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| 1 | 基于多方法融合的张家界大鲵自然保护区功能分区研究显示文摘中国大鲵(Andrias davidianus)为两栖类野生保护动物,在淡水生态系统中扮演着重要的角色和功能,但目前探讨其自然保护区功能分区的研究较少。以张家界大鲵自然保护区为研究对象,综合考虑地理环境、人类活动和大鲵分布等因素,融合最小费用距离、空间统计学方法的Ripley′s K函数、核密度分析和Iso聚类等多种方法,对张家界市域内水域的地理空间数据进行分析,得到大鲵自然保护区范围和功能分区。结果表明:(1)聚类结果所处位置和河段符合大鲵生境要求,并通过野外实地调查加以验证;(2)保护区总面积为13 101 hm^2,其中核心区面积占保护区总面积的35.46%,缓冲区面积占35.73%,实验区面积占28.81%。功能分区结果考虑了大鲵水陆两栖特性,且符合生态和经济发展双重需要,对两栖类野生动物自然保护区功能分区研究具有一定的指导意义。 | 杨杰 黄磊 罗庆华 | 2019 | 生态与农村环境学报2019，35，7： | 6 |
| 2 | ST-CFSFDP:快速搜索密度峰值的时空聚类算法显示文摘时空聚类算法是地理时空大数据挖掘的基础研究命题。针对传统CFSFDP聚类算法无法应用于时空数据挖掘的问题,本文提出一种时空约束的ST-CFSFDP(spatial-temporal clustering by fast search and find of density peaks)算法。在CFSFDP算法基础上加入时间约束,修改了样本属性值的计算策略,不仅解决了原算法单簇集多密度峰值问题,且可以区分并识别相同位置不同时间的簇集。本文利用模拟时空数据与真实的室内定位轨迹数据进行对比试验。结果表明,该算法在时间阈值90 s、距离阈值5 m的识别正确率高达82.4%,较经典ST-DBCSAN、ST-OPTICS及ST-AGNES聚类算法准确率分别提高了5.2%、4.2%和7.6%。 | 王培晓 张恒才 王海波 吴升 | 2019 | 测绘学报2019，48，11： | 4 |
| 3 | 月表高程分布特征及其分级标准初探显示文摘月球是地球的唯一天然卫星,也是现阶段深空探测的主要天体。月表形貌研究有助于了解月球的状态、结构和组成,能够为探究月球起源和演化等科学问题提供直接、可靠的证据。与地貌分类相比,月貌研究起步较晚,发展较为缓慢。尽管月貌研究已取得了一定进展,但月球形貌分类过程中仍旧缺乏对于形貌指标,如高程等的应用,对于形貌特征的描述仍存在部分缺失。本文通过分析月球表面高程的整体特征以及月海、撞击坑、南极艾肯盆地等典型地质构造单元的高程特征,认为-2500 m等高线能够较好的区分月海内部区域;-1500 m等高线能够较好的区分月海区域与月陆区域;1000 m等高线与南极艾肯盆地边界拟合程度较好;3000 m等高线能够较好地突出月陆地区撞击坑的边界。在此基础上,提出以-2500 m、-1500m、1000 m、3000 m 4个高程值作为月球形貌分类体系中的高程分类标准,将月球表面划分为极低海拔、低海拔、中海拔、高海拔和极高海拔5个形貌类型。 | 刘樯漪 程维明 阎广建 王睿博 刘建忠 | 2022 | 地理学报2022，77，1： | 3 |
| 4 | Morphological differentiation characteristics and classification criteria of lunar surface relief amplitude显示文摘Lunar landforms are the results of geological and geomorphic processes on the lunar surface.It is very important to identify the types of lunar landforms.Geomorphology is the scientific study of the origin and evolution of morphological landforms on planetary surfaces.Elevation and relief amplitude are the most commonly used geomorphic indices in geomorphological classification studies.Previous studies have determined the elevation classification criteria of the lunar surface.In this paper,we focus on the classification criteria of the topographic relief amplitude of the lunar surface.To estimate the optimal window for calculating the relief amplitude of the lunar surface,we use the mean change-point method based on LOLA(Lunar Orbiter Laser Altimeter)Digital Elevation Model(DEM)data and SLDEM2015 DEM data combining observations from LOLA and SELenological and Engineering Explorer Terrain Camera(SELENE TC).The classification criterion of the lunar surface relief amplitude is then determined according to the statistical analysis of basic lunar landforms.Taking the topographic relief amplitudes of 100 m,200 m,300 m,700 m,1500 m and 2500 m as thresholds,the lunar surface is divided into seven geomorphic types,including minor microrelief plains(<100 m),minor microrelief platforms[100 m,200 m),microrelief landforms[200 m,300 m),small relief landforms[300 m,700 m),medium relief landforms[700 m,1500 m),large relief landforms[1500 m,2500 m)and extremely large relief landforms(≥2500 m).The minor microrelief plains are mainly distributed in the maria and the basalt filled floors of craters and basins,while the minor microrelief platforms are mainly in the transition regions between the maria and highlands.The microrelief landforms are mainly located in regions with relatively high topography,such as wrinkle ridges and sinuous rilles in the mare.The small relief landforms are mainly scattered in the central peak and floor fractures of craters.The medium relief landforms are mainly distributed in the transition regions between crater floors and crater walls,between crater walls and crater rims,between basin floors and basin walls,and between basin walls and basin rims.Large and extremely large relief landforms are mainly found along crater walls and basin walls.The classification criteria determination for assessing lunar surface relief amplitude described in this paper can provide important references for the construction of digital lunar surface geomorphology classification schemes. | DENG Jiayin CHENG Weiming LIU Qiangyi JIAO Yimeng LIU Jianzhong | 2022 | Journal of Geographical Sciences2022，32，11： | 0 |
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