A Directed-Line-Segment-Based Photogrammetry Method to Survey the Tunneling Working Surface of Mine Roadway

Absolute orientation is a basic technical work in digital image geologic logging of underground coal mine. Traditional control-point-based absolute orientation method requires setting object space control points of the known three-dimensional coordinates, which may lead to low efficiency. Therefore, this paper proposed a point-free close-range photogrammetry absolute orientation algorithm, which utilized direction line segments including plumb line segments and line segments with known directions and lengths to identify the dimensional orientation of a stereoscopic model. Experiment results show that the precision of the orientation results is favorable. σ _X and σ _Y are as high as 0.5 mm, and σ _Z is 0.3 mm. Finally, this paper introduced the application of the proposed algorithm in rapid geological logging of coal mine roadway, which was fast and reliable, convenient and feasible.     

GIS Based Urban Area Spatiotemporal Change Evaluation Using Landsat and Night Time Temporal Satellite Data

This study aims at determining the spatiotemporal change in urban areas by using multi-temporal satellite images with geographic information systems integration. In this study, the city of Erzincan was selected as the sample case. The analyses of change were conducted by using the optical satellite images from LANSAT TM dated 1987 and the LANDSAT ETM+ dated 2006, besides the night images from 1998, 2006 and 2010. Spatial change maps were created for the qualitative analysis, and change matrixes were formed for the quantitative assessment of these changes. The outcomes of these change analyses were then evaluated and interpreted in the light of the demographics of the population living in the area. The results obtained from the Landsat satellite images indicate that the area of the city expanded at the annual average rate of 1.65% in 1987–2006. Night images indicate that the city area grew at an annual average rate of 4.04% in 1998–2006, while this rate was 20.28% in the period of 2006–2010. The results of the study demonstrate that the usability and contribution of satellite images is quite significant in tracking and monitoring temporal and spatial change in the area.     

Surface Reflectance Climate Data Records (CDRs) is a Reliable Landsat ETM+ Source to Study Chlorophyll Content in Pecan Orchards

We evaluated the relationships among three Landsat Enhanced Thematic Mapper (ETM+) datasets, top-of-atmosphere (TOA) reflectance, surface reflectance climate data records (surface reflectance-_CDR) and atmospherically corrected images using Fast Line-of-Sight atmospheric analysis of Spectral Hypercubes model (surface reflectance-_FLAASH) and their linkto pecan foliar chlorophyll content(chl-cont). Foliar chlorophyll content as determined with a SPAD meter, and remotely-sensed data were collected from two mature pecan orchards (one grown in a sandy loam and the other in clay loam soil) during the experimental period. Enhanced vegetation index derived from remotely sensed data was correlated to chl-cont. At both orchards, TOA reflectance was significantly lower than surface reflectance within the 550–2400 nm wavelength range. Reflectance from atmospherically corrected images (surface reflectance-_CDR and surface reflectance-_FLAASH) was similar in the shortwave infrared (SWIR: 1550–1750 and 2080–2350 nm) and statistically different in the visible (350–700 nm). Enhanced vegetation index derived from surface reflectance-_CDR and surface reflectance-_FLAASH had higher correlation with chl-cont than TOA. Accordingly, surface reflectance is an essential prerequisite for using Landsat ETM+  data and TOA reflectance could lead to miss-/or underestimate chl-cont in pecan orchards. Interestingly, the correlation comparisons (Williams t test) between surface reflectance-_CDR and chl-cont was statistically similar to the correlation between chl-cont and commercial atmospheric correction model. Overall, surface reflectance-_CDR, which is freely available from the earth explorer portal, is a reliable atmospherically corrected Landsat ETM+ image source to study foliar chlorophyll content in pecan orchards.     

Investigation of SVM and Level Set Interactive Methods for Road Extraction from Google Earth Images

Currently, methods of extracting spatial information from satellite images are mainly based on visual interpretations and drawing the consequences by human factor, which is both costly and time consuming. A large volume of data collected by satellite sensors, and significant improvement in spatial and spectral resolution of these images require the development of new methods for optimal use of these data in order to produce rapid economic and updating road maps. In this study, a new automatic method is proposed for road extraction by integrating the SVM and Level Set methods. The estimated probability of classification by SVM is used as input in Level Set Method. The average of completeness, correctness, and quality was 84.19, 88.69 and 76.06% respectively indicate high performance of proposed method for road extraction from Google Earth images.     

