Accuracy of a DTM derived from full-waveform laser scanning data under unstructured eucalypt forest: a case study

A Digital Terrain Model (DTM) is fundamental for extracting several forest canopy structure metrics from data acquired with small-footprint airborne laser scanning (ALS). This modern remote sensing technology is based on laser measurements from a laser system mounted on an aircraft and integrated with a geodetic GNSS receiver and an inertial measurement unit (IMU) or inertia navigation system (INS). In the context of a research project for deriving forest inventory parameters and fuel variables under eucalypt stands in Mediterranean climates, the vertical precision of the DTM obtained by automatic filtering of full-waveform ALS data had to be evaluated. The DTM accuracy estimation on a study area with peculiar characteristics, which are often avoided in related studies, will also allow verifying the performance of full- waveform ALS systems. The accuracy estimation is carried out in a novel way. By novel way, it is meant an exhaustive, well-planned collection of reliable control data in forest environment. The collection of the control data involves the production of DTM on 43 circular plots (radius = 11.28m) using total stations and geodetic GNSS receivers. These DTM, with a total of 3356 points, allowed one to evaluate consistently and reliably the vertical accuracy of the terrain surface produced with ALS under a eucalypt forest. This global accuracy, expressed by the Root Mean Square Error (RMSE) of the vertical differences between the field surveyed surface and the ALS derived DTM surface is 0.15m (mean=0.08m and std=0.09m). This impressive value indicates that, for an ALS point cloud density of 10pts/m2 and footprint of 20 cm, the methodology used to extract the DTM from full- waveform ALS data under an unstructured eucalypt forest is very accurate. In this article it is addressed both the strategy adopted to collect the control data and the quality assessment of the DTM produced by means of the ALS data

The influence of μ-opioid and noradrenaline reuptake inhibition in the modulation of pain responsive neurones in the central amygdala by tapentadol in rats with neuropathy

Treatments for neuropathic pain are either not fully effective or have problematic side effects. Combinations of drugs are often used. Tapentadol is a newer molecule that produces analgesia in various pain models through two inhibitory mechanisms, namely central μ-opioid receptor (MOR) agonism and noradrenaline reuptake inhibition. These two components interact synergistically, resulting in levels of analgesia similar to opioid analgesics such as oxycodone and morphine, but with more tolerable side effects. The right central nucleus of the amygdala (CeA) is critical for the lateral spinal ascending pain pathway, regulates descending pain pathways and is key in the emotional-affective components of pain. Few studies have investigated the pharmacology of limbic brain areas in pain models. Here we determined the actions of systemic tapentadol on right CeA neurones of animals with neuropathy and which component of tapentadol contributes to its effect. Neuronal responses to multimodal peripheral stimulation of animals with spinal nerve ligation or sham surgery were recorded before and after two doses of tapentadol. After the higher dose of tapentadol either naloxone or yohimbine were administered. Systemic tapentadol resulted in dose-dependent decrease in right CeA neuronal activity only in neuropathy. Both naloxone and yohimbine reversed this effect to an extent that was modality selective. The interactions of the components of tapentadol are not limited to the synergy between the MOR and α2-adrenoceptors seen at spinal levels, but are seen at this supraspinal site where suppression of responses may relate to the ability of the drug to alter affective components of pain