Burned area detection and mapping using Sentinel-1 backscatter coefficient and thermal anomalies

This paper presents a burned area mapping algorithm based on change detection of Sentinel-1 backscatter data guided by thermal anomalies. The algorithm self-adapts to the local scattering conditions and it is robust to variations of input data availability. The algorithm applies the Reed-Xiaoli detector (RXD) to distinguish anomalous changes of the backscatter coefficient. Such changes are linked to fire events, which are derived from thermal anomalies (hotspots) acquired during the detection period by the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Land cover maps were used to account for changing backscatter behaviour as the RXD is class dependent. A machine learning classifier (random forests) was used to detect burned areas where hotspots were not available. Burned area perimeters derived from optical images (Landsat-8 and Sentinel-2) were used to validate the algorithm results. The validation dataset covers 21 million hectares in 18 locations that represent the main biomes affected by fires, from boreal forests to tropical and sub-tropical forests and savannas. A mean Dice coefficient (DC) over all studied locations of 0.59±0.06 (±confidence interval, 95%) was obtained. Mean omission (OE) and commission errors (CE) were 0.43±0.08 and 0.37±0.06, respectively. Comparing results with the MODIS based MCD64A1 Version 6, our detections are quite promising, improving on average DC by 0.13 and reducing OE and CE by 0.12 and 0.06, respectively.European Space AgencyMinisterio de Educación, Cultura y Deport

Mortality and recruitment of fire-tolerant eucalypts as influenced by wildfire severity and recent prescribed fire

Mixed-species eucalypt forests of temperate Australia are assumed tolerant of most fire regimes based on the impressive capacity of the dominant eucalypts to resprout. However, empirical data to test this assumption are rare, limiting capacity to predict forest tolerance to emerging fire regimes including more frequent severe wildfires and extensive use of prescribed fire. We quantified tree mortality and regeneration in mixed-species eucalypt forests five years after an extensive wildfire that burnt under extreme fire weather. To examine combined site-level effects of wildfire and prescribed fire, our study included factorial replications of three wildfire severities, assessed as crown scorch and understorey consumption shortly after the wildfire (Unburnt, Low, High), and two times since last preceding fire (30 years since any fire). Our data indicate that while most trees survived low-severity wildfire through epicormic resprouting, this capacity was tested by high-severity wildfire. Five years after the wildfire, percentage mortalities of eucalypts in all size intervals from 10 to >70 cm diameter were significantly greater at High severity than Unburnt or Low severity sites, and included the near loss of the 10–20 cm cohort (93% mortality). Prolific seedling regeneration at High severity sites, and unreliable basal resprouting, indicated the importance of seedling recruitment to the resilience of these firetolerant forests. Recent prescribed fire had no clear effect on forest resistance (as tree survival) to wildfire, but decreased site-level resilience (as recruitment) by increasing mortalities of small stems. Our study indicates that high-severity wildfire has the potential to cause transitions to more open, simplified stand structures through increased tree mortality, including disproportionate losses in some size cohorts. Dependence on seedling recruitment could increase vulnerabilities to subsequent fires and future climates, potentially requiring direct management interventions to bolster forest resilience.Australian Governmen

Synthetic aperture radar sensitivity to forest changes: A simulations-based study for the Romanian forests

Natural and anthropogenic disturbances pose a significant threat to forest condition. Continuous, reliable and accurate forest monitoring systems are needed to provide earlywarning of potential declines in forest condition. To address that need, state-of-the-art simulationsmodelswere used to evaluate the utility of C-, L- and P-band synthetic aperture radar (SAR) sensors within an integrated Earth-Observation monitoring system for beech, oak and coniferous forests in Romania. The electromagnetic simulations showed differentiated sensitivity to vegetation water content, leaf area index, and forest disturbance depending on SAR wavelength and forest structure. C-band data was largely influenced by foliage volume and therefore may be useful for monitoring defoliation. Changes in water content modulated the C-band signal by b1 dBwhichmay be insufficient for a meaningful retrieval of drought effects on forest. Cband sensitivity to significant clear-cuts was rather low (1.5 dB). More subtle effects such as selective logging or thinning may not be easily detected using C- or L-band data with the longer P-band needed for retrieving small intensity forest disturbances. Overall, the simulations emphasize that additional effort is needed to overcome current limitations arising from the use of a single frequency, acquisition time and geometry by tapping the advantages of dense time series, and by combining acquisitions from active and passive sensors. The simulation results may be applicable to forests outside of Romania since the forests types used in the study have similar morphological characteristics to forests elsewhere in Europe.Romanian National Agency for Scientific Research and Innovation Authorit

