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Every type of remote sensing sensor has its own advantages and limitations. Integration of data from various remote sensing devices is increasingly becoming common to produce a better mapping product. For example, Light Detection and Ranging (LiDAR) data has better vertical accuracy compared to horizontal accuracy, whereas 3D data produced using aerial images has better horizontal accuracy compared to vertical accuracy. LiDAR and aerial images have several complementary properties. Therefore, integration of these two datasets could result in a better topographic product. In this article, the LiDAR data are used as vertical control to perform aerial triangulation using aerial images. The vertical measurement of LiDAR data and image plane coordinates of the corresponding point from aerial images were considered as known parameters. This method was implemented using synthetic data consisting of 54 ground points and three aerial images. Eight different scenarios were experimented that showed increased horizontal and vertical accuracy when compared to LiDAR or aerial images alone. [ABSTRACT FROM AUTHOR]

In urgent observations after disasters, we can mention that the image matching processing is an essential technique to establish more stable and rapid 3D data generation. Particularly, multi-images taken from various viewpoints are useful in the disaster monitoring. Thus, feature and corresponded point detection would be designed for a multi-image matching. Recently, Structure from Motion (SfM) is often applied to generate 3D data. The SfM is useful approach to generate 3D data from images of random viewpoints. However, Scale-Invariant Feature Transform (SIFT) requires a plenty of time to detect feature points and corresponded points from multi-images. Therefore, we proposed a methodology to improve triplet matching and SfM with line segments extracted from images. Moreover, we evaluated our methodology using multi-images taken from aerial triplet camera. [ABSTRACT FROM AUTHOR]

In aerial photogrammetry of island and reef areas, traditional aerial triangulation cannot be performed because many images in the block are partially or even completely covered by water, and thus there are not enough tie points among adjacent images. To solve this problem, an effective algorithm of position and orientation system (POS) integrated bundle block adjustment is proposed. The exterior orientation parameters of each image are modeled as functions of corresponding POS observations and their estimated systematic errors. A POS integrated bundle adjustment model is designed with the purpose of effectively eliminating the systematic errors of inertial measurement unit observations. Experimental results of three sets of island aerial images show that the proposed approach can compensate for the systematic errors of pos observations effectively. The topographic mapping requirements of hilly terrain at 1:2 000 scale can be fulfilled, provided that at least one ground control point is used in the bundle adjustment. [ABSTRACT FROM AUTHOR]

Abstract: Harnessing the radiometric information provided by photogrammetric flights could be useful in increasing the thematic applications of aerial images. The aim of this paper is to improve relative and absolute homogenization in aerial images by applying atmospheric correction and treatment of bidirectional effects. We propose combining remote sensing methodologies based on radiative transfer models and photogrammetry models, taking into account the three-dimensional geometry of the images (external orientation and Digital Elevation Model). The photogrammetric flight was done with a Z/I Digital Mapping Camera (DMC) with a Ground Sample Distance (GSD) of 45cm. Spectral field data were acquired by defining radiometric control points in order to apply atmospheric correction models, obtaining calibration parameters from the camera and surface reflectance images. Kernel-driven models were applied to correct the anisotropy caused by the bidirectional reflectance distribution function (BRDF) of surfaces viewed under large observation angles with constant illumination, using the overlapping area between images and the establishment of radiometric tie points. Two case studies were used: 8-bit images with applied Lookup Tables (LUTs) resulting from the conventional photogrammetric workflow for BRDF studies and original 12-bit images (Low Resolution Color, LRC) for the correction of atmospheric and bidirectional effects. The proposed methodology shows promising results in the different phases of the process. The geometric kernel that shows the best performance is the Lidense kernel. The homogenization factor in 8-bit images ranged from 6% to 25% relative to the range of digital numbers (0–255), and from 18% to 35% relative to levels of reflectance (0–100) in the 12-bit images, representing a relative improvement of approximately 1–30%, depending on the band analyzed. [Copyright &y& Elsevier]

Abstract-This brief describes a single-vehicle tracking algorithm relying on active contours for target extraction and an extended Kalman filter for relative position estimation. The primary difficulty lies in the estimation and regulation of range using monocular vision. The work represents a first step towards treating the problem of the control of several unmanned vehicles flying in formation using only local visual information. In particular, allowing only onboard passive sensing of the external environment, we seek to study the achievable closed-loop performance under this model. [ABSTRACT FROM AUTHOR]

