Using hipersepctral images for decay detection in Pinus halepensis (Mill.) in the Mediterranean forest

[ES] El incremento de los efectos negativos del cambio climático y la aparición de especies invasoras en los bosques de todo el mundo requieren el desarrollo de métodos innovadores para monitorear y medir cuantitativamente el estado de salud de las masas arboladas. Estos efectos son especialmente notables en el área mediterránea, donde el decaimiento de las masas por sequías recurrentes ha incrementado los daños por plagas secundarias cuyas poblaciones, de otro modo, estarían en equilibrio. Las tecnologías de teledetección nos permiten afrontar trabajos en grandes superficies con una precisión razonable. En particular, se ha demostrado que nuevos índices espectrales obtenidos a partir de imágenes hiperespectrales y térmicas de alta resolución son buenos predictores para la detección temprana de cambios fisiológicos relacionados con enfermedades. En este estudio piloto desarrollado en una masa de Pinus halepensis en la Comunitat Valenciana, se lleva a cabo una simulación controlada de decaimiento por medio del anillado secuencial de árboles, haciendo un posterior seguimiento en campo del decaimiento que provoca. La captura de imágenes hiperespectrales de alta resolución ha permitido analizar la relación entre la información espectral en cada uno de los árboles anillados con su decoloración y estado de decaimiento observado. La metodología propuesta permite la detección de árboles afectados con tres meses de antelación a la aparición de síntomas visuales, clasificándolos con un nivel de acierto superior a 0,9 con los clasificadores Random Forest y Support Vector Machine. Los índices que generaron mejores resultados fueron PRI, VOG1, VOG2, GM1 y OSAVI. Este estudio piloto permite pensar que algunos de estos índices puedan ser utilizados en la detección temprana de marchitamientos generales de los pinares y, por tanto, tengan aplicación en la monitorización de las principales amenazas de los bosques europeos, las plagas de perforadores o los organismos de cuarentena como Bursaphelenchus xylophilus.[EN] The increasing negative effects of climate change and the emergence of invasive species in forests around the world require the development of innovative methods to monitor and quantitatively measure the health status of woodlands. These effects are especially notable in the Mediterranean area, where the decline of stands due to recurrent droughts has increased the damage caused by secondary pests whose populations would otherwise be in balance. Remote sensing technologies allow us to work on large surfaces with reasonable precision. In particular, new spectral indices obtained from high-resolution hyperspectral and thermal images have been shown to be good predictors for the early detection of physiological changes related to diseases. In this pilot study developed in a stand of Pinus halepensis in the Comunitat Valenciana, a controlled simulation of a decay is carried out by means of sequential girdling of trees, making a subsequent field monitoring of the caused decay. Through a hyperspectral camera, the spectral information of each of these trees is analyzed in relation to their discoloration and state of observed decay. The proposed methodology allows the detection of affected trees three months before the appearance of visual symptoms, obtaining a precision higher than 0.9 with Random Forest and Support Vector Machine classifiers. The vegetation indices with better results were PRI, VGO1, VGO2, GM1 and OSAVI. This pilot study allows us to think that some of these indices can be used in the early detection of general pine wilt and, therefore, have application in the monitoring of the main threats to European forests, borer pests or quarantine organisms such as Bursaphelenchus xylophilus.Guillen-Climent, ML.; Mas, H.; Fernández-Landa, A.; Algeet-Abarquero, N.; Tomé, JL. (2020). Uso de imágenes hiperespectrales para la predicción del marchitamiento de Pinus halepensis (Mill.) en el bosque mediterráneo. Revista de Teledetección. 0(55):59-69. https://doi.org/10.4995/raet.2020.13289OJS596905

Rapid Coverage of Regions of Interest for Environmental Monitoring

We present a framework for rapidly determining regions of interest (ROIs) from an unknown intensity distribution, particularly in radiation fields. The vast majority of studies on area coverage path planning for mobile robots do not investigate the identification of ROIs. In a radiation field, the use of ROIs can limit the required range of exploration and mitigate the monitoring problem. However, considering that an unmanned aerial vehicle (UAV) has limited resources as a mobile measurement system, it is challenging to determine ROIs in unknown radiation fields. Given a target area, we attempt to plan a path that facilitates the localization of ROIs with a single UAV while minimizing the exploration cost. To reduce the complexity of a large-scale environment exploration, entire areas are initially adaptively decomposed using two hierarchical methods based on recursive quadratic subdivision and Voronoi-based subdivision. Once an informative decomposed subarea is selected by maximizing a utility function, the robot heuristically reaches contaminated areas, and a boundary estimation algorithm is adopted to estimate the environmental boundaries. The properties of this boundary estimation algorithm are theoretically analyzed in this paper. Finally, the detailed boundaries of the ROIs of the target area are approximated by ellipses, and a set of procedures are iterated to sequentially cover all areas. The simulation results demonstrate that our framework allows a single UAV to efficiently explore a given target area and maximize the localization rate for ROIs

Significant dose reduction is feasible in FDG PET/CT protocols without compromising diagnostic quality

