bluuebunny/crossref_metadata_2025 huggingface dataset:
GENERATION OF HIGH RESOLUTION AND HIGH PRECISION ORTHORECTIFIED ROAD IMAGERY FROM MOBILE MAPPING SYSTEM
Authors: Sakamoto M. , Tachibana K. , Shimamura H.
Published: August 2012

Abstract. In this paper, a novel technique to generate a high resolution and high precision Orthorectified Road Imagery (ORI) by using spatial information acquired from a Mobile Mapping System (MMS) is introduced. The MMS was equipped with multiple sensors such as GPS, IMU, odometer, 2-6 digital cameras and 2-4 laser scanners. In this study, a Triangulated Irregular Network (TIN) based approach, similar to general aerial photogrammetry, was adopted to build a terrain model in order to generate ORI with high resolution and high geometric precision. Compared to aerial photogrammetry, there are several issues that are needed to be addressed. ORI is generated by merging multiple time sequence images of a short section. Hence, the influence of occlusion due to stationary objects, such as telephone poles, trees, footbridges, or moving objects, such as vehicles, pedestrians are very significant. Moreover, influences of light falloff at the edges of cameras, tone adjustment among images captured from different cameras or a round trip data acquisition of the same path, and time lag between image exposure and laser point acquisition also need to be addressed properly. The proposed method was applied to generate ORI with 1 cm resolution, from the actual MMS data sets. The ORI generated by the proposed technique was more clear, occlusion free and with higher resolution compared to the conventional orthorectified coloured point cloud imagery. Moreover, the visual interpretation of road features from the ORI was much easier. In addition, the experimental results also validated the effectiveness of proposed radiometric corrections. In occluded regions, the ORI was compensated by using other images captured from different angles. The validity of the image masking process, in the occluded regions, was also ascertained.
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.
EFFICIENT EXTRACTION METHOD OF THE CHANGE OF BUILDINGS FOR FIXED PROPERTY INVESTIGATION
Authors: Tanauchi Y. , Chikatsu H.
Published: August 2012

Abstract. In order to appraise fixed property, local governments in Japan annually investigate taxable buildings on January 1, but the efficiency of the investigation is an issue. With this context, change extraction methods of buildings have been studied using various data. However, labor and time optimization for change extraction methods remains an issue. With this in mind, the authors have concentrated on developing a change extraction method for buildings that uses only photomaps of two separate times. This paper describes the extraction method using color and texture, which can be obtained from photomaps. In order to evaluate effectiveness, the proposed method was investigated using photomaps of two separate times on various locations. It was confirmed that the proposed method extracted the changed buildings. It was also verified that the change of buildings cannot be extracted by color information only; rather, the change extraction of buildings was accomplished by using both color and texture. It should be noted that all changed buildings include extracted regions so that the change extraction of buildings is effectively performed without oversights. The proposed method could extract all changed buildings. In conclusion, the proposed method can reduce over-extraction of changed buildings by intensively visually checking extracted regions that have changes in color or texture rather than by visually checking all regions of photomaps. It is concluded that the proposed method has the ability to effectively extract changed buildings by using only photomaps.
RECONSTRUCTING THREE-DIMENSIONAL SPECIFIC CURVE BUILDING MODELS FROM A SINGLE PERSPECTIVE VIEW IMAGE
Authors: Chang H. , Tsai F.
Published: August 2012

Abstract. This paper presents a systematic approach to reconstruct 3D models of complex buildings with specific curve structures from single perspective view images. The proposed method begins with the automatic extraction of straight feature lines and corner points. Three mutually orthogonal vanishing points are then calculated automatically and robustly for reconstructing three-dimensional regular (planar structure) models. For curved segments, they are extracted and processed separately. Three types of curved segments are considered in this study, including cylinder shapes, surfaces of revolution and free-form curve models. Cylinder shape structures can be defined directly by calculated length of major and minor axes. As for surfaces of revolution, the model can be reconstructed using a fitted curve contour line and determined symmetry axis. Free-form curve structures are reconstructed using measured boundary curves for the interpolation of curve surfaces. Regular and curved models are then merged based on their shared feature points. Finally, the level of detail of reconstructed models can be increased using rectified façade texture rendered from single-view images. The output imagery of a computer-simulated model and close-range photographs of real buildings are used in this study to test the performance of the developed algorithms. Quantitative evaluations of the results compared with ground-based surveying and visualized comparison with raw images indicate that the developed algorithms can successfully extract 3D information and reconstruct 3D specific curve building models.
HIERARCHICAL MATCHING OF UNCERTAIN BUILDING MODELS WITH OBLIQUE VIEW AIRBORNE IR IMAGE SEQUENCES
Authors: Iwaszczuk D. , Hoegner L. , Schmitt M. , Stilla U.
Published: August 2012

