and land management practices, and analysing the issues of agro-environmental impacts and climate change. Multi-temporal Landsat data can be used to analyse decadal changes in cropping patterns at field level, owing to its medium spatial resolution and historical availability. This study attempts to develop robust remote sensing techniques, applicable across a large geographic extent, for state-wide mapping of cropping history in Queensland, Australia. In this context, traditional pixel-based classification was analysed in comparison with image object-based classification using advanced supervised machine-learning algorithms such as Support Vector Machine (SVM). For the Darling Downs region of southern Queensland we gathered a set of Landsat TM images from the 2010–2011 cropping season. Landsat data, along with the vegetation index images, were subjected to multiresolution segmentation to obtain polygon objects. Object-based methods enabled the analysis of aggregated sets of pixels, and exploited shape-related and textural variation, as well as spectral characteristics. SVM models were chosen after examining three shape-based parameters, twenty-three textural parameters and ten spectral parameters of the objects. We found that the object-based methods were superior to the pixel-based methods for classifying 4 major landuse/land cover classes, considering the complexities of within field spectral heterogeneity and spectral mixing. Comparative analysis clearly revealed that higher overall classification accuracy (95%) was observed in the object-based SVM compared with that of traditional pixel-based classification (89%) using maximum likelihood classifier (MLC). Object-based classification also resulted speckle-free images. Further, object-based SVM models were used to classify different broadacre crop types for summer and winter seasons. The influence of different shape, textural and spectral variables, and their weights on crop-mapping accuracy, was also examined. Temporal change in the spectral characteristics, specifically through vegetation indices derived from multi-temporal Landsat data, was found to be the most critical information that affects the accuracy of classification. However, use of these variables was constrained by the data availability and cloud cover.
LAND COVER CLASSIFICATION OF MULTI-SENSOR IMAGES BY DECISION FUSION USING WEIGHTS OF EVIDENCE MODEL
Authors: Li P. , Song B.
Published: August 2012

Abstract. This paper proposed a novel method of decision fusion based on weights of evidence model (WOE). The probability rules from classification results from each separate dataset were fused using WOE to produce the posterior probability for each class. The final classification was obtained by maximum probability. The proposed method was evaluated in land cover classification using two examples. The results showed that the proposed method effectively combined multisensor data in land cover classification and obtained higher classification accuracy than the use of single source data. The weights of evidence model provides an effective decision fusion method for improved land cover classification using multi-sensor data.
ACCURACY EVALUATION OF TWO GLOBAL LAND COVER DATA SETS OVER WETLANDS OF CHINA
Authors: Niu Z. G. , Shan Y. X. , Gong P.
Published: August 2012

Abstract. Although wetlands are well known as one of the most important ecosystems in the world, there are still few global wetland mapping efforts at present. To evaluate the wetland-related types of data accurately for both the Global Land Cover 2000 (GLC2000) data set and MODIS land cover data set (MOD12Q1), we used the China wetland map of 2000, which was interpreted manually based on Landsat TM images, to examine the precision of these global land cover data sets from two aspects (class area accuracy, and spatial agreement) across China. The results show that the area consistency coefficients of wetland-related types between the two global data sets and the reference data are 77.27% and 56.85%, respectively. However, the overall accuracy of relevant wetland types from GLC2000 is only 19.81% based on results of confusion matrix of spatial consistency, and similarly, MOD12Q1 is merely 18.91%. Furthermore, the accuracy of the peatlands is much lower than that of the water bodies according to the results of per-pixel comparison. The categories where errors occurred frequently mainly include grasslands, croplands, bare lands and part of woodland (deciduous coniferous forest, deciduous broadleaf forest and open shrubland). The possible reasons for the low precision of wetland-related land cover types include (1)the different aims of various products and therefore the inconsistent wetland definitions in their systems; (2) the coarse spatial resolution of satellite images used in global data; (3) Discrepancies in dates when images were acquired between the global data set and the reference data. Overall, the unsatisfactory results highlight that more attention should be paid to the application of these two global data products, especially in wetland-relevant types across China.
MULTI-TEMPORAL SAR CHANGE DETECTION AND MONITORING
Authors: Hachicha S. , Chaabane F.
Published: August 2012