A shape reconstruction algorithm is formulated for the multimonostatic configuration and the 2-D geometry. The imaging algorithm is based on the Kirchhoff approximation, works in the frequency domain, and exploits the singular value decomposition tool to achieve a stable solution. The effectiveness of the reconstruction algorithm is shown by processing synthetic data in the time domain generated via a finite-difference time domain code. A performance analysis of the solution algorithm is addressed with varying host medium and measurement configurations, also by processing synthetic data for a 3-D geometry. Finally, an experimental validation of the technique is performed due to data collected by a time-domain ground-penetrating radar for buried pipe detection and localization. [ABSTRACT FROM AUTHOR]

We introduce a new class of active contour models that hold great promise for region and shape modelling, and we apply a special case of these models to the extraction of road networks from satellite and aerial imagery. The new models are arbitrary polynomial functionals on the space of boundaries, and thus greatly generalize the linear functionals used in classical contour energies. While classical energies are expressed as single integrals over the contour, the new energies incorporate multiple integrals, and thus describe long-range interactions between different sets of contour points. As prior terms, they describe families of contours that share complex geometric properties, without making reference to any particular shape, and they require no pose estimation. As likelihood terms, they can describe multi-point interactions between the contour and the data. To optimize the energies, we use a level set approach. The forces derived from the new energies are non-local however, thus necessitating an extension of standard level set methods. Networks are a shape family of great importance in a number of applications, including remote sensing imagery. To model them, we make a particular choice of prior quadratic energy that describes reticulated structures, and augment it with a likelihood term that couples the data at pairs of contour points to their joint geometry. Promising experimental results are shown on real images. [ABSTRACT FROM AUTHOR]

Direct georeferencing, also referred to as direct platform orientation (DPO), is defined as direct measurement of the imaging sensor external orientation parameters (EOP), using positioning and orientation sensors, such as the Global Positioning System (GPS) and Inertial Navigation System (INS) or Inertial Measurement Unit (IMU). Imaging sensors, most frequently supported by the DPO technique, are digital cameras, lidar systems, multi-spectral or hyper-spectral scanners, or interferometric synthetic aperture radar (INSAR). While for scanning sensors the use of DPO is compulsory, frame digital cameras can also directly benefit from this modern technique of sensor orientation. With direct sensor orientation, the requirement for ground control, tie-point matching and aerotriangulation (AT) is significantly reduced, or even entirely eliminated, resulting in shorter times of data acquisition and processing, and streamlined and highly automated data workflow and quality control. Most of the time, the requirement for ground control points is limited to periodic system calibrations and quality control check. Direct georeferencing is considered a fundamental technology of conventional mobile mapping systems (MMS). Despite significant progress in GSP/INS-based direct georeferencing technology in the last decade, there is still room for improvement in terms of better accuracy and better tolerance to cps outages. This paper is focused on three error modeling and compensation techniques that could potentially improve GPS/INS system's performance on both land-based and airborne platforms: (1) extended gravity compensation, (2) IMU signal de-noising, and (3) stochastic modeling of IMU errors. [ABSTRACT FROM AUTHOR]

Accurate 3D reconstruction/modelling from unmanned aerial vehicle (UAV)-based imagery has become the key prerequisite in various applications. Although current commercial software has automated the process of image-based reconstruction, a transparent system, which can be incorporated with different user-defined constraints, is still preferred by the photogrammetric research community. In this regard, this paper presents a transparent framework for the automated aerial triangulation of UAV images. The proposed framework is conducted in three steps. In the first step, two approaches, which take advantage of prior information regarding the flight trajectory, are implemented for reliable relative orientation recovery. Then, initial recovery of image exterior orientation parameters (EOPs) is achieved through either an incremental or global approach. Finally, a global bundle adjustment involving Ground Control Points (GCPs) and check points is carried out to refine all estimated parameters in the defined mapping coordinate system. Four real image datasets, which are acquired by two different UAV platforms, have been utilized to evaluate the feasibility of the proposed framework. In addition, a comparative analysis between the proposed framework and the existing commercial software is performed. The derived experimental results demonstrate the superior performance of the proposed framework in providing an accurate 3D model, especially when dealing with acquired UAV images containing repetitive pattern and significant image distortions. [ABSTRACT FROM AUTHOR]

The article presents several answers to a question on technical theory and practical applications of mapping and GIS.