Abstract. Thermal building textures can be used for detection of damaged and weak spots in the building structure. These textures can be extracted from airborne infrared (IR) image sequences by projecting the 3D building model into the images. However, the direct georeferencing is often not sufficiently accurate and the projected 3D model does not match the structures in the image. Thus we present a technique with the main goal to find the best fit between the existing 3D building model and the IR image sequence. For this purpose we developed a hierarchical approach consisting of two working stages. In the first stage we correct exterior orientation via line based matching. In the adjustment we consider both uncertainties: the ones of the model and the ones of the image. In the second stage we match each edge separately in its closest surrounding. Thanks to this approach a better fit between the 3D building model and the IR image was found. The originally unmodeled roof overlap was reconstructed.
A PRELIMINARY STUDY OF WEB-BASED SPATIAL DATA ANALYSIS FEASIBILITY – ONE OF POSSIBLE SOLUTIONS FOR DISASTER RESPONSE AND MANAGEMENT
Authors: Lim C. C. , Chang K.-C.
Published: August 2012

Abstract. As the massive tsunami that struck northeast Japan in 11 March 2011 after a magnitude 9.0 earthquake, it reveals that people are living in a critical environment. Although great improvement has been achieved in disaster prevention technologies, many natural disasters are still unpredictable. In addition to the prevention, rapid and effective responses to such disasters are also crucial. One of the key elements to success is the information dissemination of disaster, including both area and people living within that region. In the past decade, web-based spatial information system has become the major platform for both data sharing and displaying. What is coming next is the development of web-based spatial data analysis. A web-based service allows people to implement spatial analysis immediately as long as the internet connection among database and application servers is available. This useful and helpful spatial information is able to be accessed by all users around the world almost simultaneously. The main goal of this paper is to implement a spatial data analysis module based on service oriented architecture (SOA) concept. The main interest and focus of our study is based on the knowledge regularization processes of spatial data analysis to achieve the automated land cover change detection (LCCD) over internet. The proposed automated model is tested and verified by FORMOSAT-2 imageries taken in 2005 and in 2008. It will be published online for users around the world to maximize the add-on value and minimize the cost of the spatial data, moreover, to reveal the situations of disaster rapidly.
PERFORMING IMPROVED TWO-STEP CAMERA CALIBRATION WITH WEIGHTED TOTAL LEAST-SQUARES
Authors: Lu J.
Published: August 2012

Abstract. In order to improve the Tsai's two-step camera calibration method, we present a camera model which accounts for major sources of lens distortion, namely: radial, decentering, and thin prism distortions. The coordinates of principle points will be calculated at the same time. In the camera calibration model, considering the errors existing both in the observation vector and the coefficient matrix, the Total Least-Squares (TLS) solution is preferred to be utilized. The Errors-In-Variables (EIV) model will be adjusted by the solution within the nonlinear Gauss-Helmert (GH) model here. At the end of the contribution, the real experiment is investigated to demonstrate the improved two-step camera calibration method proposed in this paper. The results show that using the iteratively linearized GH model to solve this proposed method, the camera calibration parameters will be more stable and accurate, and the calculation can be preceded regardless of whether the variance covariance matrices are full or diagonal.
ACTIVITIES OF THE STUDENT FORUM OF THE GEOINFORMATION FORUM JAPAN
Authors: Oba A. , Miyazaki H.
Published: August 2012

Abstract. This reports a history and future prospects of the activities by the Student Forum of the Geoinformation Forum Japan. For growths of academic fields, active communications among students and young scientists are indispensable. Several academic communities in geoinformation fields are established by youths and play important roles of building networks over schools and institutes. The networks are expected to be innovative cooperation after the youths achieve their professions. Although academic communities are getting fixed growth particularly in Japan, youths had gotten little opportunities to make contacts with youths themselves. To promote gotten youth activities among geoinformation fields, in 1998, we started a series of programs that named the Student Forum of the Geoinformation Forum Japan involving students and young scientists within the annual conferences, Geoinformation Forum Japan. The programs have provided opportunities to do presentation their studies by posters, some events, and motivations to create networks among students and young scientists. From 2009, some members of our activities set additional conference in west area of Japan. Thus our activities are spread within Japan. As a result of these achievements, the number of youth dedicating to the programs keeps growing. From 2009, it's getting international gradually, however, almost all the participants are still Japanese. To keep and expand the network, we are planning to make some nodes with some Asian youth organizations in the field of geoinformation. This paper is concluded with proposals and future prospects on the Student Forum of the Geoinformation Forum Japan.
TRANSFER OF TECHNOLOGY FOR CADASTRAL MAPPING IN TAJIKISTAN USING HIGH RESOLUTION SATELLITE DATA
Authors: Kaczynski R.
Published: August 2012

