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Synchronized “Click” and Templated Synthesis of a Fluorescent Pyrene Crown Ether
摘要： The reaction of 6,8-bisethynylpyrene-2-carboxylic acid methyl ester with 1-azido-2-(2-(2-azidoethoxy)ethoxy)ethoxy)ethane using standard “click” chemistry produced a 1+1 crown ether (CPYR). The copper ions used both catalyse the reaction and provide a template for ensuring smooth cyclisation. The X-ray crystal structure of the compound reveals the two triazole groups are non-coplanar with the pyrene moiety. The triazole groups are more co-planar with the pyrene subunit in the first-excited singlet state as revealed by a density functional theory (DFT) calculated molecular structure (B3LYP, 6-311G). Partially structured emission observed in acetonitrile is consistent with the calculation result. In acetonitrile solution the macrocycle CPYR interacts with a Na+ ion to form a complex in which the ion binds with the crown and the pyrene residue.
关键词： pyrene,structure,click,binding,crown ether
更新于2025-11-19 16:46:39
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Optically active crown ether-based fluorescent sensor molecules: A mini-review
摘要： This mini‐review focuses on fluorescent optically active crown ethers (polymeric derivatives are not included) reported in the literature (according to our knowledge), of which enantiomeric recognition ability, and in some cases, also inorganic cation complexation properties, were investigated by the sensitive and versatile fluorescence spectroscopy. These crown ether‐based chemosensors contain various fluorophore signaling units such as binaphthyl, anthracene, pyrene, tryptophan, benzimidazole, terpyridine, acridine, phenazine, acridone, BODIPY, and another conjugated aromatic one.
关键词： enantiomeric recognition,complexation,fluorophore,chemosensor,chiral crown ether
更新于2025-09-23 15:23:52
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Individual mangrove tree measurement using UAV-based LiDAR data: Possibilities and challenges
摘要： Individual mangrove tree parameters are necessary for the efficient management and protection of this unique ecosystem, but to measure them using remote sensing (RS) is still a new and challenging task due to the high clumping density of mangrove crowns and the relatively low spatial resolution of RS data. Unmanned aerial vehicles (UAVs), as an emerging RS technique, significantly improves the spatial resolution, but has not been used for individual mangrove analysis. This study presents the first investigation into the possibility of individual tree detection and delineation (ITDD) for mangroves using light detection and ranging (LiDAR) data (91 pt./m2) collected from UAV. Specifically, we aim to detect and measure tree height (TH) and crown diameter (CD) of each mangrove tree, and analyze the impact of crown clumping density and spatial resolution on mangrove ITDD. To this end, we combined the variable window filtering method and marker controlled watershed segmentation algorithm, and successfully delineated 46.0% of the 126 field measured mangroves. This was promising considering the complexity of mangrove forest. TH and CD were estimated with higher accuracies than previous studies. The isolated trees, with the lowest clumping density, were delineated with the highest accuracy. To identify the optimal spatial resolution of canopy height model (CHM), we defined four spatial resolutions (0.1 m, 0.25 m, 0.5 m, and 1 m) and conducted a simulation. Based on the results, we propose a rule-of-thumb that the spatial resolution should be finer than one-fourth of CD for ITDD, which is also applicable to other forest types. The main difficulty for mangrove ITDD is an overall under-detection of trees, which is caused by the high clumping density and limited height difference between adjacent mangroves. We recommend combining UAV LiDAR with imagery and terrestrial LiDAR to improve the mangrove ITDD performance.
关键词： LiDAR,Unmanned aerial vehicle,Mangrove,Individual crown,Optimal spatial resolution
更新于2025-09-23 15:22:29
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Crown-Porphyrin Ligand for Optical Sensors Development
摘要： A novel porphyrin ligand, Zn(II)TPP-BPI-crown (ZnPC), functionalized with two dibenzo-crown-ether moieties was synthesized and tested as cation-sensitive ionophore. Fluorescence studies on ligand sensitivity towards a number of different metal cations (Na+, K+, Li+, Ca2+, Mg2+, Co2+, Cd2+, Pb2+, Cu2+, Zn2+ and NH4+) were carried out first in solution and then inside polymeric membrane optodes. Emission light signal was sufficiently brilliant to be captured by a low-cost computer webcam, while a commercial blue-light LED served as monochromic excitation light source. The influence on the ZnPC optode response of the lipophilic sites functionalization was investigated. The visibly (naked eye) observed color change of sensing material from green to red demonstrated the suitability of the ZnPC-based optodes to perform fast monitoring of Cu(II) ions in the concentration range between 6.6 × 10?7 and 2.4 × 10?2 mol/L with a low detection limit (estimated by s/n = 3 method) of 0.3 mg/L, which is lower than WHO guideline value of 2 mg/L.
