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Home PE&RS Journals In Press Peer Reviewed Articles

PE&RS Journals

In Press Peer Reviewed Articles

As a convenience to ASPRS members, in-press peer reviewed articles approved for publication in forthcoming issues of PE&RS have been made available for members of the society.

March 2015 Issue

Spectroscopic Analysis of Green, Desiccated and Dead Tamarisk Canopies

Ran Meng and Philip E. Dennison

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Defoliation by the northern tamarisk beetle (Diorhabda carinulata) causes changes in the reflectance of tamarisk (Tamarix spp.) canopies. Cross correlogram spectral matching was used to examine spectral separability of green, yellow desiccated, brown desiccated, and dead tamarisk canopy types. Using a feature selection technique (the instability index), four spectral regions were identified as important for canopy type discrimination, including one red (645-693 nm), one near infrared (735-946 nm), and two shortwave infrared regions (1,960-2,090 nm and 2,400-2,478 nm). The random forests decision tree algorithm was used to compare classification performances of full-range and feature-selected hyperspectral spectra as well as simulated WorldView-2 spectra. Classification results indicated that the process of feature selection can reduce data redundancy and computation time while improving accuracy of tamarisk canopy type classification.


Quaternion-Based Solutions for the Single Photo Resection Problem

Mehdi Mazaheri and Ayman Habib

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This paper introduces three quaternion-based approaches to solve the SPR problem. The first two are based on projective transformation and DLT coefficients through which the position of the perspective center is derived first using four or more planar and six or more non-planar object points, respectively. The rotation matrix is then directly estimated using quaternions. The third one (quaternion-based general approach) can handle three or more points in either planar or non-planar configuration. In this approach, the rotation angles are iteratively estimated first using quaternions without the need for user-defined approximations. Then, the position of the perspective center is directly derived. Experimental results show the feasibility of the proposed approaches and the high accuracy of the quaternion-based general approach, which is superior to the state-of-the-art non-iterative method and does not deviate more than 1 percent from the traditional non-linear SPR, i.e., the de-facto standard for the most accurate SPR solution.


Accuracy Analysis of a Dual Camera System with an Asymmetric Photogrammetric Configuration

Bo Wu, Lei Ye, and Yuansheng Yang

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This paper presents a dual camera system combining a wide field-of-view (FOV) surveillance camera and a pan-tilt-zoom (PTZ) camera with an asymmetric photogrammetric configuration, and focuses on the analysis of its attainable measurement accuracy. First, we discuss the geometric modeling of the asymmetric photogrammetric configuration and analyze the accuracy of measurement based on error propagation for different baseline lengths, different focal lengths, and different pan angles of the PTZ camera. Second, we performed a comprehensive accuracy analysis based on Monte Carlo simulation, which incorporated artificial noise into the input data. Third, we conducted actual experiments in indoor and outdoor environments to verify the theoretical and simulation results. We found that the baseline length between the dual cameras was the main factor influencing measurement accuracy. Increase of the PTZ camera focal length could improve the measurement accuracy, but this trend was not significant when its focal length was relatively long. The pan angle of the PTZ camera also influenced the measurement accuracy, but this influence was not significant at short ranges. From these discoveries, we present an optimum configuration of the dual camera system for better than 1 percent measurement accuracy of the range within a normal observation range (e.g., 60 m). This proposed dual camera system provides enhanced machine vision capabilities that can be used in various applications.


Mapping Irrigated Farmlands Using Vegetation and Thermal Thresholds Derived from Landsat and ASTER Data in an Irrigation District of Australia

Mohammad Abuzar, Andy McAllister, and Des Whitfield

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An operational approach has been presented to demonstrate how bilevel classes of satellite-derived surface temperature and vegetation status can be jointly used to detect areas of current irrigation with sufficient spatial detail for the potential benefit of both growers and resource managers. An iterative thresholding procedure to minimize within-class variance was used for bilevel segmentation. The approach was tested in an irrigation district of south-eastern Australia in 2012/2013 crop year. The overall accuracy of identifying farms with irrigated crops amounted to 88.4 percent. Seasonal data of active irrigation and growing vegetation helped define land cover classes for the better understanding of current management practices of irrigated crops.


Small Landslide Susceptibility and Hazard Assessment Based on Airborne Lidar Data

Omar E. Mora, Jung-kuan Liu, M. Gabriela Lenzano, Charles K. Toth, and Dorota A. Grejner-Brzezinska

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Landslides are natural disasters that cause environmental and infrastructure damage worldwide. To prevent future risk posed by such events, effective methods to detect and map their hazards are needed. Traditional landslide susceptibility mapping techniques, based on field inspection, aerial photograph interpretation, and contour map analysis are often subjective, tedious, difficult to implement, and may not have the spatial resolution and temporal frequency necessary to map small slides, which is the focus of this investigation. We present a methodology that is based on a Support Vector Machine (SVM) that utilizes a lidar-derived Digital Elevation Model (DEM) to quantify and map the topographic signatures of landslides. The algorithm employs several geomorphological features to calibrate the model and delineate between landslide and stable terrain. To evaluate the performance of the proposed algorithm, a road corridor in Zanesville, Ohio, was used for testing. The resulting landslide susceptibility map was validated to correctly identify 67 of the 80 mapped landslides in the independently compiled landslide inventory map of the area. These results suggest that the proposed landslide surface feature extraction method and airborne lidar data can be used as efficient tools for small landslide susceptibility and hazard mapping.


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