Estimation of urban tree canopy cover using random point sampling and remote sensing methods

Trees play an important role in urban areas by improving air quality, mitigating urban heat islands, reducing stormwater runoff and providing biodiversity habitat. Accurate and up-to-date estimation of urban tree canopy cover (UTC) is a basic need for the management of green spaces in cities, providing a metric from which variation can be understood, change monitored and areas prioritised. Random point sampling methods, such as i-Tree canopy, provide a cheap and quick estimation of UTC for a large area. Remote sensing methods using airborne Light Detection And Ranging (LiDAR) and multi-spectral images produce accurate UTC maps, although greater processing time and technical skills are required. In this paper, random point sampling and remote sensing methods are used to estimate UTC in Williamstown, a suburb of Melbourne, Australia. High resolution multi-spectral satellite images fused with LiDAR data with pixel-level accuracy are employed to produce the UTC map. The UTC is also estimated by categorising random points (a) automatically using the LiDAR derived UTC map and (b) manually using Google Maps and i-Tree canopy software. There was a minimum 1% difference between UTC estimated from the map derived from remotely sensed data and only 1000 random points automatically categorised by that same map, indicating the level of error associated with a random sampling approach. The difference between UTC estimated by remote sensing and manually categorised random point sampling varied in range of 4.5% using a confidence level of 95%. As monitoring of urban forest canopy becomes an increasing priority, the uncertainties associated with different UTC estimates should be considered when tracking change or comparing different areas using different methods.     

中国图像工程:2015

目的 本文是关于中国图像工程的年度文献综述系列之二十一。为了使国内广大从事图像工程研究和图像技术应用的科技人员能够较全面地了解国内图像工程研究和发展的现状,能够方便地查询有关文献,且向期刊编者和作者提供有用的参考,对2015年度图像工程重要文献进行了综述分析。方法 从2015年在国内15种有关图像工程重要中文期刊的共148期上所发表的2975篇学术研究和技术应用文献中,选取出723篇属于图像工程领域的文献,并根据各文献的主要内容将其分别归入图像处理,图像分析,图像理解,技术应用和综述5个大类,然后进一步分入23个专业小类(与前10年相同),并在此基础上分别进行了各期刊各类文献的统计和分析。结果 根据对2015年统计数据的分析可看出:图像分析正得到最多关注,目标跟踪的文献数量有明显增加,图像分割和边缘检测仍然是研究重点,图像匹配融合及其在遥感测绘等的应用再次成为热点。结论 我国图像工程的2015年研究深度和广度仍在提高和扩大,保持了快速进展的势头。     

AN APPLICATION OF IMAGE PROCESSING TECHNIQUES IN COMPUTED TOMOGRAPHY IMAGE ANALYSIS

An estimate of the thickness of subcutaneous adipose tissue at differing positions around the body was required in a study examining body composition. To eliminate human error associated with the manual placement of markers for measurements and to facilitate the collection of data from a large number of animals and image slices, automation of the process was desirable. The open-source and free image analysis program ImageJ was used. A macro procedure was created that provided the required functionality. The macro performs a number of basic image processing procedures. These include an initial process designed to remove the scanning table from the image and to center the animal in the image. This is followed by placement of a vertical line segment from the mid point of the upper border of the image to the image center. Measurements are made between automatically detected outer and inner boundaries of subcutaneous adipose tissue along this line segment. This process was repeated as the image was rotated (with the line position remaining unchanged) so that measurements around the complete circumference were obtained. Additionally, an image was created showing all detected boundary points so that sites of measurement could be checked by visual inspection. This paper provides a detailed account of this macro, illustrates the effect of its components on the image, and the applicability of standard image processing techniques to veterinary imaging.     

基于2D DWT与MobileNetV3融合的轻量级茶叶病害识别

针对现有茶叶病害识别方法病害信息挖掘不足导致识别准确率低的问题，该研究提出了一种基于二维离散小波变换(discrete wavelet transform, DWT)和MobileNetV3融合的茶叶病害识别模型CBAM-TealeafNet。为增强网络对病害频域特征的检测能力，将2D DWT获取的频域特征与bneck结构提取的深度特征融合，形成频域与深度特征融合的识别网络。为提高特征提取能力，在bneck结构中，嵌入卷积块注意模块 (convolutional block attention module, CBAM)，为特征通道分配相应权重。为解决样本类别不平衡对识别模型性能的影响，利用焦点损失函数取代交叉熵损失函数以提高识别精度。经验证，CBAM-TealeafNet在5种不同茶叶病害上整体识别准确率达到98.70%，参数量为3.16×10⁶，相对MobileNetV3，准确率提升2.15个百分点，参数量降低25.12%。该方法可为茶树叶部等作物病害轻量级识别研究提供模型参考。     