Abstract. European Commission funded project entitled: "Support to the mapping and certification capacity of the Agency of Land Management, Geodesy and Cartography" in Tajikistan was run by FINNMAP FM-International and Human Dynamics from Nov. 2006 to June 2011. The Agency of Land Management, Geodesy and Cartography is the state agency responsible for development, implementation, monitoring and evaluation of state policies on land tenure and land management, including the on-going land reform and registration of land use rights. The specific objective was to support and strengthen the professional capacity of the "Fazo" Institute in the field of satellite geodesy, digital photogrammetry, advanced digital satellite image processing of high resolution satellite data and digital cartography. Lectures and on-the-job trainings for the personnel of "Fazo" and Agency in satellite geodesy, digital photogrammetry, cartography and the use of high resolution satellite data for cadastral mapping have been organized. Standards and Quality control system for all data and products have been elaborated and implemented in the production line. Technical expertise and trainings in geodesy, photogrammetry and satellite image processing to the World Bank project "Land Registration and Cadastre System for Sustainable Agriculture" has also been completed in Tajikistan. The new map projection was chosen and the new unclassified geodetic network has been established for all of the country in which all agricultural parcel boundaries are being mapped. IKONOS, QuickBird and WorldView1 panchromatic data have been used for orthophoto generation. Average accuracy of space triangulation of non-standard (long up to 90km) satellite images of QuickBird Pan and IKONOS Pan on ICPs: RMSEx = 0.5m and RMSEy = 0.5m have been achieved. Accuracy of digital orthophoto map is RMSExy = 1.0m. More then two and half thousands of digital orthophoto map sheets in the scale of 1:5000 with pixel size 0.5m have been produced so far by the “Fazo” Institute in Tajikistan on the basis of technology elaborated in the framework of this project. Digital cadastral maps are produced in "Fazo" and Cadastral Regional Centers in Tajikistan using ArcMap software. These digital orthophotomaps will also be used for digital mapping of water resources and other needs of the country.
COMPARISOM OF WAVELET-BASED AND HHT-BASED FEATURE EXTRACTION METHODS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Authors: Huang X.-M. , Hsu P.-H.
Published: August 2012

Abstract. Hyperspectral images, which contain rich and fine spectral information, can be used to identify surface objects and improve land use/cover classification accuracy. Due to the property of high dimensionality of hyperspectral data, traditional statistics-based classifiers cannot be directly used on such images with limited training samples. This problem is referred as "curse of dimensionality". The commonly used method to solve this problem is dimensionality reduction, and feature extraction is used to reduce the dimensionality of hyperspectral images more frequently. There are two types of feature extraction methods. The first type is based on statistical property of data. The other type is based on time-frequency analysis. In this study, the time-frequency analysis methods are used to extract the features for hyperspectral image classification. Firstly, it has been proven that wavelet-based feature extraction provide an effective tool for spectral feature extraction. On the other hand, Hilbert-Huang transform (HHT), a relative new time-frequency analysis tool, has been widely used in nonlinear and nonstationary data analysis. In this study, wavelet transform and HHT are implemented on the hyperspectral data for physical spectral analysis. Therefore, we can get a small number of salient features, reduce the dimensionality of hyperspectral images and keep the accuracy of classification results. An AVIRIS data set is used to test the performance of the proposed HHT-based feature extraction methods; then, the results are compared with wavelet-based feature extraction. According to the experiment results, HHT-based feature extraction methods are effective tools and the results are similar with wavelet-based feature extraction methods.
EXTRACTING TEMPORAL AND SPATIAL DISTRIBUTIONS INFORMATION ABOUT ALGAL GLOOMS BASED ON MULTITEMPORAL MODIS
Authors: Chunguang L. , Qingjiu T.
Published: August 2012

Abstract. Based on MODIS remote sensing data, method and technology to extraction the time and space distribution information of algae bloom is studied and established. The dynamic feature of time and space in Taihu Lake from 2009 to 2011 can be obtained by extracted method. Variation of cyanobacterial bloom in the Taihu Lake is analyzed and discussed. The algae bloom frequency index (AFI) and algae bloom sustainability index (ASI) is important criterion which can show the interannual and inter-monthly variation in the whole area or the subregion of Taihu Lake. Utilizing the AFI and ASI from 2009 to 2011, it found some phenomena that: the booming frequency decreased from the north and west to the East and South of Taihu Lake. The annual month algae bloom variation of AFI reflect the booming existing twin peaks in the high shock level and lag trend in general. In the subregion statistics, the IBD and ASI in 2011 show the abnormal condition in the border between the Gongshan Bay and Central Lake. The date is obvious earlier than that on the same subregion in previous years and that on others subregion in the same year.
ASSESSING THE SIGNIFICANCE OF HYPERION SPECTRAL BANDS IN FOREST CLASSIFICATION
Authors: Newnham G. J. , Lazaridis D. , Sims N. C. , Robinson A. P. , Culvenor D. S.
Published: August 2012

