bluuebunny/crossref_metadata_2025 huggingface dataset:
DIRECT GEOREFERENCING OF UAV DATA BASED ON SIMPLE BUILDING STRUCTURES
Authors: Tampubolon W. , Reinhardt W.
Published: August 2016

Unmanned Aerial Vehicle (UAV) data acquisition is more flexible compared with the more complex traditional airborne data acquisition. This advantage puts UAV platforms in a position as an alternative acquisition method in many applications including Large Scale Topographical Mapping (LSTM). LSTM, i.e. larger or equal than 1:10.000 map scale, is one of a number of prominent priority tasks to be solved in an accelerated way especially in third world developing countries such as Indonesia.

 As one component of fundamental geospatial data sets, large scale topographical maps are mandatory in order to enable detailed spatial planning. However, the accuracy of the products derived from the UAV data are normally not sufficient for LSTM as it needs robust georeferencing, which requires additional costly efforts such as the incorporation of sophisticated GPS Inertial Navigation System (INS) or Inertial Measurement Unit (IMU) on the platform and/or Ground Control Point (GCP) data on the ground. To reduce the costs and the weight on the UAV alternative solutions have to be found.

 This paper outlines a direct georeferencing method of UAV data by providing image orientation parameters derived from simple building structures and presents results of an investigation on the achievable results in a LSTM application. In this case, the image orientation determination has been performed through sequential images without any input from INS/IMU equipment. The simple building structures play a significant role in such a way that geometrical characteristics have been considered. Some instances are the orthogonality of the building’s wall/rooftop and the local knowledge of the building orientation in the field. In addition, we want to include the Structure from Motion (SfM) approach in order to reduce the number of required GCPs especially for the absolute orientation purpose.

 The SfM technique applied to the UAV data and simple building structures additionally presents an effective tool for the LSTM application at low cost. Our results show that image orientation calculations from building structure essentially improve the accuracy of direct georeferencing procedure adjusted also by the GCPs. To gain three dimensional (3D) point clouds in local coordinate system, an extraction procedure has been performed by using Agisoft Photo Scan. Subsequently, a Digital Surface Model (DSM) generated from the acquired data is the main output for LSTM that has to be assessed using standard field and conventional mapping workflows. For an appraisal, our DSM is compared directly with a similar DSM obtained by conventional airborne data acquisition using Leica RCD-30 metric camera as well as Trimble Phase One (P65+) camera. The comparison reveals that our approach can achieve meter level accuracy both in planimetric and vertical dimensions.
INTEGRATION OF IMAGE-DERIVED AND POS-DERIVED FEATURES FOR IMAGE BLUR DETECTION
Authors: Teo Tee-Ann , Zhan Kai-Zhi
Published: August 2016

The image quality plays an important role for Unmanned Aerial Vehicle (UAV)’s applications. The small fixed wings UAV is suffering from the image blur due to the crosswind and the turbulence. Position and Orientation System (POS), which provides the position and orientation information, is installed onto an UAV to enable acquisition of UAV trajectory. It can be used to calculate the positional and angular velocities when the camera shutter is open. This study proposes a POS-assisted method to detect the blur image. The major steps include feature extraction, blur image detection and verification. In feature extraction, this study extracts different features from images and POS. The image-derived features include mean and standard deviation of image gradient. For POS-derived features, we modify the traditional degree-of-linear-blur (blinear) method to degree-of-motion-blur (bmotion) based on the collinear condition equations and POS parameters. Besides, POS parameters such as positional and angular velocities are also adopted as POS-derived features. In blur detection, this study uses Support Vector Machines (SVM) classifier and extracted features (i.e. image information, POS data, blinear and bmotion) to separate blur and sharp UAV images. The experiment utilizes SenseFly eBee UAV system. The number of image is 129. In blur image detection, we use the proposed degree-of-motion-blur and other image features to classify the blur image and sharp images. The classification result shows that the overall accuracy using image features is only 56%. The integration of image-derived and POS-derived features have improved the overall accuracy from 56% to 76% in blur detection. Besides, this study indicates that the performance of the proposed degree-of-motion-blur is better than the traditional degree-of-linear-blur.
NON-DESTRUCTIVE MONITORING OF RICE BY HYPERSPECTRAL IN-FIELD SPECTROMETRY AND UAV-BASED REMOTE SENSING: CASE STUDY OF FIELD-GROWN RICE IN NORTH RHINE-WESTPHALIA, GERMANY
Authors: Willkomm M. , Bolten A. , Bareth G.
Published: August 2016