Optimized ultrasound-assisted extraction of phenolic compounds from Thymus comosus Heuff. ex Griseb. et Schenk (wild thyme) and their bioactive potential

An optimized ultrasound-assisted extractive method was developed to obtain a polyphenol-enriched extract from the aerial parts of Thymus comosus Heuff. ex Griseb. et Schenk. Optimization process was conducted based on Design of Experiment (DoE) principles, determining the influence of three independent variables (time, ultrasound amplitude, ethanol concentration) on the total phenolic content of the extract (dependent variable). Additionally, the phenolic composition of the extract was characterized through UHPLC-HRMS, revealing beside the most abundant flavonoid-type compounds the presence of salvianolic acids C, D and L in high amounts. Phytochemical profile of the extract was correlated with its antioxidant activity (tested through five complementary assays) and enzyme-inhibitory potential, showing important antiglucosidase and anticholinesterase effects. Overall, it was concluded that the developed method is suitable for obtaining a good recovery of both phenolic and non-phenolic compounds from Thymus comosus aerial parts, and their presence in the optimized extract is responsible for its pharmacological potential.This work was supported by a grant of the Romanian Ministry of Education and Research, CNCS – UEFISCDI, project number PN-III-P1- 1.1-PD-2019-1245, within PNCDI III”. The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES to CIMO (UIDB/00690/2020), and for the contracts of J. Pinela (CEECIND/01011/2018) and L. Barros (institutional scientific employment program-contract).info:eu-repo/semantics/publishedVersio

Development of an optimized drying process for the recovery of bioactive compounds from the Autumn Fruits of Berberis vulgaris L. and Crataegus monogyna Jacq

Hot air drying has proven to be an efficient method to preserve specific edible plant materials with medicinal properties. This is a process involving chemical, physical, and biological changes in plant matrices. Understanding these processes will lead to an improvement in the yields of bioactive compounds. This study aims to optimize the drying process of two species’ fruits used in folk medicine, Berberis vulgaris and Crataegus monogyna. The optimized extracts’ antioxidant capacity was assessed using various assays, with the barberry extract showing very good activity (50.85, 30.98, and 302.45 mg TE/g dw for DPPH, TEAC, and FRAP assays, respectively). Both species exerted good fungal α-glucosidase inhibitory activity (IC50 = 0.34 and 0.56 mg/mL, respectively) but no activity on mammalian α-glucosidase. Additionally, this study identified and quantified the main bioactive compounds. The results presented herein are a breakthrough in industrializing this drying process. Additional studies are necessary to mechanistically understand the drying process involved in these plant materials.This work was supported by a grant of the Romanian Ministry of Education and Research, CNCS–UEFISCDI, project number PN-III-P2-2.1-PED-2019-5360.The authors are grateful to the Foundation for Science and Technology (FCT; Portugal) for financial support through national funds FCT/MCTES to CIMO (UIDB/00690/2020), the national funding for F.C.T. and P.I. and through the institutional scientific employment program contract for M.I.D., and L.B. The authors are grateful to FEDER—Interreg España—Portugal programme for financial support through the project TRANSCoLAB 0612_TRANS_CO_LAB_2_P.info:eu-repo/semantics/publishedVersio

ERGONOMIC CONCEPTS IN DENTAL MEDICINE

Dental medicine is an extremely complex medical field, comprising several specialties (orthodontics and dentofacial orthopedics, prosthodontics, dental surgery, endodontics etc.), which in most cases also require the assistance of a dental nurse. Purpose. In this paper, we have tried to present a number of very interesting ergonomic aspects in the dental office, which aim at simplifying work at this level. Material and method. This study was conducted between May and July 2018 using a questionaire applied to a number of 69 dental practitioners from Bucharest. Results and discussions. Results obtained in this study give us an image about how current dental practitioners understand ergonomics in daily practice. Conlclusions. All the aspects discussed in this study have an important role in the ergonomy of daily activity of a dental office. More important is that the majority of dentists involved in the stuty understand and apply the ergonomic concepts underlined by this study

