Inversions of landslide strength as a proxy for subsurface weathering.

Distributions of landslide size are hypothesized to reflect hillslope strength, and consequently weathering patterns. However, the association of weathering and critical zone architecture with mechanical strength properties of parent rock and soil are poorly-constrained. Here we use three-dimensional stability to analyze 7330 landslides in western Oregon to infer combinations of strength - friction angles and cohesion - through analysis of both failed and reconstructed landslide terrain. Under a range of conditions, our results demonstrate that the failure envelope that relates shear strength and normal stress in landslide terrain is nonlinear owing to an exchange in strength with landslide thickness. Despite the variability in material strength at large scales, the observed gradient in proportional cohesive strength with landslide thickness may serve as a proxy for subsurface weathering. We posit that the observed relationships between strength and landslide thickness are associated with the coalescence of zones of low shear strength driven by fractures and weathering, which constitutes a first-order control on the mechanical behavior of underlying soil and rock mass.

Object Recognition, Segmentation, and Classification of Mobile Laser Scanning Point Clouds: A State of the Art Review.

Mobile Laser Scanning (MLS) is a versatile remote sensing technology based on Light Detection and Ranging (lidar) technology that has been utilized for a wide range of applications. Several previous reviews focused on applications or characteristics of these systems exist in the literature, however, reviews of the many innovative data processing strategies described in the literature have not been conducted in sufficient depth. To this end, we review and summarize the state of the art for MLS data processing approaches, including feature extraction, segmentation, object recognition, and classification. In this review, we first discuss the impact of the scene type to the development of an MLS data processing method. Then, where appropriate, we describe relevant generalized algorithms for feature extraction and segmentation that are applicable to and implemented in many processing approaches. The methods for object recognition and point cloud classification are further reviewed including both the general concepts as well as technical details. In addition, available benchmark datasets for object recognition and classification are summarized. Further, the current limitations and challenges that a significant portion of point cloud processing techniques face are discussed. This review concludes with our future outlook of the trends and opportunities of MLS data processing algorithms and applications.

A Review of LIDAR Radiometric Processing: From Ad Hoc Intensity Correction to Rigorous Radiometric Calibration.

In addition to precise 3D coordinates, most light detection and ranging (LIDAR) systems also record "intensity", loosely defined as the strength of the backscattered echo for each measured point. To date, LIDAR intensity data have proven beneficial in a wide range of applications because they are related to surface parameters, such as reflectance. While numerous procedures have been introduced in the scientific literature, and even commercial software, to enhance the utility of intensity data through a variety of "normalization", "correction", or "calibration" techniques, the current situation is complicated by a lack of standardization, as well as confusing, inconsistent use of terminology. In this paper, we first provide an overview of basic principles of LIDAR intensity measurements and applications utilizing intensity information from terrestrial, airborne topographic, and airborne bathymetric LIDAR. Next, we review effective parameters on intensity measurements, basic theory, and current intensity processing methods. We define terminology adopted from the most commonly-used conventions based on a review of current literature. Finally, we identify topics in need of further research. Ultimately, the presented information helps lay the foundation for future standards and specifications for LIDAR radiometric calibration.

Whole genome analysis of the Epiphyas postvittana nucleopolyhedrovirus.

The nucleotide sequence of the Epiphyas postvittana nucleopolyhedrovirus (EppoMNPV) genome has been determined and analysed. The circular dsDNA genome contains 118584 bp, making it the smallest group I NPV sequenced to date. The genome has a G+C content of 40.7% and encodes 136 predicted open reading frames (ORFs), five homologous repeat regions and one unique repeat region. Of the genome, 92.9% encodes predicted ORFs and 2.2% is in repeat regions; the remaining 4.9% of the genome comprises nonrepeat intergenic regions. EppoMNPV encodes homologues of 126 Orgyia pseudotsugata MNPV (OpMNPV) ORFs and 120 Autographa californica MNPV ORFs, with average identities of 64.7 and 53.5%, respectively. Between the four sequenced group I NPVs, 117 ORFs are conserved, whereas 86 ORFs are conserved between all fully sequenced NPVs. A total of 62 ORFs is present in all baculoviruses sequenced to date, with EppoMNPV lacking a homologue of the superoxide dismutase (sod) gene, which has been found in all other fully sequenced baculoviruses. Whole genome phylogenetic analyses of the ten fully sequenced baculoviruses using the sequences of the 62 shared genes, gene content and gene order data sets confirmed that EppoMNPV clusters tightly with OpMNPV in the group I NPVs. The main variation between EppoMNPV and OpMNPV occurs where extra clusters of genes are present in OpMNPV, with sod occurring in one such cluster. EppoMNPV encodes one truncated baculovirus repeated ORF (bro) gene. The only repeated ORFs are the four iap genes. Eight, randomly distributed, unique ORFs were identified on EppoMNPV, none of which show any significant homology to genes in GenBank.