基于“2-4”模型的建筑施工高处坠落事故原因分类与统计分析

为了明确建筑施工高处坠落事故的原因分类及各类原因的发生频次概况,采用事故致因“2-4”模型分析了2000—2016年间的56起建筑施工高处坠落事故,并对各类原因进行了分类和统计分析。分析得出安全管理体系缺欠7类共62项,其中,无安全技术交底或技术交底不合格、安全组织机构不合格、无施工组织设计方案或方案不合格出现频次位于前三位;得出安全知识不足62项,安全意识不高58项,较管理者而言,一线操作者的安全知识不足和安全意识不高问题均占多数;得出不安全动作19类共296个,其中,安全培训缺失或不到位和劳动防护用品的缺乏和不正确使用2类不安全动作发生频率较高;得出不安全物态6类共54项,其中出现频率较高的是安全防护栏杆缺失或存在缺陷、脚手架或作业平台搭设不规范、安全网缺失或存在缺陷。     

Tracking land cover change along the western edge of the U.S. Corn Belt from 1984 through 2016 using satellite sensor data: observed trends and contributing factors

The Cropland Data Layers (CDL) are high-resolution geo-referenced data products made available by the U.S. Department of Agriculture. However, the CDL lacks in its ability to be employed as a tool to identify the impact of the gradually evolving drivers of land use change, e.g., climate change, due to its limited historical depth. We implement a robust, phenology-based satellite image classification algorithm to identify historical cropland allocation in eastern South Dakota and North Dakota predating the initial CDL by 13 and 22 years, respectively. Five major land covers, i.e., corn, soybeans, wheat, alfalfa and grass (including native grass, hay and pasture) are identified using archived Landsat-5 surface reflectance data, while achieving CDL-like accuracy. The long-term rate of grassland loss during 1985–2011 is found to be significantly lower (26,781 hectares or 1.5% annually) relative to the near-term rate of grassland loss during 2006-’11 (84,545 hectares or 5.2% annually). We find similar discrepancy in regional corn expansion rates. Our value-added raster data provide opportunities for improved identification of land use drivers, whereas relying solely on the CDL’s restricted historical extent may lead to biased land use change estimates and misguide policy.     

中国避暑旅居城市指标体系构建与分类评价

依据避暑旅居的内涵与特点,从环境质量、服务需求、旅游资源和市场潜力4个维度构建了我国避暑旅居指标体系,并运用多维度综合评价法对我国25个主要城市的避暑旅居潜力进行了研究。结果发现:不同城市的避暑旅居潜力差异较大,生态环境质量、旅游资源丰富性、地区经济水平、交通区位条件、服务接待能力和游客感知水平等是避暑旅居潜力大小的主要影响因素。通过对分类评价潜力模型的分析,提出各自的发展方向与建议。     

基于高分影像的城市水体遥感综合分级方法

城市水体是城市生态系统中的重要组成部分,为此,针对城市水体提出了一种基于国产高分影像的水环境遥感综合评价方法.在2017~2019年间的南京、无锡、常州和扬州市等城市多次水体采样工作的基础上,分析了城市水体光谱特征与水质参数的相应关系.基于国际标准的色度转换模型和FUI（forel-ule index）水色指数,构建了基于高分二号（GF-2）影像的适用于城市水体的U-FUI（urban forel-ule index）水色指数,实现了城市水体的遥感分级,独立的验证数据表明分级模型的识别正确率可达72%.结果表明,根据U-FUI水色指数可以将城市水体有效地分为U-FUI Ⅰ~U-FUI Ⅵ共6级水体,依次分别代表水色呈蓝色、浅绿色、深绿色、黄色、黄棕色以及灰黑色的水体.其中,U-FUI的Ⅰ级水体水质较好而在城市水体中少有分布,U-FUI的Ⅱ和Ⅲ级水体具有较高的叶绿素a浓度,U-FUI的Ⅳ和Ⅴ级水体的总悬浮物浓度和无机悬浮物浓度相对较高,U-FUI的Ⅵ级水体水质较差且水质参数与各级水体均有较大差异.同时,将该方法成功地应用于2018年4月9日南京市GF-2影像,结果显示南京市水体以U-FUI Ⅱ~U-FUI Ⅳ级水体为主,U-FUI的Ⅰ级、Ⅴ级和Ⅵ级水体在城市中的分布相对较少,空间分布特征与同期原位采样结果一致.     