Abstract. Multitemporal SAR images are a very useful source of information for a large amount of applications, especially for change detection and monitoring. In this paper, a new SAR change detection and monitoring approach is proposed through the analysis of a time series of SAR images covering the same region. The first step of the method is the SAR filtering preprocessing step using an extension of the spatial NL-means filter to the temporal domain. Then, the Rayleigh Kullback Leibler and the Rayleigh Distribution Ratio measures are combined to detect the changes between a reference image and each SAR image of the time series at both local and global scale. These measures are combined using the Dezert-Smarandache theory which takes into account conflicts between sources and thus enhances the dual change detection results. Finally, a pixel based temporal classification is applied starting from the obtained change maps in order to describe the temporal behaviour of the covered regions.
3D BUILDING CHANGE DETECTION USING HIGH RESOLUTION STEREO IMAGES AND A GIS DATABASE
Authors: Dini G. R. , Jacobsen K. , Rottensteiner F. , Al Rajhi M. , Heipke C.
Published: August 2012

Abstract. In this paper, a workflow is proposed to detect 3D building changes in urban and sub-urban areas using high-resolution stereoscopic satellite images of different epochs and a GIS database. Semi-global matching (SGM) is used to derive Digital Surface Models (DSM) and subsequently normalised digital surface models (nDSM, the difference of a DSM and a digital elevation model (DEM)), from the stereo pairs at each epoch. Large differences between the two DSMs are assumed to represent height changes. In order to reduce the effect of matching errors, heights in the nDSM of at least one epoch must also lie above a certain threshold in order to be considered as candidates for building change. A GIS database is used to check the existence of buildings at epoch 1. As a result of geometric discrepancies during data acquisition caused by different view directions and illumination conditions, the outlines of existing buildings do not necessarily match even in non-changed areas. Consequently, in the change map, there are streaking-shaped structures along the building outlines which do not correspond to actual changes. To eliminate these effects morphologic filtering is applied. The mask we use operates as a threshold on the shape and size of detected new blobs and effectively removes small objects such as cars, small trees and salt and pepper noise. The results of the proposed algorithm using IKONOS and GeoEye images demonstrate its performance for detecting 3D building changes and to extract building boundaries.
IDENTIFYING BUILDING CHANGE USING HIGH RESOLUTION POINT CLOUDS – AN OBJECT-BASED APPROACH
Authors: du Plessis S.
Published: August 2012

Abstract. High resolution point clouds provide excellent data sources for examining change over time in above-ground features such as buildings and trees. Of particular interest is the identification of illegal construction activity or damage incurred during earthquakes and other disasters. By using multi-date point cloud layers, these types of change can be efficiently identified and mapped. Such analysis is generally not as simple as differencing imagery from the two dates. Variations between the images can be caused by slight geometric mismatches between images from different acquisition dates, errors in the data returns, or natural differences caused by vegetation growth or wind direction. The factors can contribute to the detection of large amounts of inconsequential change throughout the area of interest, resulting in too many false positives for the analysis to be of any practical use. However, by conducting object-based analysis of the data – analysing meaningful objects rather than working point by point – software algorithms can be used to rapidly and accurately detect and map only the changes of interest to the customer.
CEST ANALYSIS: AUTOMATED CHANGE DETECTION FROM VERY-HIGH-RESOLUTION REMOTE SENSING IMAGES
Authors: Ehlers M. , Klonus S. , Jarmer T. , Sofina N. , Michel U. , Reinartz P. , Sirmacek B.
Published: August 2012

Abstract. A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye) new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST) analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT) and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment) with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST) of the change algorithms is applied to calculate the probability of change for a particular location. CEST was tested with high-resolution satellite images of the crisis areas of Darfur (Sudan). CEST results are compared with a number of standard algorithms for automated change detection such as image difference, image ratioe, principal component analysis, delta cue technique and post classification change detection. The new combined method shows superior results averaging between 45% and 15% improvement in accuracy.
AUTOMATIC MOVING VEHICLE'S INFORMATION EXTRACTION FROM ONE-PASS WORLDVIEW-2 SATELLITE IMAGERY
Authors: Mishra R. K.
Published: August 2012