In the context of an increasing world population, the demand for agricultural crops is continuously rising. Especially rice plays a key role in food security, not only in Asia. To increase crop production of rice, either productivity of plants has to be improved or new cultivation areas have to be found. In this context, our study investigated crop growth of paddy rice (Oryza Sativa J.) in Germany. An experimental field in the vegetation period of 2014 with two nitrogen treatments was conducted using remote sensing methods. The research project focussed on two main aspects: (1) the potential of UAV-based and hyperspectral remote sensing methods to monitor selected growth parameters at different phenological stages; (2) the potential of paddy rice cultivation under the present climate condition in western Germany. We applied a low-cost UAV-system (Unmanned Aerial Vehicle) to generate high resolution Crop Surface Models (CSM). These were compared with hyperspectral in-field measurements and directly measured agronomic parameters (fresh and dry aboveground biomass (AGB), leaf-area-index (LAI) and plant nitrogen concentration (PNC)). For all acquisition dates we could determine single in-field structures in the CSM (e.g. distribution of hills) and different growth characteristics between the nitrogen treatments. Especially in the second half of the growing season, the plants with higher nitrogen availability were about 25 – 30 % larger. The plant height in the CSM correlates particularly with fresh AGB and the LAI (R2 > 0.8). Thus, the conducted methods for plant growth monitoring can be a contribution for precision agriculture approaches.
PAIRWISE-SVM FOR ON-BOARD URBAN ROAD LIDAR CLASSIFICATION
Authors: Shu Zhen , Sun Kai , Qiu Kaijin , Ding Kou
Published: August 2016

The common method of LiDAR classifications is Markov random fields (MRF). Based on construction of MRF energy function, spectral and directional features are extracted for on-board urban point clouds. The MRF energy function is consisted of unary and pairwise potentials. The unary terms are computed by SVM classifictaion. The initial labeling is mainly processed through geometrical shapes. The pairwise potential is estimated by Naïve Bayes. From training data, the probability of adjacent objects is computed by prior knowledge. The final labeling method is reweighted message-passing to minimization the energy function. The MRF model is difficult to process the large-scale misclassification. We propose a super-voxel clustering method for over-segment and grouping segment for large objects. Trees, poles ground, and building are classified in this paper. The experimental results show that this method improves the accuracy of classification and speed of computation.
PRECURSORY SLOPE DEFORMATION AROUND LANDSLIDE AREA DETECTED BY INSAR THROUGHOUT JAPAN
Authors: Nakano T. , Wada K. , Yamanaka M. , Kamiya I. , Nakajima H.
Published: August 2016

Interferometric Synthetic Aperture Radar (InSAR) technique is able to detect a slope deformation around landslide (e.g., Singhroy et al., 2004; Une et al., 2008; Riedel and Walther, 2008; Sato et al., 2014). Geospatial Information Authority (GSI) of Japan has been performing the InSAR analysis regularly by using ALOS/PALSAR data and ALOS-2/PALSAR-2 data throughout Japan. There are a lot of small phase change sites except for crustal deformation with earthquake or volcano activity in the InSAR imagery. Most of the phase change sites are located in landslide area. We conducted field survey at the 10 sites of those phase change sites. As a result, we identified deformation of artificial structures or linear depressions caused by mass movement at the 9 sites. This result indicates that InSAR technique can detect on the continual deformation of landslide block for several years. GSI of Japan will continue to perform the InSAR analysis throughout Japan. Therefore, we will be able to observe and monitor precursory slope deformation around landslide areas throughout Japan.
GEODETIC REFERENCE SYSTEM TRANSFORMATIONS OF 3D ARCHIVAL GEOSPATIAL DATA USING A SINGLE SSC TERRASAR-X IMAGE
Authors: Vassilaki D. I. , Stamos A. A.
Published: August 2016

Many older maps were created using reference coordinate systems which are no longer available, either because no information to a datum was taken in the first place or the reference system is forgotten. In other cases the relationship between the map’s coordinate system is not known with precision, meaning that its absolute error is much larger than its relative error. In this paper the georeferencing of medium-scale maps is computed using a single TerraSAR-X image. A single TerraSAR-X image has high geolocation accuracy but it has no 3D information. The map, however, provides the missing 3D information, and thus it is possible to compute the georeferencing of the map using the TerraSAR-X geolocation information, assembling the information of both sources to produce 3D points in the reference system of the TerraSAR-X image. Two methods based on this concept are proposed. The methods are tested with real world examples and the results are promising for further research.
MEDIUM FORMAT CAMERA EVALUATION BASED ON THE LATEST PHASE ONE TECHNOLOGY
Authors: Tölg T. , Kemper G. , Kalinski D.
Published: August 2016

In early 2016, Phase One Industrial launched a new high resolution camera with a 100 MP CMOS sensor. CCD sensors excel at ISOs up to 200, but in lower light conditions, exposure time must be increased and Forward Motion Compensation (FMC) has to be employed to avoid smearing the images. The CMOS sensor has an ISO range of up to 6400, which enables short exposures instead of using FMC.

 This paper aims to evaluate the strengths of each of the sensor types based on real missions over a test field in Speyer, Germany, used for airborne camera calibration. The test field area has about 30 Ground Control Points (GCPs), which enable a perfect scenario for a proper geometric evaluation of the cameras. The test field includes both a Siemen star and scale bars to show any blurring caused by forward motion.