Purpose: To reduce the radiation dose to patients by optimizing oncological FDG PET/CT protocols. Methods: The baseline PET/CT protocol in our institution for oncological PET/CT examinations consisted of the administration of 5.18 MBq/kg of FDG and a CT acquisition with a reference current-time product of 120 mAs. In 2016, FDG activity was reduced to 4.44 and 3.70 MBq/kg and reference CT current-time-product was reduced to 100 and 80 mAs. 322 patients scanned with different protocols were retrospectively evaluated. For each patient, effective dose was calculated. The overall image quality was subjectively rated by the referring physician on a 4-point scale (IQ score: 1 excellent, 2 good, 3 poor but interpretable, 4 poor not interpretable). Image quality was quantitatively evaluated measuring noise in the liver. Results: CT Results: Effective dose was progressively reduced from 9.5 ± 2.8 to 8.0 ± 2.3 and 6.2 ± 1.5 mSv (p 2) did not increase. PET Results: Effective dose was gradually reduced from 6.5 ± 1.4 to 5.7 ± 1.3 and 5.0 ± 1.0 mSv (p < 0.001). Average dose reduction was 23.4%. IQ score (p < 0.05) and noise (p < 0.001) significantly degraded for lower activity protocols. However, all images with reduced activity were scored as interpretable (IQ score ≤ 3). Conclusions: A significant radiation dose reduction of 28.7% was reached. Despite a slight reduction in image quality, the new regime was successfully implemented with readers reporting unchanged clinical confidence

Mapping radiation interception in row-structured orchards using 3D simulation and high-resolution airborne imagery acquired from a UAV

This study was conducted to model the fraction of intercepted photosynthetically active radiation (fIPAR) in heterogeneous row-structured orchards, and to develop methodologies for accurate mapping of the instantaneous fIPAR at field scale using remote sensing imagery. The generation of high-resolution maps delineating the spatial variation of the radiation interception is critical for precision agriculture purposes such as adjusting management actions and harvesting in homogeneous within-field areas. Scaling-up and model inversion methods were investigated to estimate fIPAR using the 3D radiative transfer model, Forest Light Interaction Model (FLIGHT). The model was tested against airborne and field measurements of canopy reflectance and fIPAR acquired on two commercial peach and citrus orchards, where study plots showing a gradient in the canopy structure were selected. High-resolution airborne multi-spectral imagery was acquired at 10 nm bandwidth and 150 mm spatial resolution using a miniaturized multi-spectral camera on board an unmanned aerial vehicle (UAV). In addition, simulations of the land surface bidirectional reflectance were conducted to understand the relationships between canopy architecture and fIPAR. Input parameters used for the canopy model, such as the leaf and soil optical properties, canopy architecture, and sun geometry were studied in order to assess the effect of these inputs on canopy reflectance, vegetation indices and fIPAR. The 3D canopy model approach used to simulate the discontinuous row-tree canopies yielded spectral RMSE values below 0. 03 (visible region) and below 0. 05 (near-infrared) when compared against airborne canopy reflectance imagery acquired over the sites under study. The FLIGHT model assessment conducted for fIPAR estimation against field measurements yielded RMSE values below 0. 08. The simulations conducted suggested the usefulness of these modeling methods in heterogeneous row-structured orchards, and the high sensitivity of the normalized difference vegetation index and fIPAR to background, row orientation, percentage cover and sun geometry. Mapping fIPAR from high-resolution airborne imagery through scaling-up and model inversion methods conducted with the 3D model yielded RMSE error values below 0. 09 for the scaling-up approach, and below 0. 10 for the model inversion conducted with a look-up table. The generation of intercepted radiation maps in row-structured tree orchards is demonstrated to be feasible using a miniaturized multi-spectral camera on board UAV platforms for precision agriculture purposes. © 2012 Springer Science+Business Media, LLC.Financial support from the Spanish Ministry of Science and Innovation (MCI) for the projects AGL2009-13105, CONSOLIDER CSD2006-67, and AGL2003-01468 is gratefully acknowledged, as well as the Junta de Andalucía-Excelencia AGR-595 and FEDER. M.L. Guillén-Climent was supported by a grant JAE of CSIC, co-funded by the European Social Fund.Peer Reviewe

Heterozygous pathogenic variants in GLI1 are a common finding in isolated postaxial polydactyly A/B

Postaxial polydactyly (PAP) is a frequent limb malformation consisting in the duplication of the fifth digit of the hand or foot. Morphologically, this condition is divided into type A and B, with PAP-B corresponding to a more rudimentary extra-digit. Recently, biallelic truncating variants in the transcription factor GLI1 were reported to be associated with a recessive disorder, which in addition to PAP-A, may include syndromic features. Moreover, two heterozygous subjects carrying only one inactive copy of GLI1 were also identified with PAP. Herein, we aimed to determine the level of involvement of GLI1 in isolated PAP, a condition previously established to be autosomal dominantly inherited with incomplete penetrance. We analyzed the coding region of GLI1 in 95 independent probands with nonsyndromic PAP and found 11.57% of these subjects with single heterozygous pathogenic variants in this gene. The detected variants lead to premature termination codons or result in amino acid changes in the DNA-binding domain of GLI1 that diminish its transactivation activity. Family segregation analysis of these variants was consistent with dominant inheritance with incomplete penetrance. We conclude that heterozygous changes in GLI1 underlie a significant proportion of sporadic or familial cases of isolated PAP-A/B