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61.
生活垃圾对环境的污染评价方法探讨   总被引:5,自引:0,他引:5       下载免费PDF全文
生活垃圾对环境的污染,主要表现为垃圾渗滤液对地面水、地下水、土壤等的污染。其污染评价涉及污染物指标、污染物标准值的确定和计算模式的建立等内容。本文在总结现行环境指数评价法的基础上,探讨性地提出一套将基于生活垃圾填埋场环境监测技术标准(CJJ/T3037—95)中涉及地面水、地下水、土壤等的相关监测项和垃圾中的其他常见重要污染物,一并确定出的污染评价指标,再根据相关有毒物急性毒性分级,结合阈限值和部分浸出毒性鉴别标准值等分为5类污染指标。并在污染物的标准值确定后,进行对应于5类污染物的不同数学模式计算,得到5个分类污染指数,再比较判别这5个分类污染指数,选出最大者作为总污染指数的组合型评价垃圾污染的方法。经实例应用分析,该方法对各种污染物数据分布情况的适宜性优于现行其他常用方法。  相似文献   
62.
大连城市绿地可达性对房价影响的差异性分析   总被引:6,自引:5,他引:1  
杨俊  鲍雅君  金翠  李雪铭  李永化 《地理科学》2018,38(12):1952-1960
研究房价、遥感影像等多源数据,采用邻域分析法和地理加权回归模型分析大连市中山区绿地可达性及其与房价之间的空间相关性。结果表明: 房价均价14 745.35元/m2,呈环状分布,由沿海向内陆衰减、桂林街道起中心向外围递减; 研究区内可达性最好的绿地类型是街旁绿地,绿地可达性总体水平最高街道是桂林街道;公园绿地可达性最好的住宅区分布在昆明街道和桃源街道,街旁绿地可达性最好的住宅区分布在桂林街道,附属绿地可达性最好的分布在老虎滩街道,其他绿地可达性最好的分布在桃源街道。 不同类型绿地可达性对房价影响作用程度递减排序为:附属绿地、街旁绿地、公园绿地和其他绿地;附属绿地、街旁绿地和其他绿地与房价呈现空间正相关,随着到达绿地距离降低,房价呈现增长趋势;公园绿地与房价呈现负相关,随着到达公园绿地的距离降低,房价呈现衰减趋势。  相似文献   
63.
房产测量若干问题的解决方案   总被引:1,自引:0,他引:1  
房产测量外业数据采集及面积计算是影响房产测量精度的重要因素,就实际工作中在这两个方面容易出现的问题提出了相应的解决方法。  相似文献   
64.
The key parameters of houses such as distribution, area and height play an important role for urban-rural planning, earthquake emergency and disaster mitigation. The computer automatic extraction method is an effective way to acquire large area house information using satellite-borne or airborne optical remote-sensing images. However, because of the similarity of spectral characters for different land cover types or the influence of snow coverage, the classification accuracy of house type using traditional spectral based method can be decreased. To acquire the accurate houses distribution, a method based on the height information is proposed using unmanned aerial vehicle(UAV)in this study. With UAV flying at the height of 100m above ground, the route of the UVA was planned with the heading direction overlap of 77% and side direction overlap of 50%for the nearby pictures. Taking Qionghalajun Village in Xinjiang Uygur Autonomous Region for example, 69 pictures of the study area were obtained with DJI Phantom 3 professional. With those pictures input into the EasyUAV software, the Digital Elevation Model(DEM), Digital Surface Model(DSM), and Digital Orthophoto Map(DOM)were acquired based on photogrammetry method using the overlapped optical remote-sensing images of UAV. After that, the house distribution and height were acquired with the differences between DSM and DEM images larger than 2.6m. To eliminate the influences of disintegrated pixels on the house extraction, mainly caused by the trees or noise point, the classification aggregation tool of ENVI software was used with the disintegrated pixels' area less than 4m2. Compared with visual interpretation result, the user accuracy and mapping accuracy of the house extraction method proposed in this study is 88.69% and 97.42%, respectively. In addition, to evaluate the performance of the proposed method, the result of traditional supervised classification method using DOM data acquired previously was compared with the result of new method. The results show that the new method is more accurate the user accuracy and mapping accuracy of the supervised classification method, which is 43.23% and 85.30%, respectively. Besides the study area in this study, the performance of the proposed method will be evaluated at the other places in the further study.  相似文献   
65.