 The result of the comparison showed that both cameras offer high accuracy photogrammetric results with post processing, including triangulation, calibration, orthophoto and DEM generation. The forward motion effect can be compensated by a fast shutter speed and a higher ISO range of the CMOS-based camera. The results showed no significant differences between cameras.
THE EFFECTIVE OF DIFFERENT EXCITATION WAVELENGTHS ON THE IDENTIFICATION OF PLANT SPECIES BASED ON FLUORESCENCE LIDAR
Authors: Yang Jian , Gong Wei , Shi Shuo , Du Lin , Sun Jia , Song Shalei
Published: August 2016

Laser-induced fluorescence (LIF) served as an active technology has been widely used in many field, and it is closely related to excitation wavelength (EW). The objective of this investigation is to discuss the performance of different EWs of LIF LiDAR in identifying plant species. In this study, the 355, 460 and 556 nm lasers were utilized to excite the leaf fluorescence and the fluorescence spectra were measured by using the LIF LiDAR system built in the laboratory. Subsequently, the principal component analysis (PCA) with the help of support vector machine (SVM) was utilized to analyse fluorescence spectra. For the three EWs, the overall identification rates of the six plant species were 80 %, 83.3 % and 90 %. Experimental results demonstrated that 556 nm excitation light source is superior to 355 and 460 nm for the classification of the plant species for the same genus in this study. Thus, an appropriate excitation wavelength should be considered when the LIF LiDAR was utilized in the field of remote sensing based on the LIF technology.
POTENTIAL OF AIRBORNE IMAGING SPECTROSCOPY AT CZECHGLOBE
Authors: Hanuš J. , Fabiánek T. , Fajmon L.
Published: August 2016

Ecosystems, their services, structures and functions are affected by complex environmental processes, which are both natural and human-induced and globally changing. In order to understand how ecosystems behave in globally changing environment, it is important to monitor the current status of ecosystems and their structural and functional changes in time and space. An essential tool allowing monitoring of ecosystems is remote sensing (RS). Many ecosystems variables are being translated into a spectral response recorded by RS instruments. It is however important to understand the complexity and synergies of the key ecosystem variables influencing the reflected signal. This can be achieved by analysing high resolution RS data from multiple sources acquired simultaneously from the same platform. Such a system has been recently built at CzechGlobe - Global Change Research Institute (The Czech Academy of Sciences).

 CzechGlobe has been significantly extending its research infrastructure in the last years, which allows advanced monitoring of ecosystem changes at hierarchical levels spanning from molecules to entire ecosystems. One of the CzechGlobe components is a laboratory of imaging spectroscopy. The laboratory is now operating a new platform for advanced remote sensing observations called FLIS (Flying Laboratory of Imaging Spectroscopy). FLIS consists of an airborne carrier equipped with passive RS systems. The core instrument of FLIS is a hyperspectral imaging system provided by Itres Ltd. The hyperspectral system consists of three spectroradiometers (CASI 1500, SASI 600 and TASI 600) that cover the reflective spectral range from 380 to 2450 nm, as well as the thermal range from 8 to 11.5 μm. The airborne platform is prepared for mounting of full-waveform laser scanner Riegl-Q780 as well, however a laser scanner is not a permanent part of FLIS. In 2014 the installation of the hyperspectral scanners was completed and the first flights were carried out with all sensors.

 The new hyperspectral imaging system required adaptations in the data pre-processing chain. The established pre-processing chain (radiometric, atmospheric and geometric corrections), which was tailored mainly to the AISA Eagle instrument operated at CzechGlobe since 2004, has been now modified to fit the new system and users needs. Continuous development of the processing chain is now focused mainly on establishing pre-processing of thermal data including emissivity estimation and also on joint processing of hyperspectral and laser scanning data.
GEOMETRIC CALIBRATION OF ZIYUAN-3 THREE-LINE CAMERAS COMBINING GROUND CONTROL POINTS AND LINES
Authors: Cao Jinshan , Yuan Xiuxiao , Gong Jianya
Published: August 2016

Due to the large biases between the laboratory-calibrated values of the orientation parameters and their in-orbit true values, the initial direct georeferencing accuracy of the Ziyuan-3 (ZY-3) three-line camera (TLC) images can only reach the kilometre level. In this paper, a point-based geometric calibration model of the ZY-3 TLCs is firstly established by using the collinearity constraint, and then a line-based geometric calibration model is established by using the coplanarity constraint. With the help of both the point-based and the line-based models, a feasible in-orbit geometric calibration approach for the ZY-3 TLCs combining ground control points (GCPs) and ground control lines (GCLs) is presented. Experimental results show that like GCPs, GCLs can also provide effective ground control information for the geometric calibration of the ZY-3 TLCs. The calibration accuracy of the look angles of charge-coupled device (CCD) detectors achieved by using the presented approach reached up to about 1.0''. After the geometric calibration, the direct georeferencing accuracy of the ZY-3 TLC images without ground controls was significantly improved from the kilometre level to better than 11 m in planimetry and 9 m in height. A more satisfactory georeferencing accuracy of better than 3.5 m in planimetry and 3.0 m in height was achieved after the block adjustment with four GCPs.
CRITICAL ASSESSMENT OF CORRECTION METHODS FOR FISHEYE LENS DISTORTION
Authors: Liu Y. , Tian C. , Huang Y.
Published: August 2016

