浅谈如何在生产过程中控制1：10000地形数据（DLG）的质量

主要叙述1:10 000矢量地形数据(DLG)在采集、编辑过程中如何控制质量,针对如何提高产品质量问题进行了简要探讨.     

GM(1,1)最佳维数建模法在露天矿边坡变形预测中的应用

露天矿边坡变形是一个复杂的系统,许多影响边坡变形的因素具有灰色信息性质,因此应用灰色模型对边坡变形进行预测是一种很好的研究手段。在灰色模型预测实践中,发现建模数据的维数对模型预测精度有较大影响。从变形预测精度研究入手,提出最佳维数建模法。通过实例应用证明,该法具有较高的预测精度和可信度。     

吉林省中部农业土壤中滴滴涕的残留特征

通过分析研究吉林省中部农业土壤中DDT的含量和组成,探讨了该区土壤中DDT的残留特征及其可能的生态风险。研究结果表明,吉林省中部农业土壤中普遍残留DDT,质量分数为0.384~54.159μg/kg,残留水平较低,土壤DDT同系物中以p,p’-DDT和p,p-’DDE为主。DDT的组成表明,土壤中DDT主要是过去输入环境的DDT及其降解产物,但近期仍有少量的DDT输入。生态风险评估则显示该区土壤中的DDT具有一定的生态风险,应予以重视。     

基于MapMatrix的输电线路工程DEM编辑应用

数字摄影测量系统(MapMatrix)能够广泛应用于低空摄影、高空摄影以及卫星遥感当中.输电线路工程覆盖范围广、地形复杂、对数字高程模型(Digital Elevation Model,DEM)精度要求高.结合具体的工程项目,利用MapMatrix软件中的DEMMatrix模块进行DEM的编辑,阐述具体操作过程中软件各功能的应用情况,进一步分析DEMMatrix模块在输电线路工程DEM编辑上的实用性.实验结果表明,利用MapMatrix能够较快、精确地完成DEM编辑工作.     

OBE理念下GIS空间分析课程思政教学设计与实践

以成果导向教育(Outcome Based Education,OBE)和课程思政理念为指导进行课程设计与实践,是地理信息科学专业应用型人才培养的发展趋势.围绕专业人才培养目标和课程教学目标,以反向设计为原则,结合专业毕业要求,确定课程学习成果,然后以成果为导向,设计实施教学改革,将思政元素有机融入专业教学中,培养学生综合素养.地理信息系统(Geographic Information System,GIS)方向的课程《GIS空间分析》是地理信息科学专业核心课程,探索和实施成果导向下的课程思政教学目标的达成,围绕教学目标进行有效的教学设计,结合课程内容从理论知识和实践操作两个层面进行课程思政教学融入设计,提出课程思政融入专业课教学的典型案例和实施路径,包括制定课程目标、确定学习成果、探索和实施新型教学方式、优化课程考核和评价方式等方面.     

基于土地适宜性评价与元胞自动机模型的城市开发边界划定方法

城市开发边界的划定可以在一定程度上引导城市空间的良性扩张。为了研究边界划定的方法,以我国某港口城市作为研究区域,在空间增长模拟的方向进行探索。研究中借助土地适宜性评价和元胞自动机边界工具,构建既符合生态资源环境要求又符合城市发展需要的边界划定,同时,为了实现城市用地健康和动态管控举措,提出了建立健全土地用地管理机制的要求。     

移动背景下测量学AR实训教材设计

针对传统测量实践教学过程中对于来源多样、格式迥异的学习资料未能有效进行组织的问题,提出了增强现实(Augmented Reality,AR)实训教材的设计思路.结合测量实践课程的特点和AR技术优势,针对学生的情感认知及书籍的信息负荷等方面,从课程内容的布局、虚实场景的结合及交互方式等几个方面对AR实训教材进行设计.实现了纸质教材与移动端课程内容的融合与实时交互,为移动背景下的数字资源与传统书籍的有机结合提供一种借鉴方法.     

预测陕西关中地区需水量的改进GM(1,1)模型

需水量评价与预测是水资源规划与管理一项重要的研究内容。本文采用定额法计算需水量。通过对陕西关中地区需水量要素组成的分析,认为需水量要素属平稳时间序列,且一阶累加生成数据系列满足指数规律,符合灰色预测条件。为了提高GM(1,1)模型的精度,采用一种改变背景值的新方法,即:中心逼近方法。通过精度检验,中心逼近式GM(1,1)模型平均误差百分比、误差平方和分别比传统的GM(1,1)模型提高了0.147和1.579。用中心逼近式GM(1,1)模型预测需水量各要素近期和中长期值,经检验,其中非农业人口、农业人口、耕地面积、工业总产值预测模型满足一级模型,等级为良好。牲畜头数预测模型为不合格模型,分析其原因,主要是因为时间序列数据不完全符合指数规律。通过定额法计算,预计75%保证率时2005年和2010年关中地区工农业需水量分别占总需水量的92.21%和89.75%,生活需水量分别占7%和9.04%。     

Geochemistry of porewater and sulfate-reducing bacteria in sediment cores from the Chianan Plain, Taiwan

High concentrations of arsenic and humic substances in groundwater from the southwestern coastal plain of Taiwan were well known for their probable relationships with black-foot disease. In order to realize the relationships between the concentrations of humic substances and arsenic in this area, 24 well water samples were analyzed. After filtered through 0.45 μm glass fiber membrane in the field, samples were kept in the dark at 4℃ and then separated into six fractions with varying range of molecular weight （〈0.5, 0.5-1, 1-5, 5-10, 10-50 and 〉50 k Da） by ultrafiltration apparatus （Molecular/Por Stirred Cell system） in the lab. Concentrations of humic substances were measured by fluorescence spectrometer （HITACHI F-2000, ex=370, em=445） and arsenic by FIAS-AA （Perkin Elmer AAnalyst 100, FIAS-400）. On average, only 6.2% of the total arsenic in water existed in the fraction of 〉0.5 k Da. and the others were complexed with humic substances （including humic acid and fulvic acid）. The results demonstrated a distinct positive correlation between the concentrations of humic substances and arsenic.     

Association between multi-level inorganic arsenic exposure from drinking water and skin lesions in Inner Mongolia, China

Arsenic is one of the most important single-substance toxicants in the environment. In Inner Mongolia of China, 300000 residents are believed to drink water containing 〉50 μg/L. Skin lesions have been known as the most common consequences resulting from chronic exposure to arsenic. To clarify the prevalence of arsenic-induced skin lesions, it is important to assess the impact of this problem on the target population, and to make future planning. We evaluated the association between multi-level inorganic arsenic exposure from drinking water and skin lesions in an arsenic-affected area in Inner Mongolia, China. 109 and 32 subjects fi＇om high-level arsenic-affected （〉5 μg/L） village and low-level （≤50 μg/L） village were recruited and had detailed physical examination with special emphasis on arsenic-related skin lesions. Arsenic exposure was measured for each participant with As concentration of primary well and the duration of using the well was recorded. Arsenic-induced skin lesions including keratosis, pigmentation, and/or leucomelanosis were diagnosed in 56 and 3 subjects in the two villages, respectively. Logistic regression was conducted to calculate prevalence-odd ratios of skin lesions by levels of arsenic exposure with adjustment of sex, age group, smoking and duration of exposure. A consistent dose-response relationship between arsenic exposure level and skin lesion risk was observed.