一种改进的CSCA+PCA化工过程异常检测技术

为了解决化工过程异常检测时因参数众多且数据庞杂而导致一些异常无法被有效检出的问题,在Brownlee的克隆选择分类算法（CSCA）基础上,通过引入主成分分析（PCA）技术,进行数据降维和数据重整,探讨了人工免疫算法在化工过程异常检测中的适用效果和技术方案,以TE过程数据作为样本进行异常检测和分类实验。结果表明,过程异常数据的规模、属性的数目对CSCA异常检测效果具有明显影响,而通过主成分分析进行数据降维之后,CSCA检测效果有所提高;进一步的数据重整之后,CSCA对过程异常分类辨识的准确率可提升到85%以上;基于CSCA+PCA的数据降维及重构之后的过程异常检测技术方案,可以获得较高的异常检测准确率,从而一定程度上为化工过程安全运行提供技术保障。     

SPOT遥感数据在崇明东滩景观分类研究中的应用

以崇明东滩这一河口潮滩湿地为研究对象,利用ERDASIMAGINE图像处理软件,结合地面景观类型调查,对其1988年和2002年的SPOT遥感数据进行监督分类;对监督分类结果进行人机交互目视解译纠正,得到精度较高的崇明岛东部海岸带的景观图,并可此基础上进一步进行各种景观特征的定量分析和景观变化研究。最后讨论了不同研究目的对景观分类精度的要求,以及所采用信息源的分辨率能够划分至最细的景观要素类型。     

三峡库区武隆县滑坡灾害特点及成因机制

在大量实地调查和资料分析的基础上,主要研究了武隆县滑坡灾害的特点和成因机制。全县共有233处滑坡,滑坡体体积达1.36×108 m3,在重庆市和三峡库区都是属于滑坡灾害的重灾区。滑坡厚度分类以浅层滑坡和表层滑坡为主,物质组成分类以坡积层滑坡为主,滑坡体体积分类则以中型和小型滑坡为主。全县46个乡镇中41个有滑坡分布,总体分布不均。滑坡发育的基岩地层以页岩和泥岩最多,绝大多数滑坡发育在10°~30°的斜坡上。滑坡的成因机制主要表现在3个方面。易滑地层的广泛分布,即全县分布大量的泥岩、页岩等软弱岩层;地质构造及河流下切造成坡体结构的不稳定;暴雨和人为活动的诱发。     

构建基于GHS标准的黑头呆鱼(Pimephales promelas)急性毒性二元分类模型

鱼类急性毒性参数是进行化学品生态风险评估、分类标签等工作不可或缺的毒性指标。本文选取634个有机化学品对黑头呆鱼(Pimephales promelas)的急性毒性数据,并依据"全球化学品统一分类和标签制度"(GHS)中推荐的分类标准,将急性毒性值小于和大于100 mg·L-1的物质分别划分为有毒物质和无毒物质。以分类结果为建模指标,构建了基于欧几里德距离的K最近邻(k NN)二元分类模型。评估结果表明,模型训练集和验证集的预测准确度(Q)、敏感性(Sn)和特异性(Sp)参数均大于0.7,说明模型具有较好的预测能力。因而,在化学品分类标签工作中,可使用该模型预测缺失的鱼类急性毒性类别。     

基于卫星影像解译的华中地区自然景观分类与制图

依据１：１５０万中国卫星影像图并参考有关专题图件资料，通过景观组成要素分析法和专题图件对比分析法，拟定了华中地区自然景观分类系统并编制该区１：１５０万自然景观类型解译图，抽样检验表明，平均判对率达９０．５％。     

Establishing aquatic restoration priorities using a watershed approach

Since the passage of the Clean Water Act in 1972, the United States has made great strides to reduce the threats to its rivers, lakes, and wetlands from pollution. However, despite our obvious successes, nearly half of the nation's surface water resources remain incapable of supporting basic aquatic values or maintaining water quality adequate for recreational swimming. The Clean Water Act established a significant federal presence in water quality regulation by controlling point and non-point sources of pollution. Point-sources of pollution were the major emphasis of the Act, but Section 208 specifically addressed non-point sources of pollution and designated silviculture and livestock grazing as sources of non-point pollution. Non-point source pollutants include runoff from agriculture, municipalities, timber harvesting, mining, and livestock grazing. Non-point source pollution now accounts for more than half of the United States water quality impairments. To successfully improve water quality, restoration practitioners must start with an understanding of what ecosystem processes are operating in the watershed and how they have been affected by outside variables. A watershed-based analysis template developed in the Pacific Northwest can be a valuable aid in developing that level of understanding. The watershed analysis technique identifies four ecosystem scales useful to identify stream restoration priorities: region, basin, watershed, and site. The watershed analysis technique is based on a set of technically rigorous and defensible procedures designed to provide information on what processes are active at the watershed scale, how those processes are distributed in time and space. They help describe what the current upland and riparian conditions of the watershed are and how these conditions in turn influence aquatic habitat and other beneficial uses. The analysis is organized as a set of six steps that direct an interdisciplinary team of specialists to examine the biotic and abiotic processes influencing aquatic habitat and species abundance. This process helps develop an understanding of the watershed within the context of the larger ecosystem. The understanding gained can then be used to identify and prioritize aquatic restoration activities at the appropriate temporal and spatial scale. The watershed approach prevents relying solely on site-level information, a common problem with historic restoration efforts. When the watershed analysis process was used in the Whitefish Mountains of northwest Montana, natural resource professionals were able to determine the dominant habitat forming processes important for native fishes and use that information to prioritize, plan, and implement the appropriate restoration activities at the watershed scale. Despite considerable investments of time and resources needed to complete an analysis at the watershed scale, the results can prevent the misdiagnosis of aquatic problems and help ensure that the objectives of aquatic restoration will be met.