Abstract. The classification of vegetation in hyperspectral image scenes presents some challenges due to high band autocorrelations and problems dealing with many predictor variables. The Random Forests classification method is based on an ensemble of decision trees and attempts to address these issues by dealing with only a subset of image bands in each node of each decision tree. Random Forests has previously been used for classification of vegetation using hyperspectral data. However, the variable importance measure that is a by-product of the technique has largely been ignored. In this study we investigate the spectral qualities of variable importance in the classification of forest and non-forest in a single Hyperion scene. The spectral importance curve showed broad bands of importance over wavelength regions known to be significant in biochemical absorption.
STUDY ON OIL-GAS RESERVOIR DETECTING METHODS USING HYPERSPECTRAL REMOTE SENSING
Authors: Tian Q.
Published: August 2012

Abstract. Oil-gas reservoir exploration using hyperspectral remote sensing, which based on the theory of hydrocarbon microseepage information and fine spectral response of target, is a new direction for the application of remote sensing technology. In this paper, Qaidam Basin and Liaodong Bay in China were selected as the study areas. Based on the hydrocarbon microseepage theory, the analysis of crude oil in soil in Qaidam Basin and spectral experiment of crude oil in sea water in Liaodong Bay, Hyperion hyperspectral remote sensing images were used to develop the method of oil-gas exploration. The results indicated that the area of oil-gas reservoir in Qaidam Basin could be delimited in two ways: the oil-gas reservoir can be obtained directly by the absorption bands near 1730nm in Hyperion image; and Linear Spectral Unmixing (LSU) and Spectral Angle Matching (SAM) of alteration mineral (e.g. kaolinite, illite) could be used to indirectly detect the target area in Qaidam Basin. In addition, combined with the optimal bands in the region of visible/near-infrared, SAM was used to extract the thin oil slick of microseepage in Liaodong Bay. Then the target area of oil-gas reservoir in Liaodong Bay can be delineated.
CLASSIFICATION OF ACTIVE MICROWAVE AND PASSIVE OPTICAL DATA BASED ON BAYESIAN THEORY AND MRF
Authors: Yu F. , Li H. T. , Han Y. S. , Gu H. Y.
Published: August 2012

Abstract. A classifier based on Bayesian theory and Markov random field (MRF) is presented to classify the active microwave and passive optical remote sensing data, which have demonstrated their respective advantages in inversion of surface soil moisture content. In the method, the VV, VH polarization of ASAR and all the 7 TM bands are taken as the input of the classifier to get the class labels of each pixel of the images. And the model is validated for the necessities of integration of TM and ASAR, it shows that, the total precision of classification in this paper is 89.4%. Comparing with the classification with single TM, the accuracy increase 11.5%, illustrating that synthesis of active and passive optical remote sensing data is efficient and potential in classification.
DETERMINATION OF MAGNITUDE AND DIRECTION OF LAND USE/ LAND COVER CHANGES IN TERKOS WATER BASIN, ISTANBUL
Authors: Bektas Balcik F. , Goksel C.
Published: August 2012

Abstract. Remotely sensed data have huge importance to determine land use/cover changes for sustainable region planning and management. Variety of techniques in order to detect land cover dynamics using remote sensing imagery have been developed, tested and assessed with the results varying according to the change scenario, the information required and the imagery applied. In this study, the modified Change Vector Analysis (mCVA) technique was implemented on SPOT 4 and SPOT 5 multispectral (MS) data to monitor the dynamics of land use/land cover (LULC) change in Terkos Water Basin, İstanbul. mCVA was applied to multi-temporal data to compare the differences in the time-trajectory of the Tasseled Cap (TC) brightness, greenness and wetness for two successive time periods – 2003 and 2007. Gram Schmidt Orthogonalization Technique was used to derive the related TC coefficients for SPOT data. The efficiency of the technique was assessed based on error matrix. The overall accuracy and Kappa statistic was 84.32 % and 0.81, respectively. The results indicated that it is possible to produce accurate change detection maps with the help of mCVA and SPOT 4 &SPOT 5 satellite data.
AN INVESTIGATION OF AUTOMATIC CHANGE DETECTION FOR TOPOGRAPHIC MAP UPDATING
Authors: Duncan P. , Smit J.
Published: August 2012

