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61.
The development of groundwater favourability map is an effective tool for the sustainability management of groundwater resources in typical agricultural regions, such as southern Perak Province, Malaysia. Assessing the potentiality and pollution vulnerability of groundwater is a fundamental phase of favourability mapping. A geographic information system (GIS)-based Boolean operator of a spatial analyst module was applied to combine a groundwater potentiality map (GPM) model and a groundwater vulnerability to pollution index (GVPI) map, thereby establishing the favourable zones for drinking water exploration in the investigated area. The area GPM model was evaluated by applying a GIS-based Dempster–Shafer–evidential belief function model. In the evaluation, six geoelectrically determined groundwater potential conditioning factors (i.e. overburden resistivity, overburden thickness, aquifer resistivity, aquifer thickness, aquifer transmissivity and hydraulic conductivity) were synthesized by employing the probability-based algorithms of the model. The generated thematic maps of the seven hydrogeological parameters of the DRASTIC model were considered as pollution potential conditioning factors and were analysed with the developed ordered weighted average–DRASTIC index model algorithms to construct the GVPI map. Approximately 88.8 and 85.71% prediction accuracies for the Groundwater Potentiality and GVPI maps were established using the reacting operating characteristic curve method and water quality status–vulnerability zone relationship scheme, respectively. Finally, the area groundwater favourability map (GFM) model was produced by applying a GIS-based Boolean operator on the Groundwater Potentiality and GVPI maps. The GFM model reveals three distinct zones: ‘not suitable’, ‘less suitable’ and ‘very suitable’ zones. The area analysis of the GFM model indicates that more than 50% of the study area is covered by the ‘very suitable’ zones. Results produce a suitability map that can be used by local authorities for the exploitation and management of drinking water in the area. The study findings can also be applied as a tool to help increase public awareness of groundwater issues in developing countries.  相似文献   
62.
Bracken fern is one of the major invasive plants distributed all over the world currently threatening socio-economic and ecological systems due to its ability to swiftly colonize landscapes. The study aimed at reviewing the progress and challenges in detecting and mapping of bracken fern weeds using different remote sensing techniques. Evidence from literature have revealed that traditional methods such as field surveys and modelling have been insufficient in detecting and mapping the spatial distribution of bracken fern at a regional scale. The applications of medium spatial resolution sensors have been constrained by their limited spatial, spectral and radiometric capabilities in detecting and mapping bracken fern. On the other hand, the availability of most of these data-sets free of charge, large swath width and their high temporal resolution have significantly improved remote sensing of bracken fern. The use of commercial satellite data with high resolution have also proven useful in providing fine spectral and spatial resolution capabilities that are primarily essential to offer precise and reliable data on the spatial distribution of invasive species. However, the application of these data-sets is largely restricted to smaller areas, due to high costs and huge data volumes. Studies on bracken fern classification have extensively adopted traditional classification methods such as supervised maximum likelihood classifier. In studies where traditional methods performed poorly, the combination of soft classifiers such as super resolution analysis and traditional methods of classification have shown an improvement in bracken fern classification. Finally, since high spatial resolution sensors are expensive to acquire and have small swath width, the current study recommends that future research can also consider investigating the utility of the freely available recently launched sensors with a global footprint that has the potential to provide invaluable information for repeated measurement of invasive species over time and space.  相似文献   
63.
Macroalgae plays an important role in coastal ecosystems. The accurate delineation of macroalgae areas is important for environmental management. This study compared the pixel- and object-based methods using Gaofen satellite no. 2 image to explore an efficient classification approach. Expert system rules and nearest neighbour classifier were adopted for object-based classification, whereas maximum likelihood classifier was implemented in the pixel-based approach. Normalized difference vegetation index, normalized difference water index, mean value of the blue band and geometric characteristics were selected as features to distinguish macroalgae farms by considering the spectral and spatial characteristics. Results show that the object-based method achieved a higher overall accuracy and kappa coefficient than the pixel-based method. Moreover, the object-based approach displayed superiority in identifying Porphyra class. These findings suggest that the object-based method can delineate macroalgae farming areas efficiently and be applied in the future to monitor the macroalgae farms with high spatial resolution imagery.  相似文献   
64.
65.
Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.  相似文献   
66.