Abstract. There are several applications of vehicle information (position, speed, and direction). WorldView-2 satellite has three sensors: one Pan and two MS (MS-1: BGRN1, Pan, and MS-2:CYREN2). Because of a slight time gap in acquiring images from these sensors, the WorldView-2 images capture three different positions of the moving vehicles. This paper proposes a new technique to extract the vehicle information automatically by utilizing the small time gap in WorldView-2 sensors. A PCA-based technique has been developed to automatically detect moving vehicles from MS-1 and MS-2 images. The detected vehicles are used to limit the search space of the adaptive boosting (AdaBoost) algorithm in accurately determining the positions of vehicles in the images. Then, RPC sensor model of WorldView-2 has been used to determine vehicles' ground positions from their image positions to calculate speed and direction. The technique has been tested on a Worldview-2 image. A vehicle detection rate of over 95% has been achieved. The results of vehicles' speed calculations are reliable. This technique makes it feasible to use satellite images for traffic applications on an operational basis.
URBAN DETECTION, DELIMITATION AND MORPHOLOGY: COMPARATIVE ANALYSIS OF SELECTIVE "MEGACITIES"
Authors: Alhaddad B. , Arellano B. E. , Roca J.
Published: August 2012

Abstract. Over the last 50 years, the world has faced an impressive growth of urban population. The walled city, close to the outside, an "island"for economic activities and population density within the rural land, has led to the spread of urban life and urban networks in almost all the territory. There was, as said Margalef (1999), "a topological inversion of the landscape". The "urban" has gone from being an island in the ocean of rural land vastness, to represent the totally of the space in which are inserted natural and rural "systems". New phenomena such as the fall of the fordist model of production, the spread of urbanization known as urban sprawl, and the change of scale of the metropolis, covering increasingly large regions, called "megalopolis" (Gottmann, 1961), have characterized the century. However there are no rigorous databases capable of measuring and evaluating the phenomenon of megacities and in general the process of urbanization in the contemporary world. The aim of this paper is to detect, identify and analyze the morphology of the megacities through remote sensing instruments as well as various indicators of landscape. To understand the structure of these heterogeneous landscapes called megacities, land consumption and spatial complexity needs to be quantified accurately. Remote sensing might be helpful in evaluating how the different land covers shape urban megaregions. The morphological landscape analysis allows establishing the analogies and the differences between patterns of cities and studying the symmetry, growth direction, linearity, complexity and compactness of the urban form. The main objective of this paper is to develop a new methodology to detect urbanized land of some megacities around the world (Tokyo, Mexico, Chicago, New York, London, Moscow, Sao Paulo and Shanghai) using Landsat 7 images.
PANSHARPENING OF HYPERSPECTRAL IMAGES IN URBAN AREAS
Authors: Chisense C. , Engels J. , Hahn M. , Gülch E.
Published: August 2012

Abstract. Pansharpening has proven to be a valuable method for resolution enhancement of multi-band images when spatially high-resolving panchromatic images are available in addition. In principle, pansharpening can beneficially be applied to hyperspectral images as well. But whereas the grey values of multi-spectral images comprise at most relative information about the registered intensities, calibrated hyperspectral images are supposed to provide absolute reflectivity values of the respective material surfaces. This physical significance of the hyperspectral data should be preserved within the pansharpening process as much as possible. In this paper we compare several common pansharpening methods such as Principal Component Fusion, Wavelet Fusion, Gram-Schmidt transform and investigate their applicability for hyperspectral data. Our focus is on the impact of the pansharpening on material classifications. Apart from applying common quality measures, we compare the results of material classifications from hyperspectral data, which were pansharpened by different methods. In addition we propose an alternative pansharpening method which is based on an initial segmentation of the panchromatic image with an additional use of map vector data.
A TRANSFORMATION METHOD FOR TEXTURE FEATURE DESCRIPTION UNDER DIFFERENT IMAGINE CONDITIONS
Authors: Guan Z. , Yu J. , Feng T. , Li A.
Published: August 2012

Abstract. For high spatial resolution Remote Sensing images, it is very important to investigate the transformational methods between background and target characteristics. Only in this way rich details in images under different imaging conditions can be well extracted. Amongst the characteristics of imagery targets, texture is a visual feature that reflects the homogeneity of images and the inner attributes of different objects. What's more, it includes important information which describes the structural arrangement of objects and the connection with the surrounding environment. This paper regards texture as the major feature and investigates the transformational methods of texture feature description under different imaging conditions. This paper mainly consists of three parts:(1) Construct a wavelet filter based on Gabor wavelet, which describes texture features obtained under different imaging conditions;(2) Process and analyze the different object's texture features jointly by the relationship which is built by the wavelet description;(3) Build the transformation between the wavelet descriptions of the different object's texture features based on the characteristics of the band and direction.