A fisheye lens is widely used to create a wide panoramic or hemispherical image. It is an ultra wide-angle lens that produces strong visual distortion. The distortion modeling and estimation of the fisheye lens are the crucial step for fisheye lens calibration and image rectification in computer vision and close-range photography. There are two kinds of distortion: radial and tangential distortion. Radial distortion is large for fisheye imaging and critical for the subsequent image processing. Although many researchers have developed calibration algorithms of radial distortion of fisheye lens, quantitative evaluation of the correction performance has remained a challenge. This is the first paper that intuitively and objectively evaluates the performance of five different calibration algorithms. Upto- date research on fisheye lens calibration is comprehensively reviewed to identify the research need. To differentiate their performance in terms of precision and ease-using, five methods are then tested using a diverse set of actual images of the checkerboard that are taken at Wuhan University, China under varying lighting conditions, shadows, and shooting angles. The method of rational function model, which was generally used for wide-angle lens correction, outperforms the other methods. However, the one parameter division model is easy for practical use without compromising too much the precision. The reason is that it depends on the linear structure in the image and requires no preceding calibration. It is a tradeoff between correction precision and ease-using. By critically assessing the strengths and limitations of the existing algorithms, the paper provides valuable insight and guideline for future practice and algorithm development that are important for fisheye lens calibration. It is promising for the optimal design of lens correction models that are suitable for the millions of portable imaging devices.
COMPARATIVE ANALYSIS OF DIFFERENT LIDAR SYSTEM CALIBRATION TECHNIQUES
Authors: Miller M. , Habib A.
Published: August 2016

With light detection and ranging (LiDAR) now being a crucial tool for engineering products and on the fly spatial analysis, it is necessary for the user community to have standardized calibration methods. The three methods in this study were developed and proven by the Digital Photogrammetry Research Group (DPRG) for airborne LiDAR systems and are as follows; Simplified, Quasi-Rigorous, and Rigorous. In lieu of using expensive control surfaces for calibration, these methods compare overlapping LiDAR strips to estimate the systematic errors. These systematic errors are quantified by these methods and include the lever arm biases, boresight biases, range bias and scan angle scale bias. These three methods comprehensively represent all of the possible flight configurations and data availability and this paper will test the limits of the method with the most assumptions, the simplified calibration, by using data that violates the assumptions it’s math model is based on and compares the results to the quasi-rigorous and rigorous techniques. The overarching goal is to provide a LiDAR system calibration that does not require raw measurements which can be carried out with minimal control and flight lines to reduce costs. This testing is unique because the terrain used for calibration does not contain gable roofs, all other LiDAR system calibration testing and development has been done with terrain containing features with high geometric integrity such as gable roofs.
A NOVEL SUB-PIXEL MATCHING ALGORITHM BASED ON PHASE CORRELATION USING PEAK CALCULATION
Authors: Xie Junfeng , Mo Fan , Yang Chao , Li Pin , Tian Shiqiang
Published: August 2016

The matching accuracy of homonymy points of stereo images is a key point in the development of photogrammetry, which influences the geometrical accuracy of the image products. This paper presents a novel sub-pixel matching method phase correlation using peak calculation to improve the matching accuracy. The peak theoretic centre that means to sub-pixel deviation can be acquired by Peak Calculation (PC) according to inherent geometrical relationship, which is generated by inverse normalized cross-power spectrum, and the mismatching points are rejected by two strategies: window constraint, which is designed by matching window and geometric constraint, and correlation coefficient, which is effective for satellite images used for mismatching points removing. After above, a lot of high-precise homonymy points can be left. Lastly, three experiments are taken to verify the accuracy and efficiency of the presented method. Excellent results show that the presented method is better than traditional phase correlation matching methods based on surface fitting in these aspects of accuracy and efficiency, and the accuracy of the proposed phase correlation matching algorithm can reach 0.1 pixel with a higher calculation efficiency.
THE OUTDOOR RAPID CALIBRATION TECHNIQUE AND REALIZATION OF NONMETRIC DIGITAL CAMERA BASED ON THE METHOD OF MULTI-IMAGE DLT AND RESECTION
Authors: Qiang Zhang , Jian-jing Shen , Meng-qing Sun
Published: August 2016

