Measuring Forest Canopy Height Using a Combination of LIDAR and Aerial Photography Data

It has been demonstrated that the height of forest canopies can be measured with a good accuracy using small footprint lidars. This is essentially accomplished by subtracting the last return altitude (ground) from the corresponding first return altitude (canopy surface). The technique is considered superior to photogrammetric methods mainly because the ground level, which is difficult to see on aerial photos of densely forested areas, can be well identified using small footprint lidars. However, lidar cannot be used to characterized past forest states, while these can be assessed, and photogrammetically measured, in the wealth of historical aerial photographs most developed countries possess. Our goal is to replace the first return lidar data by altitude models derived from aerial photos in order to map forest canopy height changes of the past decades. This paper presents the first methodological steps which consist in comparing canopy heights obtained from lidar data only to a combination of lidar and photogrammetry data. The lidar data was acquired over an area of the boreal forest in Quebec, Canada, in 1998, using Optech’s ALTM1020 flying at an altitude of 700 m. Two stereo-pairs of aerial black and white photographs were used: 1) a pair of 1:15,000 photos taken in 1994, and 2) a pair of 1:40,000 photos taken in 1998. A lidar canopy height model (CHM) was created by subtracting ground altitudes from canopy altitudes. Aerial photo altitude models were derived using the image correlation methods of Virtuozo 3.2 software. The ground level altitudinal fit between the aerial photo altitude model and the lidar data was checked on rock outcrops. A photo CHM was created by subtracting the lidar ground altitude model from the aerial photo altitude model. The photo CHM and the lidar CHM show a good degree of correlation

A reappraisal of the impact of dairy foods and milk fat on cardiovascular disease risk

Background This review provides a reappraisal of the potential effects of dairy foods, including dairy fats, on cardiovascular disease (CVD)/coronary heart disease (CHD) risk. Commodities and foods containing saturated fats are of particular focus as current public dietary recommendations are directed toward reducing the intake of saturated fats as a means to improve the overall health of the population. A conference of scientists from different perspectives of dietary fat and health was convened in order to consider the scientific basis for these recommendations. Aims This review and summary of the conference focus on four key areas related to the biology of dairy foods and fats and their potential impact on human health: (a) the effect of dairy foods on CVD in prospective cohort studies; (b) the impact of dairy fat on plasma lipid risk factors for CVD; (c) the effects of dairy fat on non-lipid risk factors for CVD; and (d) the role of dairy products as essential contributors of micronutrients in reference food patterns for the elderly. Conclusions Despite the contribution of dairy products to the saturated fatty acid composition of the diet, and given the diversity of dairy foods of widely differing composition, there is no clear evidence that dairy food consumption is consistently associated with a higher risk of CVD. Thus, recommendations to reduce dairy food consumption irrespective of the nature of the dairy product should be made with cautionJ. Bruce German, Robert A. Gibson, Ronald M. Krauss, Paul Nestel, Benoît Lamarche, Wija A. van Staveren, Jan M. Steijns, Lisette C. P. G. M. de Groot, Adam L. Lock and Frédéric Destaillat

Effects of Viewing Geometry on Multispectral Lidar-Based Needle-Leaved Tree Species Identification

Identifying tree species with remote sensing techniques, such as lidar, can improve forest management decision-making, but differences in scan angle may influence classification accuracy. The multispectral Titan lidar (Teledyne Optech Inc., Vaughan, ON, Canada) has three integrated lasers with different wavelengths (1550, 1064 and 532 nm), and with different scan angle planes (respectively tilted at 3.5°, 0° and 7° relative to a vertical plane). The use of multispectral lidar improved tree species separation, compared to mono-spectral lidar, by providing classification features that were computed from intensities in each channel, or from pairs of channels as ratios and normalized indices (NDVIs). The objective of the present study was to evaluate whether scan angle (up to 20°) influences 3D and intensity feature values and if this influence affected species classification accuracy. In Ontario (Canada), six needle-leaf species were sampled to train classifiers with different feature selection. We found the correlation between feature values and scan angle to be poor (mainly below |±0.2|), which led to changes in tree species classification accuracy of 1% (all features) and 8% (3D features only). Intensity normalization for range improved accuracies by 8% for classifications using only single-channel intensities, and 2–4% when features that were unaffected by normalization were added, such as 3D features or NDVIs