Abstract. Changes to the landscape are constantly occurring and it is essential for geospatial and mapping organisations that these changes are regularly detected and captured, so that map databases can be updated to reflect the current status of the landscape. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa's national mapping agency, currently relies on manual methods of detecting changes and capturing these changes. These manual methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The aim of this research is to do an investigation into a methodology for automatic or semi-automatic change detection for the purpose of updating topographic databases. The method investigated for detecting changes is through image classification as well as spatial analysis and is focussed on urban landscapes. The major data input into this study is high resolution aerial imagery and existing topographic vector data. Initial results indicate the traditional pixel-based image classification approaches are unsatisfactory for large scale land-use mapping and that object-orientated approaches hold more promise. Even in the instance of object-oriented image classification generalization of techniques on a broad-scale has provided inconsistent results. A solution may lie with a hybrid approach of pixel and object-oriented techniques.
EVALUATING THE CONSISTENCY OF REMOTE SENSING BASED SNOW DEPTH PRODUCTS IN ARID ZONE OF WESTERN CHINA
Authors: Zhou Q. , Sun B.
Published: August 2012

Abstract. Snow cover is a sensitive indicator of global climate change. Among various snow cover parameters, snow depth which can indicate snow accumulation is essential for retrieving snow water equivalent. In arid zone of western China, based on different inversion models, snow depth products retrieved from passive microwave remote sensing sensors have been issued. However, none of them can promise a high accuracy due to the spatial heterogeneity of snow cover especially in mountain areas with complex terrain. This study aims to analyse the reliability of existing long-term snow depth products in arid zone of western China. Two datasets are compared including GlobSnow snow water equivalent (SWE) product and snow depth dataset provided by Environmental and Ecological Science Data Center for West China. Statistical techniques like regression and intra-class correlation coefficient (ICC) models are employed to examine the consistency of these two remote sensing based snow depth products in a selected sampling site. More than 260 samples during three years are tested covering from snow falling to snow melting periods. Result shows that there is a discrepancy between the two datasets. Accordingly, remote sensing based snow depth measurement is not reliable in mountain areas in arid zone of western China. This study gives an awareness of the stabilities of current snow depth detection models. A further study is expected to calibrate snow depth products based on in-situ observation and measurements from ground monitoring stations.
SYNTHETIC APERTURE RADAR (SAR) AND OPTICAL IMAGERY DATA FUSION: CROP YIELD ANALYSIS IN SOUTHEAST ASIA
Authors: Parks S. M.
Published: August 2012

Abstract. With the expanding energy crisis and rising food prices, crop yield analysis in Southeast Asia is an increasingly important topic in this region. Rice is the most important food crop in Southeast Asia and the ability to accurately predict crop yields during a growing season is useful for decision-makers, aid providers, and commercial trade organizations. The use of optical satellite image data by itself is difficult due to the almost constant cloud in many parts of Southeast Asia. However, Synthetic Aperture Radar (SAR), or SAR data, which can image the Earth's surface through cloud cover, is suitable for many agricultural purposes, such as the detection of rice fields, and the identification of different crop species. Crop yield analysis is difficult in this region due to many factors. Rice cropping systems are often characterized by the type of rice planted, the size of rice field, the sowing dates for different fields, different types of rice cropping systems from one area to another, as well as cultural practices such as sowing and transplanting. This paper will discuss the use of SAR data fused with optical imagery to improve the ability to perform crop yield analysis on rice crops in Southeast Asia.
FUSION OF OPTICAL DATA AND SAR DATA FOR THE ESTIMATION OF NITROGEN CONCENTRATION IN PEARL RIVER ESTUARY HONG KONG SEAS, CHINA
Authors: Liu X. , Liu M. , Wu L.
Published: August 2012

Abstract. The knowledge of nitrogen concentration in the ocean is fundamental for the study of oceanic biogeochemical processes. The objective of this research is to estimate total inorganic nitrogen (TIN) by integrating optical parameters from HJ-1 CCD image and polarization parameters from RADARSAT-2 quad-polarization image. The situ data and HJ-1 CCD, RADARSAT-2 image were acquired from Pearl River Estuary Hong Kong Seas, China in August, 2010. The four sensitive parameters, reflectance of Band 4, NDSI (Normalized Difference Spectral Index), the backscattering coefficient of HV and VH were derived as input variables to assess the TIN. A multiple regression model was established between four input variables and TIN. The result showed that the fusion of optical data and SAR data was proved to be successful in estimating TIN in sea surface, with the correlation coefficient (R2) between measured TIN and predicated TIN of 0.774, and the root mean square error (RMSE) of 0.063. The optical data in combination with SAR data is promising for detecting biochemical component in sea surface.
AN ACCURACY ASSESSMENT OF GEOREFERENCED POINT CLOUDS PRODUCED VIA MULTI-VIEW STEREO TECHNIQUES APPLIED TO IMAGERY ACQUIRED VIA UNMANNED AERIAL VEHICLE
Authors: Harwin S. , Lucieer A.
Published: August 2012

