Fitting Volume Models for Parana Pine With a Nonlinear Regression, Genetic Algorithm and Simulated Annealing

Improving volumetric quantification of Parana pine (Araucaria angustifolia) in Mixed Ombrophilous Forest is a constant need in order to provide accurate and timely information on current and future growing stock to ensure forest management. Thus, the present study aimed to evaluate and compare the volume estimates obtained through Nonlinear Regression (NR), Genetic Algorithm (GA) and Simulated Annealing (SA) in order to generate accurate volume estimates. Volumetric equations were developed including the independent variables diameter at breast height (dbh), total height (h) and crown rate (cr) and from the fit through the NR, GA and SA approaches. The GA and SA approaches evaluated proved to be a reliable optimization strategy for parameter estimation in Parana pine volumetric modelling, however, no significant differences were found in comparison with the NR approach. This study therefore contributes through the generation of robust equations that could be used for accurate estimates of the volume of the Parana pine in southern Brazil, thus supporting the planning and establishment of management and conservation actions.

CT for estimating adequacy of lymph node dissection in patients with squamous cell carcinoma of the head and neck

Background Indices obtained from lymph node dissection specimens, specifically lymph node yield (LNY) and lymph node ratio (LNR), have prognostic significance in the setting of head and neck squamous cell carcinoma (HNSCCa). However, there are currently no validated tools to estimate adequacy of planned lymph node dissection using preoperative data. The present study sought to evaluate CT-derived estimates of lymphatic tissue volumes as a preoperative tool to guide cervical node dissection. Methods Fifteen cervical lymph node dissections were performed in 14 subjects with HNSCCa. Preoperative CT-derived estimates of lymphatic tissue volumes were compared with gross pathology tissue volume estimates and pathologically-determined LNY. Results Resected tissue volume (calculated using the triaxial ellipsoid method) correlates with CT-derived preoperative lymphatic volume estimates (r = 0.74, p = 0.003) while LNY does not(r = − 0.12, p = 0.67). When excluding pathologically enlarged lymph nodes (“refined” data), a negative correlation was observed between refined CT-derived volume estimates and refined LNY (r = − 0.65, p = 0.009). Conclusion In the setting of cervical lymph node dissection, CT-derived lymphatic volume estimates correlate with resected tissue volume, but refined CT-derived volume estimates correlate negatively with refined LNY. Trial registration Retrospectively registered. Level of evidence 4

Spatially Covarying Patterns of Gray Matter Volume and Concentration Highlight Distinct Regions in Schizophrenia

Introduction: Individuals with schizophrenia have consistent gray matter reduction throughout the cortex when compared to healthy individuals. However, the reduction patterns vary based on the quantity (concentration or volume) utilized by study. The objective of this study was to identify commonalities between gray matter concentration and gray matter volume effects in schizophrenia.Methods: We performed both univariate and multivariate analyses of case/control effects on 145 gray matter images from 66 participants with schizophrenia and 79 healthy controls, and processed to compare the concentration and volume estimates.Results: Diagnosis effects in the univariate analysis showed similar areas of volume and concentration reductions in the insula, occipitotemporal gyrus, temporopolar area, and fusiform gyrus. In the multivariate analysis, healthy controls had greater gray matter volume and concentration additionally in the superior temporal gyrus, prefrontal cortex, cerebellum, calcarine, and thalamus. In the univariate analyses there was moderate overlap between gray matter concentration and volume across the entire cortex (r = 0.56, p = 0.02). The multivariate analyses revealed only low overlap across most brain patterns, with the largest correlation (r = 0.37) found in the cerebellum and vermis.Conclusions: Individuals with schizophrenia showed reduced gray matter volume and concentration in previously identified areas of the prefrontal cortex, cerebellum, and thalamus. However, there were only moderate correlations across the cortex when examining the different gray matter quantities. Although these two quantities are related, concentration and volume do not show identical results, and therefore, should not be used interchangeably in the literature.