Tolerance of four spring barley (Hordeum vulgare) varieties to weed harrowing

We investigated the tolerance to weed harrowing of four spring barley varieties and examined the possible interactions between varietal weed suppressive ability and two nutrient levels. Tolerance was defined as the combined effect of crop resistance (ability to resist soil covering) and crop recovery (the ability to recover in terms of yield). The weed harrowing strategy was a combination of one pre‐ and one post‐emergence weed harrowing. In terms of yield, the four varieties responded significantly differently to weed harrowing and the response depended on nutrient level. At the lower nutrient level, weed harrowing caused an increase in yield of 4.4 hkg ha⁻¹ for a strong competitor (cv. Otira), while there was no effect on yield at the higher nutrient level. For a weaker competitor (cv. Brazil), weed harrowing caused no change in yield at the lower nutrient level, whereas yield decreased by 6.0 hkg ha⁻¹ at the higher nutrient level. There were marked differences between the weed suppressive ability of the four varieties when not harrowed, with less pronounced but significant differences when harrowed. Weed harrowing did not change the weed suppressive ability of a variety. Varieties that are tall at post‐emergence harrowing and have increased density after pre‐emergence harrowing, are the ones that benefit most from weed harrowing.     

Desiring image for Women in Modern Chinese Writers＇ ＂South Pacific＂ Story

研究了现代作家有关“南洋”女性人物的作品，认为中国现代作家笔下涉及“南洋”故事的女性描写，多呈现出“男权主义”的叙境。其中包括“景色女”的被凝视、“商人妇”的被“闺范”以及“英雄妻”附属性的被欲望化叙事，所有这一切都显示了“菲勒斯中心主义”的欲像图式的胜利。     

Evaluating Modified Atmospheric Correction Methods for Landsat Imagery: Image‐Based and Model‐Based Calibration Methods

Abstract

To increase the accuracy of remotely sensed data for agricultural forecasting, pixel values must be corrected for atmospheric effects and converted to spectral reflectance. The objective of this research was to compare two atmospheric correction methods of Landsat imagery under a range of atmospheric conditions. Ground‐based dark‐object subtraction (GDOS) is an image‐based calibration method that used in situ ground data that the dark‐object subtraction (DOS) method did not use, whereas atmospheric calibration (AC) is a model‐based calibration method that required a standard atmospheric profile refined with the use of in situ atmospheric data. GDOS and AC methods improved the reflectance values and had relationships with measured bands, which were approximately 1 to 1 in all bands. However, the GDOS generally had lower root‐mean‐square errors (RMSE) than AC. Data from this study suggest that at the present time the GDOS method may be more accurate than the AC method.     

Fine-scale vegetation patches decline in size and cover with increasing rainfall in Australian savannas

Fine-scale vegetation patches (<5 m in width) are critically important in many landscapes because they function to obstruct surface flows of water and wind. These obstructions increase the infiltration of runoff and the capture of nutrients in runoff sediments and in wind-blown soil and litter. The importance of redistribution of runoff into runon patches from spaces between patches (fetches) is likely to be greater in drier than in wetter environments. In this paper we examine the hypothesis that the ratio of fetch to patch decreases as rainfall increases, and that this trend will be most evident on intermediate-textured soils because these soils are more prone to runoff. We measured fine-scale patches on 38 sites with sand, loam or clay soils. Sites were located along a 1000-mm rainfall gradient in the savannas of northern Australia. The width and intercept length of patches and the fetch between patches was measuring along line transects of 100–120 m oriented down slope. We found that the ratio of fetch to patch area did not decrease with decreasing rainfall, but increased on both sand and loam soils. This result was because with increasing rainfall mean spacing between patches disproportionally increased while mean patch size and cover declined. The cover of patches was negatively correlated with tree canopy cover, which significantly increased with rainfall. This negative correlation suggests that in higher rainfall savannas the size and spacing of ground-layer patches is controlled by the tree layer, and that as rainfall decreases this control decreases and runoff-runon processes increasingly structure the landscape. For savannas on clay soils these trends were not significant except that on the highest rainfall sites the cover of ground-layer patches was nearly 100% while trees were absent.     

5种弥散神经内分泌细胞在鸭腔上囊中的表达特征

应用免疫组化技术并结合图像分析软件研究了胃泌素、β-内啡肽、胰高血糖素、5-羟色胺、生长押素在鸭腔上囊中的表达特征.结果显示鸭腔上囊小结相关上皮细胞呈胃泌素强阳性反应;滤泡间粘膜上皮呈β-内啡肽中强度阳性反应;淋巴滤泡皮质部有少量的β-内啡肽、胃泌素、5-羟色胺阳性细胞,呈中、强度免疫反应;淋巴滤泡髓质有胃泌素强阳性细胞;生长抑素和胰高血糖素均呈阴性反应.结果说明,鸭腔上囊中存在β-内啡肤、胃泌素、5-羟色胺弥散神经内分泌细胞,它们在淋巴滤泡皮质部的表达特征有利于其通过内分泌和旁分泌方式调节B细胞的发育.     

论强化公关形象对构建和谐高校的意义

高校公共关系的一个重要目标是调动师生员工的积极因素, 促进高校教育教学质量的提高。其目的在于建立、维持和发展学校与公众之间关系的总体协调, 确保高校的方针政策顺利贯彻实施, 并通过完成高校的基本教学任务, 树立高校良好形象, 提高高校美誉度。高校公共关系的这种价值追求与和谐社会、和谐校园的内在要求完全相契合。