Assessing the Utility of Sentinel-1 Coherence Time Series for Temperate and Tropical Forest Mapping

This study tested the ability of Sentinel-1 C-band to separate forest from other common land use classes (i.e., urban, low vegetation and water) at two different sites. The first site is characterized by temperate forests and rough terrain while the second by tropical forest and near-flat terrain. We trained a support vector machine classifier using increasing feature sets starting from annual backscatter statistics (average, standard deviation) and adding long-term coherence (i.e., coherence estimate for two acquisitions with a large time difference), as well as short-term (six to twelve days) coherence statistics from annual time series. Classification accuracies using all feature sets was high (>92% overall accuracy). For temperate forests the overall accuracy improved by up to 5% when coherence features were added: long-term coherence reduced misclassification of forest as urban, whereas short-term coherence statistics reduced the misclassification of low vegetation as forest. Classification accuracy for tropical forests showed little differences across feature sets, as the annual backscatter statistics sufficed to separate forest from low vegetation, the other dominant land cover. Our results show the importance of coherence for forest classification over rough terrain, where forest omission error was reduced up to 11%

Patch-based Image Classification for Sentinel-1 and Sentinel-2 Earth Observation Image Data Products

Due the continuous growth of Earth Observation (EO) image data collections acquired from a great variety of sensors, we can observe an increasing need for methods and techniques of querying remote sensing images, not only by their annotations but also by their semantic content. Various methods of content based image retrieval (CBIR) have been proposed in the remote sensing domain, but no general approaches are available. Regardless of the used method, the CBIR systems have the same function, to identify the most similar images with the query image. Some authors developed powerful CBIR tools such as GeoIRIS system of Shyu C. et al. which is a content-based multimodal Geospatial Information Retrieval and Indexing System and includes automatic feature extraction, visual content mining from large-scale image databases, and high-dimensional database indexing for fast retrieval, KIM - knowledge-driven information mining proposed by Datcu M. et al. which is based on human-centered concepts and implements new features and functions allowing improved feature extraction, search on a semantic level, the availability of collected knowledge and interactive knowledge discovery, SemQuery,developed by Sheikholeslami G. et al., which is a semantics-based clustering and indexing approach, used to support visual queries on heterogeneous features of images. Regarding the idea of finding a common ground between synthetic aperture radar (SAR), optical data and even data fusion products, the goal is to develop an application capable to join feature extraction algorithms and classification algorithms. Therefore, this paper is presenting a framework of feature extraction methods for SAR, Multispectral and Data fusion image products that can be used in automatic or semi-automatic classification of urban areas. Our results demonstrate the usability of patch based image classification techniques that can be applied on Sentinel-1 and Sentinel-2 public data sets. Also, another goal is to demonstrate how data fusion products perform in the context of patch based image classification and automatic annotation of urban areas. In order to do so, the selected scene is grouped in a few generic classes like buildings, vegetation, forest, water, streets etc. Then we use feature extraction methods such as Gabor filter banks and Weber Local Descriptors in combination with Support Vector Machine (SVM) and k-Nearest Neighbours (k-NN) to define an application to be tested on SAR, optical data and data fusion products. The result of the study is intended to establish the optimum number of classes that can be found in the Sentinel-1 and Sentinel-2 images when using patch based image classification techniques. Also another important objective of this paper is to determine the best patch sizes suitable for this type of classification and that can be used to obtain the best results for Sentinel-1 and Sentinel-2 EO images

Sar sensitivity to burn severity and forest recovery in mediterranean environments: Backscatter and interferometric coherence analysis

