Other Species’ Alarm Calls Evoke a Predator-Specific Search Image in Birds

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Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data

Aims　Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods　In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R²) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.     

Combination of dual-energy computed tomography and iterative metal artefact reduction to increase general quality of imaging for radiotherapy patients with high dense materials. Phantom study

PurposeTo evaluate the use of pseudo-monoenergetic reconstructions (PMR) from dual-energy computed tomography, combined with the iterative metal artefact reduction (iMAR) method.MethodsPseudo-monoenergetic CT images were obtained using the dual-energy mode on the Siemens Somatom Definition AS scanner. A range of PMR combinations (70–130 keV) were used with and without iMAR. A Virtual Water™ phantom was used for quantitative assessment of error in the presence of high density materials: titanium, alloys 330 and 600. The absolute values of CT number differences (AD) and normalised standard deviations (NSD) were calculated for different phantom positions. Image quality was assessed using an anthropomorphic pelvic phantom with an embedded hip prosthesis. Image quality was scored blindly by five observers.ResultsAD and NSD values revealed differences in CT number errors between tested sets. AD and NSD were reduced in the vicinity of metal for images with iMAR (p < 0.001 for AD/NSD). For ROIs away from metal, with and without iMAR, 70 keV PMR and pCT AD values were lower than for the other reconstructions (p = 0.039). Similarly, iMAR NSD values measured away from metal were lower for 130 keV and 70 keV PMR (p = 0.002). Image quality scores were higher for 70 keV and 130 keV PMR with iMAR (p = 0.034).ConclusionThe use of 70 keV PMR with iMAR allows for significant metal artefact reduction and low CT number errors observed in the vicinity of dense materials. It is therefore an attractive alternative to high keV imaging when imaging patients with metallic implants, especially in the context of radiotherapy planning.     

Issues in using whole slide imaging for diagnostic pathology: “routine” stains,immunohistochemistry and predictive markers

The traditional microscope, together with the “routine” hematoxylin and eosin (H & E) stain, remains the “gold standard” for diagnosis of cancer and other diseases; remarkably, it and the majority of associated biological stains are more than 150 years old. Immunohistochemistry has added to the repertoire of “stains” available. Because of the need for specific identification and even measurement of “biomarkers,” immunohistochemistry has increased the demand for consistency of performance and interpretation of staining results. Rapid advances in the capabilities of digital imaging hardware and software now offer a realistic route to improved reproducibility, accuracy and quantification by utilizing whole slide digital images for diagnosis, education and research. There also are potential efficiencies in work flow and the promise of powerful new analytical methods; however, there also are challenges with respect to validation of the quality and fidelity of digital images, including the standard H & E stain, so that diagnostic performance by pathologists is not compromised when they rely on whole slide images instead of traditional stained tissues on glass slides.     

基于遥感的建筑物高度快速提取研究综述

近年来我国城市化进程不断推进,不仅体现在城市面积上的增长,也体现在建筑物高度的增长。高度增长一方面能尽量克服城市土地资源匮乏的瓶颈,另一方面为优化城市结构及城市功能做出贡献。在城市遥感研究领域,对于城市建筑物高度的提取也成为研究的重点。城市建筑物高度的估计与测量,已成为城市规划和扩张、城市灾害风险预警与评估的重要参数,同时也为数字城市三维模型的建立提供了基础测绘资料。分别基于光学遥感影像、高分辨率SAR(Synthetic Aperture Radar)影像以及光学遥感影像与高分辨率SAR影像的融合三方面,全面阐述城市建筑物高度的提取方法,并比较两类影像在提取建筑物高度的优劣势,通过回顾早年研究方法,逐步引入近年来新的发展趋势。     

基于TM/ETM~+数据的沈阳市各区城市热岛特征

应用2001年8月和2010年8月Landsat TM/ETM+数据,计算沈阳市区及三环内各区的地表热岛强度(SUHI),根据土地利用数据和热岛源汇特征提取源汇信息,分析SUHI与土地利用类型、热岛源汇面积及边界长度、归一化植被指数(NDVI)、归一化建筑指数(NDBI)、改进的归一化差异水体指数(MNDWI)的关系。结果表明:2001年沈阳市区的中等热岛强度以上区域主要集中在三环内和苏家屯区,强热岛地区主要出现在铁西区和皇姑区;2010年中等以上热岛强度地区,与城区发展相一致,主要向西南,南面扩展,弱热岛、中等强度和强热岛地区有较大幅度的增加;城市热岛强度与NDVI存在显著的负相关,与NDBI存在显著的正相关;热岛源在区域内的面积比重与中等强度以上热岛存在较显著的相关关系,源汇边界长度与弱热岛和中等热岛存在较显著的相关关系。