For non-metric CCD digital camera features and the needs of Rapid field non-metric cameras calibration, the error sources was detailed analyzed and a mathematical calibration model has been founded. Both detailed multi-image group iterative method for solving DLT coefficient, the elements of interior orientation and distortion parameters of lens and the multi-image resection method for solving the elements of interior orientation, elements of exterior orientation and distortion parameters of lens have been discussed. A standard steel cage (e.g. Figure 1) has been made for real calibrating non-metric cameras outdoor quickly. In order to verify the accuracy, each method mentioned has been used to solve elements of interior orientation and distortion parameters with the same camera (e.g. Figure 2) and the same test images. The results of accuracy show that the maximum X error was 0.2585mm, the maximum Y error was 0.6719mm and the maximum Z error was 0.1319mm by using multi-image DLT algorithm. On the other hand, the maximum X error was 0.1914mm, the maximum Y error was 0.9808mm and the maximum Z error was 0.1453mm by using multi-image resection algorithm. The forward intersection accuracy of the two methods was quite, and the both were less than 1mm. By using multi-image DLT algorithm the planimetric accuracy was less than 0.2585mm and the height accuracy was less than 0.6719mm. On the other hand, by using multi-image resection algorithm the planimetric accuracy was less than 0.1914mm and the height accuracy was less than 0.9808mm. The planimetric accuracy of resection algorithm was the better than DLT algorithm, but the elevation accuracy of DLT algorithm was the better than resection algorithm. In summary both method can be accepted for nonmetric camera calibration. But also the solver accuracy in the inner orientation elements and distortion parameters was not very high has been noted. However for non-metric camera, the true value of inner orientation elements and lens distortion were unknown did not affect the accuracy of photogrammetry.
JAVA-LIBRARY FOR THE ACCESS, STORAGE AND EDITING OF CALIBRATION METADATA OF OPTICAL SENSORS
Authors: Firlej M. , Kresse W.
Published: August 2016

The standardization of the calibration of optical sensors in photogrammetry and remote sensing has been discussed for more than a decade. Projects of the German DGPF and the European EuroSDR led to the abstract International Technical Specification ISO/TS 19159-1:2014 “Calibration and validation of remote sensing imagery sensors and data – Part 1: Optical sensors”.

 This article presents the first software interface for a read- and write-access to all metadata elements standardized in the ISO/TS 19159-1. This interface is based on an xml-schema that was automatically derived by ShapeChange from the UML-model of the Specification. The software interface serves two cases. First, the more than 300 standardized metadata elements are stored individually according to the xml-schema. Secondly, the camera manufacturers are using many administrative data that are not a part of the ISO/TS 19159-1. The new software interface provides a mechanism for input, storage, editing, and output of both types of data. Finally, an output channel towards a usual calibration protocol is provided. The interface is written in Java.

 The article also addresses observations made when analysing the ISO/TS 19159-1 and compiles a list of proposals for maturing the document, i.e. for an updated version of the Specification.
IMPROVE THE ZY-3 HEIGHT ACCURACY USING ICESAT/GLAS LASER ALTIMETER DATA
Authors: Li Guoyuan , Tang Xinming , Gao Xiaoming , Zhang Chongyang , Li Tao
Published: August 2016

ZY-3 is the first civilian high resolution stereo mapping satellite, which has been launched on 9th, Jan, 2012. The aim of ZY-3 satellite is to obtain high resolution stereo images and support the 1:50000 scale national surveying and mapping. Although ZY-3 has very high accuracy for direct geo-locations without GCPs (Ground Control Points), use of some GCPs is still indispensible for high precise stereo mapping. The GLAS (Geo-science Laser Altimetry System) loaded on the ICESat (Ice Cloud and land Elevation Satellite), which is the first laser altimetry satellite for earth observation. GLAS has played an important role in the monitoring of polar ice sheets, the measuring of land topography and vegetation canopy heights after launched in 2003. Although GLAS has ended in 2009, the derived elevation dataset still can be used after selection by some criteria.

 In this paper, the ICESat/GLAS laser altimeter data is used as height reference data to improve the ZY-3 height accuracy. A selection method is proposed to obtain high precision GLAS elevation data. Two strategies to improve the ZY-3 height accuracy are introduced. One is the conventional bundle adjustment based on RFM and bias-compensated model, in which the GLAS footprint data is viewed as height control. The second is to correct the DSM (Digital Surface Model) straightly by simple block adjustment, and the DSM is derived from the ZY-3 stereo imaging after freedom adjustment and dense image matching. The experimental result demonstrates that the height accuracy of ZY-3 without other GCPs can be improved to 3.0 meter after adding GLAS elevation data. What’s more, the comparison of the accuracy and efficiency between the two strategies is implemented for application.
ABSOLUTE RADIOMETRIC CALIBRATION OF THE GÖKTÜRK-2 SATELLITE SENSOR USING TUZ GÖLÜ (LANDNET SITE) FROM NDVI PERSPECTIVE
Authors: Sakarya Ufuk , Hakkı Demirhan İsmail , Deveci Hüsne Seda , Teke Mustafa , Demirkesen Can , Küpçü Ramazan , Öztoprak A. Feray , Efendioğlu Mehmet , Şimşek F. Fehmi , Berke Erdinç , Gürbüz Sevgi Zübeyde
Published: August 2016