Worldwide, forests fires destroy annually millions of hectares from tropical to boreal region. In the European part of the Mediterranean basin alone about five hundred thousand hectares are affected each year making fires one of the most important ecological threats. Remotely sensed data can contribute to a better, cost effective, objective and time saving method to monitor and quantify location, extent and intensity of fire events. Despite the extensive archives of space borne synthetic aperture radar (SAR) data few studies were carried out having as topic forest fires. This thesis explores the use of synthetic aperture radar for post-fire studies highlighting not only its advantages but also the potential sources of error. Regional models for burn severity assessment were developed using field samples (composite burn index - CBI) and optical based spectral indices (difference Normalized Burn Ratio - dNBR) to assess the relationship strength between these variables across five recently burned sites in northeastern Spain. Linear and non-linear models were tested and the estimation error of each model was estimated. SAR data at X-, C- and L-band were investigated to determine the relationship between radar metrics (backscatter and interferometric coherence) and forest burn severity over three burn scars. The dependency of the SAR backscatter upon local incidence angle and environmental conditions has been also analyzed. In addition, SAR data were used to analyze backscatter and interferometric coherence from regrowing forests previously affected by fire. L-band data analysis was extended to burned boreal forests.Statistical analysis was used to assess the radar metrics as a function of burn severity level or forest regrowth phase after stratifying the data by local incidence angle. Determination coefficients were used to quantify the relationship between radar data and burn severity estimates. Fire scar differentiation using optical based indices is attainable in Aragón pine forests. Burn severity estimation errors for highly burned sites were well below 10 % whereas for low and moderate severities errors increased up to 25%. A strong linear relation was found between burn severity at plot level and understory and overstory composites. The analysisdemonstrated the model consistency at regional level and the need for new estimation methods in areas affected by low to moderate burn severities even for homogeneous forests. SAR metrics (backscatter and coherence) were sensitive to burn severity. For co-polarized channels (HH and VV)the backscatter increased with burn severity for X- and C-band whereas for L-band it decreased. Cross-polarized (HV) backscatter decreased with burn severity for all frequencies. The sensitivity of the co-polarized backscatter to burn severity decreased for increasing local incidence angle for all frequencies except at L-band. For X- and C-band co-polarized data higher determination coefficients were observed for slopes oriented towards the sensors whereas for cross-polarized data the determination coefficients were higher for slopes oriented away from the sensor. At L-band the association strength of cross-polarized data to burn severity was high for all local incidence angles. Co-polarized coherence increased with the increase of burn severity at X- and C-band whereas cross-polarized coherence was practically insensitive to burn severity. Higher sensitivity to burn severity was found at L-band for both co- and cross-polarized channels. The association strength between coherence and burn severity was strongest for images acquired under stable, dry environmental conditions. When the local incidence angle is accounted for, the determination coefficients increased from 0.6 to 0.9 for X- and C-band. At L-band the local incidence angle had less influence on the association strength to burn severity. L-band (both metrics) showed the highest potential for burn severity estimation in the Mediterranean environment. The small dynamic range observed for X-band data could hinder its use in forests affected by fires. At L-band, the results from boreal forest confirmed the data trends obtained in the Mediterranean basin at least for specific environmental conditions (images acquired during the growing season in relatively dry conditions). Low sensitivity to forest regrowth was observed for X-band backscatter, the average backscatter increasing by 1-2 dB between the most recent fire scars and the unburned forest. C-band showed increased sensitivity, the backscatter difference between burned and unburned forest being around 4 dB. L-band backscatter presented the highest sensitivity to forest regrowth, the backscatter difference being approximately 8 dB. For a given frequency the sensitivity of the SAR backscatter to forest regrowth varied with local incidence angle and polarization. The interferometric coherence showed low sensitivity to forest regrowth at all SAR frequencies. For mediterranean forests five phases of forest regrowth were discerned whereas for boreal forest, up to four different regrowth phases could be discerned with L-band SAR data. In comparison, the Normalized Difference Vegetation Index (NDVI) provided reliable differentiation only for the most recent development stages, as it registers mostly information related to the vegetation cover. The results obtained were consistent in both environments. These findings indicate that SAR systems have potential for burn severity estimation using either the backscatter coefficient or the interferometric coherence. The joint use of backscatter and coherence did not significantly improved burn severity estimation in any of the studied frequencies. Promising results were achieved for forest regrowth monitoring when using the backscatter coefficient of low frequency bands (L-). The higher frequency bands (X- and C-) showed low sensitivity to changes in forest structure, having little potential for differentiating between forest regrowth stages