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31.
根据2018年4月(春季)和10月(秋季)在舟山群岛外海域进行的渔业资源调查资料,分析了鱼类的种类组成、数量分布和优势种,并用典范对应分析方法分析了其与水文环境之间的关系。结果表明,舟山群岛外海域鱼类有106种,隶属于12目47科80属,春、秋季鱼类质量密度分别为210.50 kg/km2和829.06 kg/km2,尾数密度分别为8.08×103 ind/km2和165.94×103 ind/km2。春季鱼类资源密度在调查海域的西北部较高,东部较低,而秋季鱼类资源密度在东部海域较高,西北部海域较低。两个季节的鱼类优势种更替明显,春季优势种为黄鮟鱇(Lophius litulon)、日本红娘鱼(Lepidotrigla japonica)、细条天竺鲷(Apogon lineatus),秋季为细条天竺鲷、日本发光鲷(Acropom japonicum)。鱼类种数呈现显著的季节和空间变化,但是都以西部以及西北部靠近近岸岛屿的海域种类数较高,大部分鱼类栖息在50~80 m水深海域。典范对应分析结果表明,表层温度、底层温度、表层盐度是影响调查海域鱼类种类组成和数量分布的主要环境因子。 相似文献
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Pinus taiwanensis is a species endemic to China. This study selected four typical plots of Pinus taiwanensis in the natural secondary forest around Macheng City, in order to reveal the characteristics of and the relationships between different diameter classes (determined based on the diameter at breast height or DBH), forest densities and species diversity, as well as the similarities of species diversity of different plots within the community. The result showed that Pinus taiwanensis was the dominant species in the community. The ratio of Pinus taiwanensis trees of diameter class IV reached a peak of 19.46% of the total followed by diameter class VII at 18.92%. The study recorded 156 species of vascular plants from 130 genera of 71 families; Pinus taiwanensis was the dominant species in the community. When the forest density was 1200 trees ha -1 with the largest average diameter of DBH=36.779±4.444 cm, the diversity (Shannon index H'=1.6716) and the evenness (Pielou index E=0.6727) of the tree layer was the highest. When the forest density reached 1525 trees ha -1 with the lowest average diameter of DBH=18.957±5.141 cm, the richness (Dma=5.4308), the diversity (H'=2.9612) and the evenness (E=0.8985) of all shrub layers climbed to the maximum. When the forest density was 1325 trees ha -1, the richness (Dma=5.8132), the diversity (H'=3.0697) and the evenness (E=0.9025) of all herb layers peaked. In terms of vertical structure, the average diversity indexes were herb layer>shrub layer>tree layer. High canopy density weakened light intensity in the community, causing a reduction in the species diversities of herbs and shrubs. The average similarity coefficient between the sample plots was 0.3356, which was at the medium dissimilarity level. External disturbances and improper management were major contributors to the low species diversity of the community. The implementation of scientific management measures is urgently needed to optimize the forest structures of Pinus taiwanensis, create a benign community environment, and promote species diversities and establish a stable forest community structure. 相似文献
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移动轨迹聚类方法研究综述 总被引:6,自引:2,他引:4
轨迹数据是人类移动行为的表征,能够映射出人的出行模式和社会属性等信息。怎样有效挖掘轨迹数据蕴藏的人类活动规律一直是研究的热点。通过轨迹聚类发现行为相似的类簇,从而探究群体的移动模式是轨迹挖掘和深度应用常见的方法之一。本文首先根据轨迹数据的特点,将轨迹数据模型分为轨迹点模型和轨迹段模型,并据此定义相应的相似性度量:空间相似性度量和时空相似性度量;然后,对两类模型的聚类方法进行了综述,并总结不同聚类算法的优缺点,以期为不同应用选取聚类算法提供科学依据;最后对移动轨迹数据聚类方法研究的发展趋势进行了讨论。 相似文献
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Identification of Convective and Stratiform Clouds Based on the Improved DBSCAN Clustering Algorithm
Yuanyuan ZUO Zhiqun HU Shujie YUAN Jiafeng ZHENG Xiaoyan YIN Boyong LI 《大气科学进展》2022,39(12):2203-2212
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
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为研究导热系数与影响因素之间的相关关系,建立导热系数的推算公式,以长春地区粉质黏土为研究对象,对原状土样的导热系数与其物理参数之间的相关性进行回归分析。制作9个重塑土样,测其相关的参数值,以验证回归方程的适用性。结果表明,回归分析建立导热系数与2个物理参数之间的关系式不成立;考虑天然密度、含水率和孔隙度为自变量,其分别对应的相关性系数T检验显著值(Sig)都0. 05,复决定系数为0. 886,建立的回归方程成立,自变量能准确解释因变量的变化,且含水率与导热系数呈负相关,天然密度和孔隙度呈正相关。重塑土样相关参数代入回归方程得到的导热系数值与实验实测值之间相对误差低于4%,验证了该回归方程的普遍性和适用性。 相似文献
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夜间经济是一个城市经济发展和消费水平的重要表征。目前国内外研究者对夜间经济的研究多停留在理论层面,或基于市场调研和问卷调查的小范围精细化研究。本文融合多源数据为夜间经济提供了新的视角,相较于传统的调查数据,具有更加快速、高效、广泛的特点,适合于夜间经济大范围研究。本文基于夜间灯光、POI、OD流等多源数据,采用DBSCAN、K-Means++等空间聚类算法和研究供需关系的盈亏法,分别从消费者角度和商户角度识别厦门市夜间活动热点区域和夜间服务设施分布区域,分析厦门市夜间经济时空分布格局及相关性。研究表明:① 厦门市夜间活动在空间上呈多环状分布并向四周递减,夜间活动热点区域分布受假期的影响因地而异;② 厦门市部分区域已有服务设施未能很好地服务于夜间经济,现有的照明、夜景等夜间灯光基础设施存在供给不足之处;③ 居住人口密度与夜间活动密度呈中度正相关,研究结果具有有效性,夜间服务设施盈亏值及数量、夜间灯光与夜间活动密度呈中、弱度相关,并且餐饮设施更加依赖于夜间灯光。最后,为厦门市未来夜间经济建设提出了根据不同的消费人群和心理提供不同的夜间服务、加强夜间灯光基础设施建设以及市场扶持的举措。研究结论对促进社会就业、增强基础设施使用率有积极意义,同时也能够为城市夜间经济发展和政策制定提供参考。 相似文献