TÜBİTAK UZAY has conducted a research study on the use of space-based satellite resources for several aspects of agriculture. Especially, there are two precision agriculture related projects: HASSAS (Widespread application of sustainable precision agriculture practices in Southeastern Anatolia Project Region (GAP) Project) and AKTAR (Smart Agriculture Feasibility Project). The HASSAS project aims to study development of precision agriculture practice in GAP region. Multi-spectral satellite imagery and aerial hyperspectral data along with ground measurements was collected to analyze data in an information system. AKTAR aims to develop models for irrigation, fertilization and spectral signatures of crops in Inner Anatolia. By the end of the project precision agriculture practices to control irrigation, fertilization, pesticide and estimation of crop yield will be developed. Analyzing the phenology of crops using NDVI is critical for the projects. For this reason, absolute radiometric calibration of the Red and NIR bands in space-based satellite sensors is an important issue. The Göktürk-2 satellite is an earth observation satellite which was designed and built in Turkey and was launched in 2012. The Göktürk-2 satellite sensor has a resolution 2.5 meters in panchromatic and 5 meters in R/G/B/NIR bands. The absolute radiometric calibration of the Göktürk-2 satellite sensor was performed via the ground-based measurements - spectra-radiometer, sun photometer, and meteorological station- in Tuz Gölü cal/val site in 2015. In this paper, the first ground-based absolute radiometric calibration results of the Göktürk-2 satellite sensor using Tuz Gölü is demonstrated. The absolute radiometric calibration results of this paper are compared with the published cross-calibration results of the Göktürk-2 satellite sensor utilizing Landsat 8 imagery. According to the experimental comparison results, the Göktürk-2 satellite sensor coefficients for red and NIR bands estimated in this work sustained to agree within 2% of calibration coefficients estimated in the cross-calibration results.
ON-ORBIT GEOMETRIC CALIBRATION APPROACH FOR HIGH-RESOLUTION GEOSTATIONARY OPTICAL SATELLITE GaoFen-4
Authors: Wang Mi , Cheng Yufeng , Long Xiaoxiang , Yang Bo
Published: August 2016

The GaoFen-4 (GF-4) remote sensing satellite is China’s first civilian high-resolution geostationary optical satellite, which has been launched at the end of December 2015. To guarantee the geometric quality of imagery, this paper presents an on-orbit geometric calibration method for the area-array camera of GF-4. Firstly, we introduce the imaging features of area-array camera of GF-4 and construct a rigorous imaging model based on the analysis of the major error sources from three aspects: attitude measurement error, orbit measurement error and camera distortion. Secondly, we construct an on-orbit geometric calibration model by selecting and optimizing parameters of the rigorous geometric imaging model. On this basis, the calibration parameters are divided into two groups: external and internal calibration parameters. The external parameters are installation angles between the area-array camera and the star tracker, and we propose a two-dimensional direction angle model as internal parameters to describe the distortion of the areaarray camera. Thirdly, we propose a stepwise parameters estimation method that external parameters are estimated firstly, then internal parameters are estimated based on the generalized camera frame determined by external parameters. Experiments based on the real data of GF-4 shows that after on-orbit geometric calibration, the geometric accuracy of the images without ground control points is significantly improved.
GEOREFERENCING ACCURACY ANALYSIS OF A SINGLE WORLDVIEW-3 IMAGE COLLECTED OVER MILAN
Authors: Barazzetti L. , Roncoroni F. , Brumana R. , Previtali M.
Published: August 2016

The use of rational functions has become a standard for very high-resolution satellite imagery (VHRSI). On the other hand, the overall geolocalization accuracy via direct georeferencing from on board navigation components is much worse than image ground sampling distance (predicted < 3.5 m CE90 for WorldView-3, whereas GSD = 0.31 m for panchromatic images at nadir).

 This paper presents the georeferencing accuracy results obtained from a single WorldView-3 image processed with a bias compensated RPC camera model. Orientation results for an image collected over Milan are illustrated and discussed for both direct and indirect georeferencing strategies as well as different bias correction parameters estimated from a set of ground control points. Results highlight that the use of a correction based on two shift parameters is optimal for the considered dataset.
OBJECT-BASED ANALYSIS OF LIDAR GEOMETRIC FEATURES FOR VEGETATION DETECTION IN SHADED AREAS
Authors: Lin Yu-Ching , Lin ChinSu , Tsai Ming-Da , Lin Chun-Lin
Published: August 2016