Abstract. Low-cost Unmanned Aerial Vehicles (UAVs) are becoming viable environmental remote sensing tools. Sensor and battery technology is expanding the data capture opportunities. The UAV, as a close range remote sensing platform, can capture high resolution photography on-demand. This imagery can be used to produce dense point clouds using multi-view stereopsis techniques (MVS) combining computer vision and photogrammetry. This study examines point clouds produced using MVS techniques applied to UAV and terrestrial photography. A multi-rotor micro UAV acquired aerial imagery from a altitude of approximately 30–40 m. The point clouds produced are extremely dense (<1–3 cm point spacing) and provide a detailed record of the surface in the study area, a 70 m section of sheltered coastline in southeast Tasmania. Areas with little surface texture were not well captured, similarly, areas with complex geometry such as grass tussocks and woody scrub were not well mapped. The process fails to penetrate vegetation, but extracts very detailed terrain in unvegetated areas. Initially the point clouds are in an arbitrary coordinate system and need to be georeferenced. A Helmert transformation is applied based on matching ground control points (GCPs) identified in the point clouds to GCPs surveying with differential GPS. These point clouds can be used, alongside laser scanning and more traditional techniques, to provide very detailed and precise representations of a range of landscapes at key moments. There are many potential applications for the UAV-MVS technique, including coastal erosion and accretion monitoring, mine surveying and other environmental monitoring applications. For the generated point clouds to be used in spatial applications they need to be converted to surface models that reduce dataset size without loosing too much detail. Triangulated meshes are one option, another is Poisson Surface Reconstruction. This latter option makes use of point normal data and produces a surface representation at greater detail than previously obtainable. This study will visualise and compare the two surface representations by comparing clouds created from terrestrial MVS (T-MVS) and UAV-MVS.
LIDAR WAVEFORM SIMULATION OVER COMPLEX TARGETS
Authors: Kim S. , Lee I. , Lee M.
Published: August 2012

Abstract. Unlike discrete-return LIDAR system that measures the return times of some echoes, waveform LIDAR provides the full-waveform data by digitising multi-echoes. From the waveform data we can extract more information about the geometry and reflectance of the target surfaces by applying various algorithms to interpret waveform. There have been many researches about the laser beam's interaction with the illuminated surfaces and the diverse algorithms for waveform processing. The purpose of this paper is to suggest the method to simulate waveform coming from complex targets. First, we analysed the previous relevant works. And based on these we attempted to generate the simulated waveform over the complex surfaces. For the waveform simulation, we defined the sub-beams spread with a consistent interval within the beam's divergence coverage. Each sub-beam has its geometry (origin and direction) and the transmitted energy considering the laser beam's profile. Then, we searched the surfaces that intersect with sub-beams using ray-tracing algorithm, and computed the intersection points and the received energies. Using on the computed distance, the received energy and predefined pulse model, we generated the signals of echoes and put them together into a waveform. Finally, we completed the waveform simulation adding the signal noise. As a result of performing waveform simulation, we confirmed that the waveform data was successfully simulated by the proposed method. We believe that our method of the waveform simulation will be helpful to understand the waveform data and develop the algorithms for the waveform processing.
WAVEFORM ANALYSIS FOR THE EXTRACTION OF POST-FIRE VEGETATION CHARACTERISTICS
Authors: Pirotti F. , Guarnieri A. , Vettore A.
Published: August 2012

Abstract. Full-waveform is becoming increasingly available in today's LiDAR systems and the analysis of the full return signal can provide additional information on the reflecting surfaces. In this paper we present the results of an assessment on full-waveform analysis, as opposed to the more classic discrete return analysis, for discerning vegetation cover classes related to post-fire renovation. In the spring of 2011 an OPTECH ALTM sensor was used to survey an Alpine area of almost 20 km2 in the north of Italy. A forest fire event several years ago burned large patches of vegetation for a total of about 1.5 km2 . The renovation process in the area is varied because of the different interventions ranging from no intervention to the application of re-forestation techniques to accelerate the process of re-establishing protection forest. The LiDAR data was used to divide the study site into areas with different conditions in terms of re-establishment of the natural vegetation condition. The LiDAR survey provided both the full-waveform data in Optech's CSD+DGT (corrected sensor data) and NDF+IDX (digitizer data with index file) formats, and the discrete return in the LAS format. The method applied to the full-waveform uses canopy volume profiles obtained by modelling, whereas the method applied to discrete return uses point geometry and density indexes. The results of these two methods are assessed by ground truth obtained from sampling and comparison shows that the added information from the full-waveform does give a significant better discrimination of the vegetation cover classes.
EXPLORING WEAK AND OVERLAPPED RETURNS OF A LIDAR WAVEFORM WITH A WAVELET-BASED ECHO DETECTOR
Authors: Wang C. K.
Published: August 2012