关键词： chemical optical sensor,novel Zn(II)-porphyrin ligand functionalized with two dibenzo-crown-ether moieties,naked eye detection of Cu(II) ions
更新于2025-09-23 15:21:01
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Fusion of Multitemporal LiDAR Data for Individual Tree Crown Parameter Estimation on Low Density Point Clouds
摘要： The increasingly availability of Light Detection and Ranging (LiDAR) data acquired at different times can be used to analyze the forest dynamics at individual tree level. This often requires to deal with LiDAR point clouds having significantly different point densities. To address this issue, this paper presents a method for the fusion of multitemporal LiDAR data which aims at using the information provided by high density LiDAR data (higher than 10 pts/m2) to improve the single tree parameter estimation of low density data (up to 5 pts/m2) acquired over the same forest at different times. The method first accurately characterizes the crown shapes on the high density data. Then, it uses the obtained estimates to drive the tree parameter estimation on the low density LiDAR data. The method has been tested on a multitemporal dataset acquired in coniferous forests located in the Italian Alps. Experimental results confirmed the effectiveness of the method.
关键词： Point Cloud,Tree Crown Parameters,Remote Sensing,Multitemporal LiDAR Data,Data Fusion
更新于2025-09-23 15:21:01
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A Local Projection-Based Approach to Individual Tree Detection and 3-D Crown Delineation in Multistoried Coniferous Forests Using High-Density Airborne LiDAR Data
摘要： Accurate crown detection and delineation of dominant and subdominant trees are crucial for accurate inventorying of forests at the individual tree level. The state-of-the-art tree detection and crown delineation methods have good performance mostly with dominant trees, whereas exhibits a reduced accuracy when dealing with subdominant trees. In this paper, we propose a novel approach to accurately detect and delineate both the dominant and subdominant tree crowns in conifer-dominated multistoried forests using small footprint high-density airborne Light Detection and Ranging data. Here, 3-D candidate cloud segments delineated using a canopy height model segmentation technique are projected onto a novel 3-D space where both the dominant and subdominant tree crowns can be accurately detected and delineated. Tree crowns are detected using 2-D features derived from the projected data. The delineation of the crown is performed at the voxel level with the help of both the 2-D features and 3-D texture information derived from the cloud segment. The texture information is modeled by using 3-D Gray Level Co-occurrence Matrix. The performance evaluation was done on a set of six circular plots for which reference data are available. The high detection and delineation accuracies obtained over the state of the art prove the performance of the proposed method.
关键词： forest,3-D tree crown delineation,tree top detection,airborne laser scanner,Light Detection and Ranging (LiDAR)
更新于2025-09-23 15:21:01
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Understanding Tree-to-Tree Variations in Stone Pine (Pinus pinea L.) Cone Production Using Terrestrial Laser Scanner
摘要： Kernels found in stone pinecones are of great economic value, often surpassing timber income for most forest owners. Visually evaluating cone production on standing trees is challenging since the cones are located in the sun-exposed part of the crown, and covered by two vegetative shoots. Very few studies were carried out in evaluating how new remote sensing technologies such as terrestrial laser scanners (TLS) can be used in assessing cone production, or in trying to explain the tree-to-tree variability within a given stand. Using data from 129 trees in 26 plots located in the Spanish Northern Plateau, the gain observed by using TLS data when compared to traditional inventory data in predicting the presence, the number, and the average weight of the cones in an individual tree was evaluated. The models using TLS-derived metrics consistently showed better fit statistics, when compared to models using traditional inventory data pertaining to site and tree levels. Crown dimensions such as projected crown area and crown volume, crown density, and crown asymmetry were the key TLS-derived drivers in understanding the variability in inter-tree cone production. These results underline the importance of crown characteristics in assessing cone production in stone pine. Moreover, as cone production (number of cones and average weight) is higher in crowns with lower density, the use of crown pruning, abandoned over 30 years ago, might be the key to increasing production in combination with stand density management.