The extraction of land cover information from remote sensing data is a complex process. Spectral information has been widely utilized in classifying remote sensing images. However, shadows limit the use of multispectral images because they result in loss of spectral radiometric information. In addition, true reflectance may be underestimated in shaded areas. In land cover classification, shaded areas are often left unclassified or simply assigned as a shadow class. Vegetation indices from remote sensing measurement are radiation-based measurements computed through spectral combination. They indicate vegetation properties and play an important role in remote sensing of forests. Airborne light detection and ranging (LiDAR) technology is an active remote sensing technique that produces a true orthophoto at a single wavelength. This study investigated three types of geometric lidar features where NDVI values fail to represent meaningful forest information. The three features include echo width, normalized eigenvalue, and standard deviation of the unit weight observation of the plane adjustment, and they can be derived from waveform data and discrete point clouds. Various feature combinations were carried out to evaluate the compensation of the three lidar features to vegetation detection in shaded areas. Echo width was found to outperform the other two features. Furthermore, surface characteristics estimated by echo width were similar to that by normalized eigenvalues. Compared to the combination of only NDVI and mean height difference, those including one of the three features had a positive effect on the detection of vegetation class.
MULTI-SATELLITE SCHEDULING APPROACH FOR DYNAMIC AREAL TASKS TRIGGERED BY EMERGENT DISASTERS
Authors: Niu X. N. , Zhai X. J. , Tang H. , Wu L. X.
Published: August 2016

The process of satellite mission scheduling, which plays a significant role in rapid response to emergent disasters, e.g. earthquake, is used to allocate the observation resources and execution time to a series of imaging tasks by maximizing one or more objectives while satisfying certain given constraints. In practice, the information obtained of disaster situation changes dynamically, which accordingly leads to the dynamic imaging requirement of users. We propose a satellite scheduling model to address dynamic imaging tasks triggered by emergent disasters. The goal of proposed model is to meet the emergency response requirements so as to make an imaging plan to acquire rapid and effective information of affected area. In the model, the reward of the schedule is maximized. To solve the model, we firstly present a dynamic segmenting algorithm to partition area targets. Then the dynamic heuristic algorithm embedding in a greedy criterion is designed to obtain the optimal solution. To evaluate the model, we conduct experimental simulations in the scene of Wenchuan Earthquake. The results show that the simulated imaging plan can schedule satellites to observe a wider scope of target area. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.
ON THE EVALUATION OF GNSS COMPLEMENTARY BY USING QUASIZENITH SATELLITE OF JAPAN
Authors: Sekiguchi N. , Shikada M. , Kanai T.
Published: August 2016

The positional information has an important role in our lifestyle. People need to get positional information by GNSS. The satellite positioning must receive a signal from four or more satellites, however, most of Japanese country is covered with mountain and urban area has a lot of tall buildings. Then Japanese government launched QZS (Quasi Zenith Satellite) which is the first satellite of QZSS (Quasi Zenith Satellite System) in 2010. QZSS including QZS can improve positioning accuracy and reliability. QZS has 6 signals by using four kinds of frequency. These signals are the same frequency of GPS and GLONASS and so on. This paper was reported about the comparison of the positioning between GPS and QZSS.
PLÉIADES PROJECT: ASSESSMENT OF GEOREFERENCING ACCURACY, IMAGE QUALITY, PANSHARPENING PERFORMENCE AND DSM/DTM QUALITY
Authors: Topan Hüseyin , Cam Ali , Özendi Mustafa , Oruç Murat , Jacobsen Karsten , Taşkanat Talha
Published: August 2016

Pléiades 1A and 1B are twin optical satellites of Optical and Radar Federated Earth Observation (ORFEO) program jointly running by France and Italy. They are the first satellites of Europe with sub-meter resolution. Airbus DS (formerly Astrium Geo) runs a MyGIC (formerly Pléiades Users Group) program to validate Pléiades images worldwide for various application purposes. The authors conduct three projects, one is within this program, the second is supported by BEU Scientific Research Project Program, and the third is supported by TÜBİTAK. Assessment of georeferencing accuracy, image quality, pansharpening performance and Digital Surface Model/Digital Terrain Model (DSM/DTM) quality subjects are investigated in these projects. For these purposes, triplet panchromatic (50 cm Ground Sampling Distance (GSD)) and VNIR (2 m GSD) Pléiades 1A images were investigated over Zonguldak test site (Turkey) which is urbanised, mountainous and covered by dense forest.

 The georeferencing accuracy was estimated with a standard deviation in X and Y (SX, SY) in the range of 0.45m by bias corrected Rational Polynomial Coefficient (RPC) orientation, using ~170 Ground Control Points (GCPs). 3D standard deviation of ±0.44m in X, ±0.51m in Y, and ±1.82m in Z directions have been reached in spite of the very narrow angle of convergence by bias corrected RPC orientation. The image quality was also investigated with respect to effective resolution, Signal to Noise Ratio (SNR) and blur coefficient. The effective resolution was estimated with factor slightly below 1.0, meaning that the image quality corresponds to the nominal resolution of 50cm. The blur coefficients were achieved between 0.39-0.46 for triplet panchromatic images, indicating a satisfying image quality. SNR is in the range of other comparable space borne images which may be caused by de-noising of Pléiades images. The pansharpened images were generated by various methods, and are validated by most common statistical metrics and also visual interpretation. The generated DSM and DTM were achieved with ±1.6m standard deviation in Z (SZ) in relation to a reference DTM.
THE SYSTEM OVERVIEW AND GEOMETRIC IMAGE QUALITY OF THE TH-1 SATELLITE
Authors: Wang Jianrong , Hu Xin
Published: August 2016