Abstract. Full waveform data recording the reflected laser signal from ground objects have been provided by some commercial airborne LIDAR systems in the last few years. Waveform data enable users to explore more information and characteristics of the earth surface than conventional LIDAR point cloud. An important application is to extract extra point clouds from waveform data in addition to the point cloud generated by the online process of echo detection. Some difficult-to-detect points, which may be important to topographic mapping, can be rediscovered from waveform data. The motivation of this study is to explore weak and overlapped returns of a waveform. This paper presents a wavelet-based echo detection algorithm, which is compared with the zero-crossing detection method for evaluation. Some simulated waveforms deteriorated with different noises are made to test the limitations of the detector. The experimental results show that the wavelet-based detector outperformed the zero-crossing detector in both difficult-to-detect cases. The detector is also applied to a real waveform dataset. In addition to the total number of echoes provided by the instrument, the detector found 18% more of echoes. The proposed detector is significant in finding weak and overlapped returns from waveforms.
A NEW PERSISTENT SCATTER NETWORK CONSTRUCTION ALGORITHM FOR PERSISTENT SCATTER INSAR AND ITS APPLICATION TO THE DETECTION OF URBAN SUBSIDENCE
Authors: Luo X. , Huang D. , Liu G. , Zhou L. , Dai K.
Published: August 2012

Abstract. To extremely eliminate atmospheric delays for improving the accuracy of persistent scatter InSAR, the algorithm for constructing three-dimensional Delaunay network of global positioning system (GPS) stations is introduced to construct three-dimensional persistent scatter Delaunay network. The comparison with two-dimensional persistent scatter network indicates that three-dimensional Delaunay network is stable and avoids the affect of landscape conversion from geography space to image space. The urban subsidence of Lujiazui in Shanghai during 1992–2002 was effectively detected with InSAR based on three-dimensional persistent scatter Delaunay network. The result shows that persistent scatter InSAR based on three-dimensional persistent scatter Delaunay network can be used to efficiently and accurately detect ground deformation. The comparison with Leveling and InSAR based on persistent scatter planar network indicates that the accuracy and reliability of InSAR based on three-dimensional persistent scatter Delaunay network are significantly improved.
INSAR OF AQUATIC BODIES
Authors: Tarikhi P.
Published: August 2012

Abstract. Radar remote sensing is a new earth observation technology with promising results and future. InSAR is a sophisticated radar remote sensing technique for combining synthetic aperture radar (SAR) single look complex images to form interferogram and utilizing its phase contribution to land topography, surface movement and target velocity. In recent years considerable applications of Interferometric SAR technique have been developed. It is an established technique for precise assessment of land surface movements, and generating high quality digital elevation models (DEM) from space-borne and airborne data. InSAR is able to produce DEMs with the precision of a couple of ten meters whereas its movement map results have sub-centimeter precision. The technique has many applications in the context of earth sciences such as topographic mapping, environmental modelling, rainfall-runoff studies, landslide hazard zonation, and seismic source modelling. Nevertheless new developments are taking place in the application of InSAR for aquatic bodies. We have observed that using SAR Interferometry technique for aquatic bodies with the maximum temporal baseline of 16 seconds for image pairs shows considerable results enabling us to determine the direction of sea surface motion in a large area, estimate the sea surface fluctuations in the direction of sensor line-of-the-sight, detect wave pattern and the sea surface disturbance and whether the water motion is bulk and smooth or otherwise. This paper presents our experience and achievements on this new topic through discussing the facts and conditions for the use of InSAR technique. The method has been examined for Haiti, Dominican Republic, Western Chile and Western Turkey coast areas and inland lakes however ground truth data is needed for final verification. This technique scheduled to be applied in some other sites for which the proper data is available.
FUSION OF MULTI PRECURSORS EARTHQUAKE PARAMETERS TO ESTIMATE THE DATE, MAGNITUDE AND AFFECTED AREA OF THE FORTHCOMING POWERFUL EARTHQUAKES
Authors: Akhoondzadeh M. , Saradjian M. R.
Published: August 2012