Effect of variability of normalized differences calculated from multi-spectral lidar on individual tree species identification

1041881903National Sciences and Engineering Research Council of Canad

A Comparison of Three Airborne Laser Scanner Types for Species Identification of Individual Trees

Species identification is a critical factor for obtaining accurate forest inventories. This paper compares the same method of tree species identification (at the individual crown level) across three different types of airborne laser scanning systems (ALS): two linear lidar systems (monospectral and multispectral) and one single-photon lidar (SPL) system to ascertain whether current individual tree crown (ITC) species classification methods are applicable across all sensors. SPL is a new type of sensor that promises comparable point densities from higher flight altitudes, thereby increasing lidar coverage. Initial results indicate that the methods are indeed applicable across all of the three sensor types with broadly similar overall accuracies (Hardwood/Softwood, 83–90%; 12 species, 46–54%; 4 species, 68–79%), with SPL being slightly lower in all cases. The additional intensity features that are provided by multispectral ALS appear to be more beneficial to overall accuracy than the higher point density of SPL. We also demonstrate the potential contribution of lidar time-series data in improving classification accuracy (Hardwood/Softwood, 91%; 12 species, 58%; 4 species, 84%). Possible causes for lower SPL accuracy are (a) differences in the nature of the intensity features and (b) differences in first and second return distributions between the two linear systems and SPL. We also show that segmentation (and field-identified training crowns deriving from segmentation) that is performed on an initial dataset can be used on subsequent datasets with similar overall accuracy. To our knowledge, this is the first study to compare these three types of ALS systems for species identification at the individual tree level

A mutation that creates a pseudoexon in SOD1 causes familial ALS.

International audienceAmyotrophic lateral sclerosis (ALS) is an adult onset neurodegenerative disease which targets motor neurons of the cortex, brainstem and spinal cord. About 5-10% of all amyotrophic lateral sclerosis cases are familial (FALS), and 15-20% of FALS cases are caused by mutations in the zinc-copper superoxide dismutase gene (SOD1). We identified a large family from France with ten members affected with ALS. Linkage was established to the SOD1 locus on chromosome 21 and genomic and cDNA sequencing was performed for the SOD1 gene. This revealed an activated pseudoexon between exons 4 and 5 that was present in two tested members of the family. Translation of this 43 base pair exon results in the introduction of seven amino acids before a stop codon is present, leading to a prematurely truncated SOD1 protein product of 125 amino acids. Sequencing intron 4 in a patient revealed a eterozygous change 304 bp before exon 5 (c.358 - 304C > G), but only 5 bp after the cryptic exon, thus causing this alternative splice product. This mutation segregated in all affected individuals of the family. This adds an additional genetic mechanism for developing OD1-linked ALS and is one which can be more readily targeted by gene therapy

Author Correction: Postzygotic inactivating mutations of RHOA cause a mosaic neuroectodermal syndrome [Correction to: Nature Genetics https://doi.org/10.1038/s41588-019-0498-4, published online 30 September 2019]

Indexation en cours. In the version of this article initially published, support from the Wellcome Trust and NIHR to author Veronica A. Kinsler was not included in the Acknowledgements. The error has been corrected in the HTML and PDF versions of the article.International audienceAn amendment to this paper has been published and can be accessed via a link at the top of the paper

Postzygotic inactivating mutations of <em>RHOA</em> cause a mosaic neuroectodermal syndrome

International audienceHypopigmentation along Blaschko's lines is a hallmark of a poorly defined group of mosaic syndromes whose genetic causes are unknown. Here we show that postzygotic inactivating mutations of RHOA cause a neuroectodermal syndrome combining linear hypopigmentation, alopecia, apparently asymptomatic leukoencephalopathy, and facial, ocular, dental and acral anomalies. Our findings pave the way toward elucidating the etiology of pigmentary mosaicism and highlight the role of RHOA in human development and disease