关键词： modeling,terrestrial laser scanner,inter-tree variability,stone pinecone production,crown characteristics
更新于2025-09-23 15:19:57
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Ultrahigh-efficiency aqueous flat nanocrystals of CdSe/CdS@Cd <sub/>1?x</sub> Zn <sub/>x</sub> S colloidal core/crown@alloyed-shell quantum wells
摘要： Colloidal semiconductor nanoplatelets (NPLs) are highly promising luminescent materials owing to their exceptionally narrow emission spectra. While high-efficiency NPLs in non-polar organic media can be obtained readily, NPLs in aqueous media suffer from extremely low quantum yields (QYs), which completely undermines their potential, especially in biological applications. Here, we show high-efficiency water-soluble CdSe/CdS@Cd1?xZnxS core/crown@shell NPLs formed by layer-by-layer grown and composition-tuned gradient Cd1?xZnxS shells on CdSe/CdS core/crown seeds. Such control of shell composition with monolayer precision and effective peripheral crown passivation, together with the compact capping density of short 3-mercaptopropionic acid ligands, allow for QYs reaching 90% in water, accompanied by a significantly increased photoluminescence lifetime (～35 ns), indicating the suppression of nonradiative channels in these NPLs. We also demonstrate the controlled attachment of these NPLs without stacking at the nanoscale by taking advantage of their 2D geometry and hydrophilicity. This is a significant step in achieving controlled assemblies and overcoming the stacking process, which otherwise undermines their film formation and performance in optoelectronic applications. Moreover, we show that the parallel orientation of such NPLs achieved by the controlled attachment enables directed emission perpendicular to the surface of the NPL films, which is highly advantageous for light extraction in light-emitting platforms.
关键词： nanoplatelets,quantum yield,core/crown@shell,aqueous media,directed emission
更新于2025-09-19 17:15:36
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Individual Tree Crown Segmentation of a Larch Plantation Using Airborne Laser Scanning Data Based on Region Growing and Canopy Morphology Features
摘要： The detection of individual trees in a larch plantation could improve the management efficiency and production prediction. This study introduced a two-stage individual tree crown (ITC) segmentation method for airborne light detection and ranging (LiDAR) point clouds, focusing on larch plantation forests with different stem densities. The two-stage segmentation method consists of the region growing and morphology segmentation, which combines advantages of the region growing characteristics and the detailed morphology structures of tree crowns. The framework comprises five steps: (1) determination of the initial dominant segments using a region growing algorithm, (2) identification of segments to be redefined based on the 2D hull convex area of each segment, (3) establishment and selection of profiles based on the tree structures, (4) determination of the number of trees using the correlation coefficient of residuals between Gaussian fitting and the tree canopy shape described in each profile, and (5) k-means segmentation to obtain the point cloud of a single tree. The accuracy was evaluated in terms of correct matching, recall, precision, and F-score in eight plots with different stem densities. Results showed that the proposed method significantly increased ITC detections compared with that of using only the region growing algorithm, where the correct matching rate increased from 73.5% to 86.1%, and the recall value increased from 0.78 to 0.89.
关键词： airborne laser scanning (ALS),individual tree crown (ITC) segmentation,light detection and ranging (LiDAR),region growing,canopy morphology,larch plantation
更新于2025-09-19 17:13:59
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Characterizing fire effects on conifers at tree level from airborne laser scanning and high-resolution, multispectral satellite data
摘要： Post-fire assessment is made after a wildfire incident to provide details about damage level and its distribution over burned areas. Such assessments inform restoration plans and future monitoring of ecosystem recovery. Due to the high cost and time to conduct fieldwork, remote sensing is an appealing alternative to assess post-fire condition over larger areas than can be surveyed practically in the field. The aim of this study is to use remote sensing data to characterize post-fire severity at tree level in a mixed conifer forest following the Cascade and East Zone megafires of 2007 in central Idaho, USA. We used remote sensing metrics derived from Airborne Laser Scanning (ALS) data (2008) and high-resolution QuickBird (QB) multispectral satellite imagery (2007–2009) for calibrating and validating predictive models with field data (2008). We compared fire effects on trees in open canopies within recent fuel treatments to similar trees in closed canopies on adjacent, untreated sites. We observed more trees with charred crowns in high fire severity sites, mostly untreated, whereas we observed more trees with live crowns in low fire severity sites, independent of the treatment. Individual trees were more accurately detected from ALS data in treated sites with open canopies than untreated sites with closed canopies. For detected trees, the response variables predicted from ALS and QB metrics were total height (Ht), crown base height (CBH), total basal area (BAT), live basal area (BAL), scorched basal area (BAS), charred basal area (BAC) and crown severity (CS). None of the selected QB metrics were strongly correlated with the selected ALS metrics, which justified combining both data types into the predictive models. Random Forest regression models combining ALS + QB metrics or using ALS metrics alone performed similarly but clearly better than models using only QB metrics. This study shows the superiority of ALS data to high resolution, multispectral QB imagery for mapping fire severity at tree level. Managers with limited resources to plan for restoration of fire affected forests are advised to prioritize spending for data collection on ALS data and a modest number of field inventory plots, rather than QB or other broadband satellite imagery.
关键词： Crown fire severity,Fire effects,Random Forest,Individual tree attributes,Fuel treatment effectiveness
更新于2025-09-16 10:30:52