WOOD VOLUMETRY OF Tachigali vulgaris PURE PLANTATIONS IN DIFFERENT PLANTING SPACINGS

The aim of this study was to develop volumetric equations for tachi-branco trees (Tachigali vulgaris L. G. Silva & H. C. Lima), by assessing the effect of initial planting spacing in volume estimates, as well as developing an equation to estimate the equivalent diameter (deq). Data are from an experiment located in north Pará. The experiment was conducted with the randomized blocks design, being three blocks with six treatments each. The most used volumetric models were assessed for two distinct situations: considering each trunk as a tree and using the tree deq as independent variables in the volumetric model. The need for individual equations for initial planting spacing was tested. In addition, an equation for deq estimate was proposed. The use of deq provided more precise and accurate volumetric estimates regarding diameter at breast height. Among the models tested, the Schumacher-Hall model was selected. Through the model identity test, the equation can be used to estimate tree volume of Tachigali vulgaris, regardless of planting spacing. The equivalent diameter can be estimated via equation from minimum and maximum diameters of tree trunks. The maximum percentage differences of volume by hectare obtained with the measurement of all trunks and deq were only 5% without loss in production accuracy per unit of area

Comparative analysis of SRTM, TanDEM-X and UAV-SfM DEMs to estimate lavaka (gully) volumes and mobilization rates in the Lake Alaotra region (Madagascar)

Over the past decades, developments in remote sensing have resulted in an ever growing availability of topographic information on a global scale. A recent development is TanDEM-X, an interferometric SAR mission of the Deutsche Zentrum für Luft- und Raumfahrt providing near-global coverage and high resolution DEMs. Moreover, ongoing developments in unmanned aerial vehicle (UAV) technology has enabled acquisitions of topographic information at a sub-meter resolution. Although UAV products are generally preferred for volume assessments of geomorphic features, their acquisition remains time-consuming and is spatially constrained. However, some applications in geomorphology such as the estimation of regional or national erosion quantities of specific landforms, require data over large areas. TanDEM-X data can be applied at such scales, but this raises the question of how much accuracy is lost because of the lower spatial resolution. Here, we evaluated the performance of the 12 m TanDEM-X DEM to i) estimate gully volumes, ii) establish an area-volume (A-V) relationship, and iii) determine mobilization rates, through comparison with a high resolution (0.2 m) UAV-SfM DEM and lower resolution (30 m) SRTM DEM. We did this for six study areas in the Lake Alaotra region (central Madagascar) where lavaka (gullies) are omnipresent and lavaka surface area changes over the period 1949–2010s are available for 699 lavaka. SRTM derived lavaka volume estimates were systematically too low, indicating that the SRTM DEM is too coarse to accurately estimate volumes of geomorphic features at the lavaka-scale (100–100 000 m2). Lavaka volumes obtained from TanDEM-X were similar to UAV-SfM volumes for the largest features, whereas the volumes of smaller features were generally underestimated. To deal with this bias we introduce a breakpoint analysis to eliminate volume reconstructions that suffer from processing errors as evidenced by significant fractions of negative volumes. This elimination allowed the establishment of an area-volume relationship for the TanDEM-X data that is within the 95 % confidence interval of the UAV-SfM A-V relationship. Our calibrated area-volume relationship enabled us to obtain large-scale lavaka mobilization rates ranging between 18 ± 6 and 289 ± 125 ton ha−1 yr−1 with an average of 102 ± 41 ton ha−1 yr−1. These results indicate that current lavaka mobilization rates are two orders of magnitude higher than long-term erosion rates. With this study we demonstrate that the global TanDEM-X 12 m DEM can be used to accurately estimate volumes of gully-shaped features at the lavaka-scale (100–100 000 m2), where the proposed breakpoint-method can be applied without requiring the availability of a higher resolution DEM. Furthermore, we use this information to make a first assessment of regional lavaka erosion rates in the central highlands of Madagascar.

Sampling with probability proportional to prediction (3P sampling) using covariates derived from spherical images

Using a two-phase sampling approach with systematic selection of large samples of covariates followed by a sampling with probability proportional to prediction (3P sampling) process to subsample field measures of the parameters of interest can be an efficient design to sample larger forest areas. To assist in obtaining predictions for each sample plot consistently and rapidly, we propose using a 360° spherical camera. In this study, three covariates derived from spherical images were evaluated: (i) basal area (P[BA]); (ii) sum of squared heights per hectare (P[SHT]); and (iii) stem fraction (P[SF]). These covariates were used to estimate volume. Sample simulations showed no biases in volume estimates for any of the three covariates. Overall, P[SF] had the lowest standard error percentages across different simulated sample sizes (10% for five subsamples to 2.5% for 50 subsamples), even though it had the lowest correlations with field volume (correlation = 0.30–0.31). This may be a result of the relatively consistent stand conditions within the study site. Based on our results, standard errors of 5% were obtainable with measurement fractions of about 25% of the number of image-based predictions when using P[SF] or P[BA] and 75% when using P[SHT].