The Tian-Hui 1 (TH-1) is the first stereo mapping transmission satellite in China, and the primary mission goal of the satellite is for topographic mapping at 1:50,000 scale without Ground Control Points (GCPs). 1st, 2nd and 3rd satellite of TH-1 was launched on August 24, 2010, May 6, 2012 and October 26, 2015. In TH-1 satellite, many payloads are put on a small satellite platform, which has a low cost. The optical camera of TH-1 includes Line-Matrix CCD (LMCCD) camera, high resolution camera and multispectral camera with 60 km ground swath width. To get high geometric accuracy without GCPs, the on-orbit calibration camera parameters and the Equivalent Frame Photo (EFP) Multi-functional bundle adjustment are proposed and realized in ground image processing of TH-1. In order to evaluate the location accuracy of TH-1, some testing fields are established. All GCPs of testing fields are measured by GPS. The GCPs are not participated the EFP Multi-functional bundle adjustment, and are only as Check Points (CPs) to evaluate the location accuracy. The evaluation of 1st satellite is shown: the horizontal accuracy is 10.3 m (RMSE) and the vertical accuracy is 5.7 m (RMSE) without GCPs, which can satisfy for topographic mapping at 1:50,000 scale. The overviews of TH-1 satellite are described in this paper: First, the system overview is introduced, including mission and optical camera of TH-1. Then, the on-orbit calibration camera parameters using LMCCD image and the EFP Multi-functional bundle adjustment are presented. Finally, the location performance is analysed without GCPs and with different number of GCPs. In addition, the products of TH-1 are introduced.
3D FEATURE POINT EXTRACTION FROM LIDAR DATA USING A NEURAL NETWORK
Authors: Feng Y. , Schlichting A. , Brenner C.
Published: August 2016

Accurate positioning of vehicles plays an important role in autonomous driving. In our previous research on landmark-based positioning, poles were extracted both from reference data and online sensor data, which were then matched to improve the positioning accuracy of the vehicles. However, there are environments which contain only a limited number of poles. 3D feature points are one of the proper alternatives to be used as landmarks. They can be assumed to be present in the environment, independent of certain object classes. To match the LiDAR data online to another LiDAR derived reference dataset, the extraction of 3D feature points is an essential step. In this paper, we address the problem of 3D feature point extraction from LiDAR datasets. Instead of hand-crafting a 3D feature point extractor, we propose to train it using a neural network. In this approach, a set of candidates for the 3D feature points is firstly detected by the Shi-Tomasi corner detector on the range images of the LiDAR point cloud. Using a back propagation algorithm for the training, the artificial neural network is capable of predicting feature points from these corner candidates. The training considers not only the shape of each corner candidate on 2D range images, but also their 3D features such as the curvature value and surface normal value in z axis, which are calculated directly based on the LiDAR point cloud. Subsequently the extracted feature points on the 2D range images are retrieved in the 3D scene. The 3D feature points extracted by this approach are generally distinctive in the 3D space. Our test shows that the proposed method is capable of providing a sufficient number of repeatable 3D feature points for the matching task. The feature points extracted by this approach have great potential to be used as landmarks for a better localization of vehicles.
MONITORING CAPABILITIES OF A MOBILE MAPPING SYSTEM BASED ON NAVIGATION QUALITIES
Authors: Jing H. , Slatcher N. , Meng X. , Hunter G.
Published: August 2016

Mobile mapping systems are becoming increasingly popular as they can build 3D models of the environment rapidly by using a laser scanner that is integrated with a navigation system. 3D mobile mapping has been widely used for applications such as 3D city modelling and mapping of the scanned environments. However, accurate mapping relies on not only the scanner’s performance but also on the quality of the navigation results (accuracy and robustness) . This paper discusses the potentials of using 3D mobile mapping systems for landscape change detection, that is traditionally carried out by terrestrial laser scanners that can be accurately geo-referenced at a static location to produce highly accurate dense point clouds. Yet compared to conventional surveying using terrestrial laser scanners, several advantages of mobile mapping systems can be identified. A large area can be monitored in a relatively short period, which enables high repeat frequency monitoring without having to set-up dedicated stations. However, current mobile mapping applications are limited by the quality of navigation results, especially in different environments. The change detection ability of mobile mapping systems is therefore significantly affected by the quality of the navigation results. This paper presents some data collected for the purpose of monitoring from a mobile platform. The datasets are analysed to address current potentials and difficulties. The change detection results are also presented based on the collected dataset. Results indicate the potentials of change detection using a mobile mapping system and suggestions to enhance quality and robustness.
ROAD SIGNS DETECTION AND RECOGNITION UTILIZING IMAGES AND 3D POINT CLOUD ACQUIRED BY MOBILE MAPPING SYSTEM
Authors: Li Y. H. , Shinohara T. , Satoh T. , Tachibana K.
Published: August 2016

High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.
VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION
Authors: Schlichting A. , Brenner C.
Published: August 2016

LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees.

 For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.