Distributed Source Coding of Hyperspectral Images Based on Three-Dimensional Wavelet

To reduce the possibility of poor efficiency and weak anti-error capability while encoding and transmitting hyperspectral images, we present a distributed source coding scheme for hyperspectral images based on three-dimensional (3D) set partitioning in hierarchical trees (SPIHT). First, the 3D wavelet transform is performed on the hyperspectral image. Thereafter, the low frequency section is regarded as the Key frame and the high frequency section as the Wyner–Ziv frame to enable independent SPIHT coding through different transmission channels. The Wyner–Ziv encoder uses Turbo channel coding to create high frequency information that reflects the details of the image with better anti-error capacity, while the low frequency information shows the main energy of the image. In this study, we used SPIHT coding to acquire a bit stream with quality scalability. Results show that the proposed scheme is more efficient during coding, while at the same time providing improved anti-error capability and quality scalability of the bit stream.     

Implementation of RISAT-1 Hybrid Polarimetric Decomposition Techniques and Analysis Using Corner Reflector Data

With recent advances in polarimetry, Synthetic Aperture Radar (SAR) with Hybrid–polarity architecture, a demonstration of compact polarimetry enabled larger swath coverage, reduced PRF and SAR system complexity as compared to fully polarimetric systems. The first Hybrid Polarimetric Space-borne SAR in Earth Observation orbit, India’s Radar Imaging Satellite (RISAT-1) is a new-fangled gateway to remote sensing user community for land and oceanic applications. In response to a right-circular polarized transmitted signal, based on the derived stokes vectors, Stokes parameters are estimated to produce several useful quantitative measures for generating polarimetric decomposed image. m-delta, m-chi and m-alpha polarimetric decomposition methods along with suitable weighting functions in terms of three principal components are implemented which maps Stokes parameters to RGB image space for representing odd bounce, even bounce and volume scattering targets. Various RISAT-1 Hybrid Fine Resolution Stripmap Single-Look Complex SAR datasets acquired over deployed corner reflectors at calibration site, Shadnagar have been considered over which different hybrid polarimetric decomposition techniques are implemented using in-house developed software. Further analysis produced encouraging results with standard point targets like dihedral and trihedral corner reflectors against distributed targets in the same scene to demonstrate the scattering mechanisms as per their characteristics when interacted with a polarized signal were presented in this paper.     

Effects of Landslide Sampling Strategies on the Prediction Skill of Landslide Susceptibility Modelings

In this study, landslide susceptibility assessments were achieved using logistic regression, in a 523 km² area around the Eastern Mediterranean region of Southern Turkey. In reliable landslide susceptibility modeling, among others, an appropriate landslide sampling technique is always essential. In susceptibility assessments, two different random selection methods, ranging 78–83% for the train and 17–22% validation set in landslide affected areas, were applied. For the first, the landslides were selected based on their identity numbers considering the whole polygon while in the second, random grid cells of equal size of the former one was selected in any part of the landslides. Three random selections for the landslide free grid cells of equal proportion were also applied for each of the landslide affected data set. Among the landslide preparatory factors; geology, landform classification, land use, elevation, slope, plan curvature, profile curvature, slope length factor, solar radiation, stream power index, slope second derivate, topographic wetness index, heat load index, mean slope, slope position, roughness, dissection, surface relief ratio, linear aspect, slope/aspect ratio have been considered. The results showed that the susceptibility maps produced using the random selections considering the entire landslide polygons have higher performances by means of success and prediction rates.     

Comparative Analyses of the Point Cloud Produced by Using Close-Range Photogrammetry and Terrestrial Laser Scanning for Rock Surface

Point cloud produced by using theoretically and practically different techniques is one of the most preferred data types in various engineering applications and projects. The advanced methods to obtain point cloud data in terrestrial studies are close range photogrammetry (CRP) and terrestrial laser scanning (TLS). In the TLS technique, separated from the CRP in terms of system structure, denser point cloud at certain intervals can be produced. However, point clouds can be produced with the help of photographs taken at appropriate conditions depending on the hardware and software technologies. Adequate quality photographs can be obtained by consumer grade digital cameras, and photogrammetric software widely used nowadays provides the generation of point cloud support. The tendency and the desire for the TLS are higher since it constitutes a new area of research. Moreover, it is believed that TLS takes the place of CRP, reviewed as antiquated. In this study that is conducted on rock surfaces located at Istanbul Technical University Ayazaga Campus, whether point cloud produced by means photographs can be used instead of point cloud obtained by laser scanner device is investigated. Study is worked on covers approximately area of 30 m?×?10 m. In order to compare the methods, 2D and 3D analyses as well as accuracy assessment were conducted. 2D analysis is areal-based whereas 3D analysis is volume-based. Analyses results showed that point clouds in both cases are similar to each other and can be used for similar other studies. Also, because the factors affecting the accuracy of the basic data and derived product for both methods are quite variable, it was concluded that it is not appropriate to make a choice regardless of the object of interest and the working conditions.