Responses of landscape pattern of China’s two largest freshwater lakes to early dry season after the impoundment of Three-Gorges Dam

The effects of hydrologic cycle change (caused by human activity and global climate change) on ecosystems attract the increasing attention around the world. As a result of impounding of the Three Gorges Dam (TGD), climate change and sand mining, the dry season of Poyang Lake and Dongting Lake (China’s two largest freshwater lakes) came early after the TGD impoundment. It was the primary cause of the increasing need for sluice/dam construction to store water in the Lakes and attracted increasing attention. In this paper, we compared the landscape pattern between three hydrologic years with early dry season (EY) and three normal hydrologic years (NY) of each lake by remote sensing technology, to reveal the effect of early dry season on landscape pattern. The results showed that early dry season caused expanding of Phalaris to mudflat zone in Poyang Lake, while caused expanding of Carex to Phalaris zone and expanding of Phalaris to mudflat zone in Dongting Lake. In landscape level, there was no significant difference in landscape grain size, landscape grain shape, habitat connectivity and landscape diversity between EY and NY in the two lakes. While in habitat class level, there were significant changes in area of mudflat and Phalaris and grain size of mudflat in Poyang Lake, and in area of Carex, grain size of Phalaris and grain shape of Carex and Phalaris in Dongting Lake. These changes will impact migrating birds of East Asian and migratory fishes of Yangtze River.     

Automated delineation and characterization of drumlins using a localized contour tree approach

Drumlins are ubiquitous landforms in previously glaciated regions, formed through a series of complex subglacial processes operating underneath the paleo-ice sheets. Accurate delineation and characterization of drumlins are essential for understanding the formation mechanism of drumlins as well as the flow behaviors and basal conditions of paleo-ice sheets. Automated mapping of drumlins is particularly important for examining the distribution patterns of drumlins across large spatial scales. This paper presents an automated vector-based approach to mapping drumlins from high-resolution light detection and ranging (LiDAR) data. The rationale is to extract a set of concentric contours by building localized contour trees and establishing topological relationships. This automated method can overcome the shortcomings of previously manual and automated methods for mapping drumlins, for instance, the azimuthal biases during the generation of shaded relief images. A case study was carried out over a portion of the New York Drumlin Field. Overall 1181 drumlins were identified from the LiDAR-derived DEM across the study region, which had been underestimated in previous literature. The delineation results were visually and statistically compared to the manual digitization results. The morphology of drumlins was characterized by quantifying the length, width, elongation ratio, height, area, and volume. Statistical and spatial analyses were conducted to examine the distribution pattern and spatial variability of drumlin size and form. The drumlins and the morphologic characteristics exhibit significant spatial clustering rather than randomly distributed patterns. The form of drumlins varies from ovoid to spindle shapes towards the downstream direction of paleo ice flows, along with the decrease in width, area, and volume. This observation is in line with previous studies, which may be explained by the variations in sediment thickness and/or the velocity increases of ice flows towards ice front.     

安徽省A级旅游景区空间结构演变特征分析

选取安徽省2001年、2004年、2007年、2011年和2014年A级旅游景区为研究样本,系统分析全省近13年来A级旅游景区演变特征;运用最邻近点指数、地理集中指数、基尼系数、洛伦兹曲线和热点分析,探讨其空间分布类型、集中程度和均衡程度的演变特征。结果表明:2001年以来安徽省A级景区总量逐年上升,其中3A级和4A级旅游景区增加数量最多;A级旅游景区主要集中在皖中和皖南地区,整体上呈现"少—多—多"的格局;2007年以后,景区等级结构逐步形成以4A、3A、2A中间等级旅游景区为主,两端高级和初级旅游景区较少的纺锤型结构,趋于相对稳定、合理;全省A级景区空间分布类型从随机分布趋于聚集分布,同时地理集中指数表明各个时期在各地市分布愈加集中,基尼系数表明在三大地理区域中分布愈加集中不均衡,全省A级景区在2004—2014年十年间逐渐由景点分散和热点区域集聚不明显演变为以黄山市和合肥市为核心的多极热点区域。     

景观格局在地理国情综合统计分析中的应用——以三江自然保护区为例

为了研究景观格局在地理国情综合统计中的应用,本文以三江自然保护区为例,综合考虑景观格局指数的生态意义并对区域景观的总体结构、斑块特征、多样性及脆弱性进行综合统计分析。研究结果表明,通过景观格局分析可以有效了解区域生态环境状态及地表覆盖格局特征,为地理国情普查综合统计分析生态协调性专题定量化计算提供参考。     

An innovative GPS trajectory data based model for geographic recommendation service

Geographic services based on GPS trajectory data, such as location prediction and recommender services, have received increasing attention because of their potential social and commercial benefits. In this study, a Geographic Service Recommender Model (GSRM) is proposed, which loosely comprises three essential steps. Firstly, location sequences are obtained through a clustering operation on GPS locations. To improve efficiency, a programming model with a distributed algorithm is employed to accelerate the clustering. Secondly, in order to mine spatial and temporal information from the cluster trajectory, an algorithm (MiningMP) is designed. Last but not least, the next possible location to which the user will travel is predicted. An integrated framework of GSRM could then be constructed and provide the appropriate geographic recommendation service by considering location sequences as well as other related semantic information. Experiments were conducted based on real GPS trajectories from Microsoft Research Asia (182 users within a period of five years). The experimental results clearly demonstrate that our proposed GSRM model is effective and efficient at predicting locations and can provide users with personalized smart recommendation services in the following possible position with excellent performance in scalability, adaptability, and quality of service.     