Abstract. Since not any individual precursor can be used as an accurate stand alone means for the earthquake prediction, it is necessary to integrate different kinds of precursors. The precursors selected for analysis in this study include electron and ion density, electron temperature, total electron content (TEC), electric and magnetic fields and land surface temperature (LST) several days before three strong earthquakes which happened in Samoa Islands, Sichuan (China) and Borujerd (Iran). The precursor's variations were monitored using data obtained from experiments onboard DEMETER (IAP, ISL, ICE and IMSC) and Aqua-MODIS satellites. Regarding the ionospheric precursors, the geomagnetic indices Dst and Kp were used to distinguish pre-earthquake disturbed states from the other anomalies related to the geomagnetic activities. The inter-quartile range of data was utilized to construct their upper and lower bound to detect disturbed states outsides the bounds which might be associated with impending earthquakes. When the disturbed state associated with impending earthquake is detected, based on the type of precursor, the number of days relative to earthquake day is estimated. Then regarding the deviation value of the precursor from the undisturbed state the magnitude of impending earthquake is estimated. The radius of the affected area is calculated using the estimated magnitude and Dobrovolsky formula. In order to assess final earthquake parameters (which are date, magnitude and radius of the affected area) for each case study, using the median and inter-quartile range of earthquake parameters obtained from different precursors, the approximate bounds of final earthquake parameters are defined. For each studied case, a good agreement was found between the estimated and registered earthquake parameters.
METHODOLOGY FOR LANDSLIDE MONITORING IN A ROAD CUT BY MEANS OF TERRESTRIAL LASER-SCANNING TECHNIQUES
Authors: Hernández M. A. , Pérez-García J. L. , Fernández T. , Cardenal F. J. , Mata E. , López A. , Delgado J. , Mozas A.
Published: August 2012

Abstract. After the heavy rains of 2009/10 winter, a road cut in the national highway A-44 and the upper slope became unstable; the mass invaded the way and caused important traffic interruptions by several months. The landslide was measured by means of terrestrial laser-scanner techniques and, because of the zone morphology, the used methodology involved scanning the mobilized zone from different stations with several captures from each point. Two scanning campaigns were carried out in a time interval of 14 days. The antenna phase centers were determined by GPS techniques and incorporated to the point clouds as an additional point in the TLS reference system; next, the relative orientation of the different point clouds of each scan station is made, adjusting and merging them in a single point cloud; finally, we proceed to data transformation to a reference system global and common to both campaigns, in which surface and terrain models can be compared. From field data, a digital surface model have been built, and then filtered and edited to have digital elevation models of centimeter spatial resolution. The results obtained by the comparison of models show two rupture zones in the road cut affecting also to the upslope, in which an important volume material flowed with superficial displacements of about 0,55–0,65 m day-1. We also calculated 210 m3 of depleted material and 124,5 m3 of accumulated material; the differences between these volumes (wasting material) are explained because the civil works that were made to clear the road of materials.
LOW-COST, ULTRA-HIGH SPATIAL AND TEMPORAL RESOLUTION MAPPING OF INTERTIDAL ROCK PLATFORMS
Authors: Bryson M. , Johnson-Roberson M. , Murphy R.
Published: August 2012

Abstract. Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time which could compliment field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at relatively course, sub-meter resolutions or with limited temporal resolutions and relatively high costs for small-scale environmental science and ecology studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric pipeline that was developed for constructing highresolution, 3D, photo-realistic terrain models of intertidal rocky shores. The processing pipeline uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine colour and topographic information at sub-centimeter resolutions over an area of approximately 100m, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rock platform at Cape Banks, Sydney, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.
THE ROLE OF REMOTE SENSING FOR SUSTAINABLE ELEPHANT MANAGEMENT IN SOUTH AFRICA. FOUR MEDIUM SIZED GAME RESERVES AS CASE STUDIES
Authors: Jordaan M.
Published: August 2012

Abstract. Loxodonta africana (African Elephant) are running out of living space so the protection of what space they have is essential. Existing areas of suitable elephant habitat need to be protected not only from human development but from the elephants themselves. As most elephant populations in South Africa are enclosed and multiplying, there is some increasing cause for concern as the damage caused will escalate and could reach unsustainable proportions. This study examined the utilization of satellite images for the detection of elephant induced ecosystem modification. A pilot study was conducted on four medium sized Game Reserves (each ±30 000 ha) in South Africa. The aim was to ascertain the feasibility of using image analysis as instrument by which Game Reserve managers could assess biodiversity richness, habitat loss, and population-habitat viability. NDVI as indicator of primary production in vegetation is one of the instruments used to evaluate whether the carrying capacity for elephants of each Game Reserve has been reached and to compare the current biomass with those of previous years. The study also looked at the use of the woody canopy cover as target for change detection analysis. Spectral characteristics of specific trees species which are known for being preferred by elephants were used to conduct a temporal analysis on satellite images starting from the period when the elephants were re-introduced into each Game Reserve, thus attempting to identify possible impact on the biodiversity of the respective Game Reserves. Images from satellites such as Landsat, SPOT, Quickbird and SumbandilaSAT provided the needed data and maps.