A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. To identify convective and stratiform clouds in different developmental phases, two-dimensional (2D) and three-dimensional (3D) models are proposed by applying reflectivity factors at 0.5° and at 0.5°, 1.5°, and 2.4° elevation angles, respectively. According to the thresholds of the algorithm, which include echo intensity, the echo top height of 35 dBZ (ET), density threshold, and ε neighborhood, cloud clusters can be marked into four types: deep-convective cloud (DCC), shallow-convective cloud (SCC), hybrid convective-stratiform cloud (HCS), and stratiform cloud (SFC) types. Each cloud cluster type is further identified as a core area and boundary area, which can provide more abundant cloud structure information. The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing, Xuzhou, and Qingdao. The results show that cloud clusters can be intuitively identified as core and boundary points, which change in area continuously during the process of convective evolution, by the improved DBSCAN algorithm. Therefore, the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification. Because density thresholds are different and multiple elevations are utilized in the 3D model, the identified echo types and areas are dissimilar between the 2D and 3D models. The 3D model identifies larger convective and stratiform clouds than the 2D model. However, the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds. In addition, the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.  相似文献   
67.
依据一种基于建筑用地比例和土地利用信息熵的城乡站点划分方法,将西安市环境与气象站点划分为城区、郊区和两类乡村站,讨论其PM2.5的城乡分布特征及与城市热岛效应强度(Urban Heat Island Intensity,UHII)间的相关关系。结果表明,不同季节西安市呈现不同的PM2.5城乡分布特征和日变化特征,两类乡村站点PM2.5差异明显且下风向乡村站点(乡村D)对应的UHIID对城区和乡村的影响程度大于上风向乡村站点(乡村U)对应的UHIIU。在城区较多本地排放的影响下,乡村PM2.5浓度与 UHIIU(或UHIID)相关系数均大于城区。随着UHIID的增加,城乡PM2.5相对浓度差值(RUPIID)整体呈下降趋势且UHIID与RUPIID在春夏秋季显著负相关。UHIID增大,城区近地面PM2.5的水平扩散能力减弱,但PM2.5的垂直扩散能力较乡村更强,从而UHIID通过影响PM2.5的传输扩散特征,进一步影响西安市RUPIID。  相似文献   
68.
The Swedish Geotechnical Society has adopted a general methodology for risk management in geotechnical engineering projects to reduce the costs related to negative outcomes of geotechnical risks. This technical note highlights the main features of the methodology and strives to inspire the international geotechnical community to apply sensible risk management methods. In the authors’ opinion, a successful geotechnical risk management needs to be structured, be tailored to the project, and permeate the engineers’ everyday work. Then, sufficient quality can be achieved in the project with larger probability.  相似文献   
69.
研究地球工程对海洋酸化的影响对于评估地球工程对全球气候和环境的影响有重要意义。文中使用中等复杂程度的地球系统模式,模拟了典型CO2高排放情景RCP8.5下,实施太阳辐射管理地球工程对海洋表面的pH和文石(碳酸钙的一种亚稳形态)饱和度的影响,并定量分析了各环境因子对海洋酸化影响的机理。模拟结果表明,在RCP8.5情景下,到2100年,相对于工业革命前水平,全球海洋表面平均pH下降了0.43,文石饱和度下降了1.77。相对于RCP8.5情景,2100年地球工程情景下全球海洋表面平均pH增加了0.003,而文石饱和度降低了0.16。地球工程通过改变溶解无机碳、碱度、温度等环境因子影响海洋酸化。相对于RCP8.5情景,实施地球工程引起的溶解无机碳浓度的增加使pH和文石饱和度均减小,碱度的增加使pH和文石饱和度均增大,温度的降低使pH增大而使文石饱和度减小。总体而言,太阳辐射管理地球工程可以降低全球温度,但无法减缓海洋酸化。  相似文献   
70.
胡林凯  崔东文 《水文》2018,38(6):65-71
为科学识别云南省16个州市最严格水资源管理区域类型,提出最优觅食算法(OFA)-投影寻踪(PP)识别模型。从最严格水资源管理用水总量控制红线、用水效率控制红线、纳污控制红线3个方面分别构建指标体系和分级标准,利用2015年云南省各州市指标数据及分级标准阈值分别构建基于"三条红线"的投影指标函数,采用OFA分别搜索最优投影向量,并计算各州市综合投影值和各分级标准阈值投影值,利用分级标准阈值投影值对各区域最严格水资源管理类型进行识别。结果表明,OFA-PP识别模型具有较好的识别效果,识别结果可为云南省实行最严格水资源管理制度提供参考。  相似文献   
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