皖江城市带植被NPP时空变化及其气候响应

针对现有植被净初级生产力研究对城市圈、城市带尺度缺乏关注的问题,基于MODIS遥感数据、地面气象资料等,利用改进的CASA模型,结合回归分析、相关分析等方法探究了2000—2013年皖江城市带植被NPP的时空变化及其对气候因子的响应,为区域生态环境质量评价提供参考。结果表明:近14年来,皖江城市带植被NPP总体呈增加趋势;不同土地利用类型NPP差异显著,林地草地耕地建设用地未利用土地水体;年NPP均值呈现由南部向西北部减少的空间分布特征;植被NPP年际变化率较小,介于±10gC·m-2·a-1范围内;温度是影响研究区植被NPP时空变化的主要气候因子。     

中印城镇化区域差异及城镇体系空间演化比较

中国和印度作为两个正在崛起的大国,发展历程较为相似,但发展路径和模式差异较大。两个国家政治制度、经济体系、发展环境等的显著差异已经吸引了学者的广泛关注,本文将从地理学视角出发,重点关注两国城镇化及城镇体系的区域差异和空间演化过程。以人口普查和联合国城市人口数据为基础,采用空间分析、参数估计、非参数估计等多种方法,对中印两国城镇化和城镇体系的空间特征进行系统的比较分析,结果表明：① 20世纪90年代以来,中国城镇化的区域差异由南北差异转变为沿海—内部差异,而印度南北差异的格局则基本稳定;② 从省（邦）级空间尺度来看,中国和印度的人口密度和城镇化率都呈现正相关关系,当城镇化率超过50%后,两者的相关性更为显著,但是近年来中国人口密度与城镇化率的相关性不断增强,而印度则呈现降低的趋势;③ 现阶段中印两国以大中城市为主的城镇体系符合位序—规模分布的特征,但是经济改革对于两个国家城镇体系空间演化的影响差异明显,改革使得中国城镇发展的主要驱动力由地理历史因素向经济系统空间结构转变,而印度城镇发展的驱动力始终是地理历史因素,经济改革甚至降低了经济系统空间结构对城镇发展的影响。     

不透水地表盖度视角下中美城市群空间结构对比——以“京津冀”与“波士华”为例

将城市不透水地表盖度产品应用于城市群空间结构研究具有重要价值。本文基于多源遥感数据提取了“京津冀”与“波士华”城市群近40年（1972-2011年）亚像元级不透水地表专题信息,构建了城市群空间结构对比分析数据集;并引入引力模型和景观格局理论,利用引力指数、景观格局指数以及空间结构参数等,采用地理信息系统空间分析方法,从城市群与城市两个尺度对城市群空间结构进行了对比研究。结果表明：① “京津冀”城市群不透水地表快速增长,而“波士华”城市群较为稳定;② “京津冀”城市群空间结构经历了城市孤立发展阶段、双核心城市群阶段、城市群组阶段以及城市群网络化阶段,“波士华”城市群空间结构较为稳定,空间结构呈现出“点—轴”带状分布;③ 中国城市不透水地表盖度“高—高”聚集区呈现出典型团块状“摊大饼”形态,而美国城市呈现出一种“多中心集聚、分散成组”的态势;④ “京津冀”城市群生态、生产与生活用地不透水地表面积占比均高于“波士华”城市群。最后,基于两国城市群空间结构的对比结果,从空间布局优化角度对“京津冀”城市群的发展提出了初步建议。     

中国老年人口分布的集疏格局及其形成机制

中国已全面进入快速老龄化社会,研究老龄人口空间集疏格局及形成机制,不仅是开展老龄人口空间研究的理论基础,也是指导面向老龄化社会城市更新问题的关键所在。选取地级以上行政单元为研究对象,基于五普、六普老年人口数据,采用老龄化率、集聚度和空间自相关等方法,定量分析2000年和2010年全国城市老年人口分布的集疏格局及空间关联。研究表明：全国地级以上城市总体处于老龄化中期水平,城市间老龄化空间分异较大,老年人口密集区城市主要分布在胡焕庸线以东,稀疏区城市则均位于胡焕庸线以西,这与总人口分布状况基本一致;高密区城市基本都分布在东部沿海地区,中密区主要分布在长三角、珠三角、中原、山东半岛、成渝和京津冀地区,为中国分布范围最广的老年人口集聚区;城市间人口老龄化存在较强的空间正相关特征,空间集聚状况有所增强,人口老龄化空间格局表现出以热点区为中心,逐渐向外围过渡的“中心—外围”结构;自然环境、经济环境、城市化建设、人口环境等是导致老年人口集疏格局的关键形成因素。     

A context-sensitive correlated random walk: a new simulation model for movement

Computational Movement Analysis focuses on the characterization of the trajectory of individuals across space and time. Various analytic techniques, including but not limited to random walks, Brownian motion models, and step selection functions have been used for modeling movement. These fall under the rubric of signal models which are divided into deterministic and stochastic models. The difficulty of applying these models to the movement of dynamic objects (e.g. animals, humans, vehicles) is that the spatiotemporal signal produced by their trajectories a complex composite that is influenced by the Geography through which they move (i.e. the network or the physiography of the terrain), their behavioral state (i.e. hungry, going to work, shopping, tourism, etc.), and their interactions with other individuals. This signal reflects multiple scales of behavior from the local choices to the global objectives that drive movement. In this research, we propose a stochastic simulation model that incorporates contextual factors (i.e. environmental conditions) that affect local choices along its movement trajectory. We show how actual global positioning systems observations can be used to parameterize movement and validate movement models and argue that incorporating context is essential in modeling movement.