The german camera evaluation project - results from the geometry group

The so-called German camera evaluation project was initiated by the German society of Photogrammetry, Remote Sensing and Geoinformation (DGPF) in order to allow for comprehensive empirical test on photogrammetric digital airborne camera systems. During this test, the digital camera systems DMC, Ultracam-X, ADS40 (2nd generation), JAS-150, Quattro DigiCAM and AIC-x1 were flown in the test site Vaihingen/Enz in summer 2008. In addition, RMK analogue images and ALS50 LiDAR data were recorded for comparison, while reference measurements on the ground were made available as well. Parts of the test field were also covered from hyper-spectral sensor flights, namely the AISA+ and ROSIS system. After data collection all this material was prepared, documented and distributed to more than 30 institutions which participated in the evaluation and formed the project network of expertise. This evaluation phase included topics like the analysis of geometric accuracy and sensor calibration, the radiometric performance including on-site radiometric calibration and multi-spectral land classifications. Additionally, the performance of photogrammetric surface model generation and the potential of manual stereo plotting from digital images were investigated. Within this paper, the major findings from the geometric evaluations, namely sensor orientation and height model generation are presented

Color Coded: Party Politics in the American West, 1950-2016

Review of: Color Coded: Party Politics in the American West, 1950–2016, by Walter Nugent

Libyan women and revolution : a study of the changes in women\u27s political and social roles during and after the Libyan revolution

Several uprisings against some long-term dictatorships in the Arab region took place during the year of 2011. The phenomenon, commonly known as the Arab Spring, started in December 2010 in Tunisia, a small North African Arabic country that was going through tough economic times. The domino effect of the Tunisian revolution spread quickly through the region. Almost all Arab countries witnessed political unrest and protests demanding reforms, but in a few of them--- Egypt, Libya, Syria, and Yemen---the situation escalated to the level of popular revolution. The Arab Spring phenomenon opened the door for studies on collective behavior and revisiting social movements literature. However, most of the studies conducted on the Arab uprising events focus, for the most part, on the collective action of the Arab Spring societies as a whole. Moreover, the scholarly work on the early stages of the uprisings focused largely on the military role in the unfolding events and the role played by social media. In this research study, however, I examine the phenomenon from a different perspective. I focus on the role of a particular agent in the society by analyzing women\u27s political and civic involvement in Libya, one of the Arab Spring countries, during the revolution against the dictatorship regime of Mu\u27ammar Gaddafi in 2011. Libyan women played a significant role in initiating the uprising and throughout the events of the revolution. Furthermore, my research highlights the ongoing dynamics and challenges Libyan women to maintain the gains they made through their participation in the revolution. This analysis is placed in the context of the social movement theory literature, as it provides a much-needed study of women\u27s political and civic involvement in contemporary Libya

A Novel Methodology to Estimate Single-Tree Biophysical Parameters from 3D Digital Imagery Compared to Aerial Laser Scanner Data

Airborne laser scanner (ALS) data provide an enhanced capability to remotely map two key variables in forestry: leaf area index (LAI) and tree height (H). Nevertheless, the cost, complexity and accessibility of this technology are not yet suited for meeting the broad demands required for estimating and frequently updating forest data. Here we demonstrate the capability of alternative solutions based on the use of low-cost color infrared (CIR) cameras to estimate tree-level parameters, providing a cost-effective solution for forest inventories. ALS data were acquired with a Leica ALS60 laser scanner and digital aerial imagery (DAI) was acquired with a consumer-grade camera modified for color infrared detection and synchronized with a GPS unit. In this paper we evaluate the generation of a DAI-based canopy height model (CHM) from imagery obtained with low-cost CIR cameras using structure from motion (SfM) and spatial interpolation methods in the context of a complex canopy, as in forestry. Metrics were calculated from the DAI-based CHM and the DAI-based Normalized Difference Vegetation Index (NDVI) for the estimation of tree height and LAI, respectively. Results were compared with the models estimated from ALS point cloud metrics. Field measurements of tree height and effective leaf area index (LAIe) were acquired from a total of 200 and 26 trees, respectively. Comparable accuracies were obtained in the tree height and LAI estimations using ALS and DAI data independently. Tree height estimated from DAI-based metrics (Percentile 90 (P90) and minimum height (MinH)) yielded a coefficient of determination (R2) = 0.71 and a root mean square error (RMSE) = 0.71 m while models derived from ALS-based metrics (P90) yielded an R2 = 0.80 and an RMSE = 0.55 m. The estimation of LAI from DAI-based NDVI using Percentile 99 (P99) yielded an R2 = 0.62 and an RMSE = 0.17 m2/m−2. A comparative analysis of LAI estimation using ALS-based metrics (laser penetration index (LPI), interquartile distance (IQ), and Percentile 30 (P30)) yielded an R2 = 0.75 and an RMSE = 0.14 m2/m−2. The results provide insight on the appropriateness of using cost-effective 3D photo-reconstruction methods for targeting single trees with irregular and heterogeneous tree crowns in complex open-canopy forests. It quantitatively demonstrates that low-cost CIR cameras can be used to estimate both single-tree height and LAI in forest inventories

DMSA -- Dense Multi Scan Adjustment for LiDAR Inertial Odometry and Global Optimization

We propose a new method for fine registering multiple point clouds simultaneously. The approach is characterized by being dense, therefore point clouds are not reduced to pre-selected features in advance. Furthermore, the approach is robust against small overlaps and dynamic objects, since no direct correspondences are assumed between point clouds. Instead, all points are merged into a global point cloud, whose scattering is then iteratively reduced. This is achieved by dividing the global point cloud into uniform grid cells whose contents are subsequently modeled by normal distributions. We show that the proposed approach can be used in a sliding window continuous trajectory optimization combined with IMU measurements to obtain a highly accurate and robust LiDAR inertial odometry estimation. Furthermore, we show that the proposed approach is also suitable for large scale keyframe optimization to increase accuracy. We provide the source code and some experimental data on https://github.com/davidskdds/DMSA_LiDAR_SLAM.git.Comment: accepted for ICRA 202

Preface: Workshop “Semantics3D - Semantic Scene Analysis and 3D Reconstruction from Images and Image Sequences”

[no abstract available

Preface: Workshop “Semantics3D - Semantic Scene Analysis and 3D Reconstruction from Images and Image Sequences”

[no abstract available