Earthquake events are one of the most extraordinarily serious natural calamities, which not only cause heavy casualties and economic losses, but also various secondary disasters. Such events are devastating, and have far-reaching influences. As the main disaster bearing body in earthquake, buildings are often seriously damaged, thus it can be used as an important reference for earthquake damage assessment. Identifying damaged buildings from post-earthquake images quickly and accurately is of real importance, which has guidance meaning to rescue and emergency response. At present, the assessment of earthquake damage is mainly through artificial field investigation, which is time-consuming and cannot meet the urgent requirements of rapid emergency response. Markov Random Field(MRF)combines the neighborhood system of pixels with the prior distribution model to effectively describe the dependence between spatial pixels and pixels, so as to obtain more accurate segmentation results. The support vector machine(SVM)model is a simple and clear mathematical model which has a solid theoretical basis; in addition, it also has unique advantages in solving small sample, nonlinear and high-dimensional pattern recognition problems. Thus, in this paper, a Markov random field-based method for damaged buildings extraction from the single-phase seismic image is proposed. The framework of the proposed method has three components. Firstly, Markov Random Field was used to segment the image; then, the spectral and texture features of the post-earthquake damaged building area are extracted. After that, Support Vector Machine was used to extract the damaged buildings according to the extracted features. In order to evaluate the proposed method, 5 areas in ADS40 earthquake remote sensing image were selected as experimental data, this image covers parts of Wenchuan City, Sichuan Province, where an earthquake had struck in 2008. And in order to verify the applicability of this method to different resolution images, an experimental area was selected from different resolution images obtained by the same equipment. The experimental results show that the proposed method has good performance and could effectively identify the damaged buildings after the earthquake. The average overall accuracy of the selected experimental areas is 93.02%. Compared with the result extracted by the widely used eCognition software, the proposed method is simpler in operation and can improve the extraction accuracy and running time significantly. Therefore, it has significant meaning for both emergency rescue work and accurate disaster information providing after earthquake.  相似文献   
66.
墙体开洞影响下房屋砖砌体结构地震易损性分析   总被引:2,自引:0,他引:2       下载免费PDF全文
为获取可靠的墙体开洞影响下房屋砖砌体结构地震易损性分析结果,采用ABAQUS有限元分析软件构建房屋砖砌体结构墙体模型,设置合理的墙体模型参数和数值模拟参数;对比模拟数值与以往研究的测试值,证明所构建模型参数取值合理;将截取的峰值段江油地震波作为上述模型的地震动输入,根据测得的房屋砖砌体结构的力学变化数据,分析房屋砖砌体结构的地震易损性。分析结果表明:地震情况下,随着墙体开洞率的增加,墙体荷载能力下降、墙体水平承载力增长幅度降低、墙体相对刚度退化率增加;墙体开洞数量越多,房屋砖砌体结构侧向刚度下降越快。因此分析得出墙体开洞率大、墙体开洞数量多,房屋砖砌体结构的地震易损性越显著。  相似文献   
67.
木构架承重-空斗墙围护民居大量分布在我国南方农村地区,该类民居整体性较差,历次地震中该类民居破坏较严重。采取高延性混凝土ECC面层加固围护空斗墙,扁钢、角钢及薄钢板增强木构架节点,穿墙钢筋捆绑木构架与围护墙体等加固措施。设计了1/2缩尺模型进行振动台试验,通过调整输入地震波峰值加速度来考虑不同水准地震烈度,分析了围护空斗墙损伤,探讨了模型频率与阻尼比变化特性,对比了围护空斗墙体与木构架加速度放大系数和位移包络值,并验证了二者在地震中的变形协调性。试验结果表明:(1)围护墙体仅在外侧出现明显裂缝,内侧ECC面层与墙体始终未脱离且未出现裂缝,围护墙整体性仍可得到一定保障;(2)木构架与钢加固件连接部位仅发生轻微破坏,木构架没有出现明显损伤;(3)木构架与围护墙体之间出现滑移,整体上二者协同抗震变形性能良好。该系列措施的加固效果较理想,适用于该类民居的抗震加固。  相似文献   
68.
汶川地震应急监测评估方法研究   总被引:8,自引:3,他引:8  
以汶川地震灾害应急遥感监测评估过程为例,介绍了利用遥感技术等手段对巨灾灾情进行应急监测评估的技术方法,并重点对四川、陕西和甘肃3省受灾较重的152个县(市、区)进行了应急评估.结果表明,汶川地震房屋倒损严重,受灾人口分布点多面广,受灾程度总体上与断裂带分布呈明显对应关系,山区受灾重于平原,农村重于城镇.四川省汶川、北川、青川、绵竹等12个县(市、区)受灾极为严重,甘肃省文县和陕西省勉县等受灾相对较重,利用地面调查数据验证,证明了评估结果具有较高的准确性.提出了基于遥感数据研判、空间分析外推技术的自下向上、逐级汇总的应急评估技术路线,能够发挥遥感数据的优势,也能保证应急评估的时效性,同时有利于组织大规模协同运行与综合结果生成,具有良好的科学性和可操作性,特别适合于巨灾灾情遥感应急评估工作.  相似文献   
69.
渤中34-2油田P10井为一口调整井,属于正常温度、压力系统,孔隙度较低,近井带污染比较严重,完井射孔方式采用复合射孔。针对射孔作业中出现减震器上端油管挤瘪、RTTS封隔器水力锚和胶筒损坏、点火棒卡于封隔器芯管内等现象,从管柱设计、负压选择、管柱材质、现场施工管理等方面对此次事故进行分析,并提出相关建议,对射孔作业中类似事故的应对及处理有一定的指导意义。  相似文献   
70.
本文对花卉塑料大棚夏季降温试验进行了分析,结果表明:采用直接阻挡太阳辐射的降温方法、棚膜外或棚膜内地面喷水的降温方法,其降温效果均好。这为成都地区花卉塑料大棚周年生产的科学管理提供了依据。  相似文献   
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