Do People Make the Place?: An Examination of the Attraction-Selection-Attrition Hypothesis

This study tests the hypotheses that (1) congruence between internal need states and external environments drives the organizational-choice process, and (2) those attracted to particular organizations are more homogeneous than the applicant pool in general. Subjects were evaluated on fourteen needs using the Jackson Personality Research Form. They then viewed two video-taped segments of simulated campus interviews to gain information about two distinct organizational types. The interview segments entered the discussion in-progress to avoid any reference to a particular job which might introduce an occupational confound. Subjects received job offers from both organizations and were asked to indicate which of the two organizations they found more attractive by accepting one of the offers. Analysis of variance results indicated only weak support for the congruency hypothesis. Differences were observed in n Ach between the groups of subjects attracted to each organization. No differences were found for any of the other need strength measures. This suggests that the subjects attracted to the ifferent organizations are substantially similar. Implications for the homogeneity hypothesis are discussed and suggestions for further study of this concept are offered

Towards Automatic SAR-Optical Stereogrammetry over Urban Areas using Very High Resolution Imagery

In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do this mainly from a geometrical point of view, we first analyze the height reconstruction accuracy to be expected for different stereogrammetric configurations. Then, we propose a strategy for simultaneous tie point matching and 3D reconstruction, which exploits an epipolar-like search window constraint. To drive the matching and ensure some robustness, we combine different established handcrafted similarity measures. For the experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR imagery is generally feasible with 3D positioning accuracies in the meter-domain, although the matching of these strongly hetereogeneous multi-sensor data remains very challenging. Keywords: Synthetic Aperture Radar (SAR), optical images, remote sensing, data fusion, stereogrammetr

Robust Feature Matching Method for SAR and Optical Images by Using Gaussian-Gamma-Shaped Bi-Windows-Based Descriptor and Geometric Constraint

Improving the matching reliability of multi-sensor imagery is one of the most challenging issues in recent years, particularly for synthetic aperture radar (SAR) and optical images. It is difficult to deal with the noise influence, geometric distortions, and nonlinear radiometric difference between SAR and optical images. In this paper, a method for SAR and optical images matching is proposed. First, interest points that are robust to speckle noise in SAR images are detected by improving the original phase-congruency-based detector. Second, feature descriptors are constructed for all interest points by combining a new Gaussian-Gamma-shaped bi-windows-based gradient operator and the histogram of oriented gradient pattern. Third, descriptor similarity and geometrical relationship are combined to constrain the matching processing. Finally, an approach based on global and local constraints is proposed to eliminate outliers. In the experiments, SAR images including COSMO-Skymed, RADARSAT-2, TerraSAR-X and HJ-1C images, and optical images including ZY-3 and Google Earth images are used to evaluate the performance of the proposed method. The experimental results demonstrate that the proposed method provides significant improvements in the number of correct matches and matching precision compared with the state-of-the-art SIFT-like methods. Near 1 pixel registration accuracy is obtained based on the matching results of the proposed method