Spatiotemporal correlation in WebGIS group-user intensive access patterns

Group-user intensive access to WebGIS exhibits spatiotemporal behaviour patterns with aggregation features and regularity distributions when geospatial data are accessed repeatedly over time and aggregated in certain spatial areas. We argue that these observable group-user access patterns provide a foundation for improved optimization of WebGIS so that it can respond to volume intensive requests with a higher quality of service and improve performance. Subsequently, a measure of access popularity distribution must precisely reflect the access aggregation and regularity features found in group-user intensive access. In our research, we considered both the temporal distribution characteristics and spatial correlation in the access popularity of tiled geospatial data (tiles). Based on the observation that group-user access follows a Zipf-like law, we built a tile-access popularity distribution based on time-sequence, to express the access aggregation of group-users with heavy-tailed characteristics. Considering the spatial locality of user-browsed tiles, we built a quantitative expression for the correlation between tile-access popularities and the distances to hotspot tiles, reflecting the attenuation of tile-access popularity to distance. Moreover, given the geographical spatial dependency and scale attribute of tiles, and the time-sequence of tile-access popularity, we built a Poisson regression model to express the degree of correlation among the accesses to adjacent tiles at different scales, reflecting the spatiotemporal correlation in tile access patterns. Experiments verify the accuracy of our Poisson regression model, which we then applied to a cluster-based cache-prefetching scenario. The results show that our model successfully reflects the spatiotemporal aggregation features of group-user intensive access and group-user behaviour patterns in WebGIS. The refined mathematical method in our model represents a time-sequence distribution of intensive access to tiles and the spatial aggregation and correlation in access to tiles at different scales, quantitatively expressing group-user spatiotemporal behaviour patterns with aggregation features and a regular distribution. Our proposed model provides a precise and empirical basis for performance-optimization strategies in WebGIS services, such as planning computing resource allocation and utilization, distributed storage of geospatial data, and providing distributed services so as to respond rapidly to geospatial data requests, thus addressing the challenges of volume-intensive user access.     

贵州省乡村贫困空间格局与形成机制分析

以贫困态势严峻、区域内部贫困差异大的贵州省为研究区,分析了贵州省区县层面乡村贫困的空间异质性和空间依赖性格局,定量测度了乡村贫困空间差异的影响因素和因素效应的空间差异性,进而归纳了贵州省乡村贫困的形成机制。结果发现,贵州省区县乡村贫困具有时空稳定性,呈现出东、南、西部高而中、北部低的“马蹄”形空间异质性格局。区县贫困存在较强的空间依赖性,“高-高”型贫困地域即空间贫困陷阱区域,集聚分布在贵州省的东南部、南部。定量模型发现,坡度、到所在市中心的距离、青少年人口占比、少数民族人口占比是导致贵州区县层面乡村贫困空间差异的显著因素,且这些因素的效应水平呈现出不同的空间模式。产业发展受限、劳动力流动性差、金融和人力资本积累不足是贵州贫困空间形成的主导机制。最后建议扶贫政策层面应将基于地方和基于人的政策相结合。     

黑河中游地区耕地景观演变及社会经济驱动力分析

选取1987~2010年的土地利用数据,运用变化轨迹分析方法以及景观指数表征黑河中游地区耕地景观的演变过程,采用偏最小二乘回归模型分析耕地景观演变的驱动力。结果表明：从耕地的变化轨迹来看,研究期间耕地的扩张是黑河中游地区耕地景观演变的主要趋势;从空间上来看,扩张型耕地和缩减型耕地分布趋向集中,主要集中在稳定型耕地边缘,同时耕地扩张的方向趋向河流;从驱动因素分析来看,总人口、城市化、产业发展、机电井数等是促使耕地景观演变的主要社会经济驱动因素,但是各个驱动因素的驱动作用均有差异。     

南疆铁路沿线地区城市化与土地利用相关分析

 以南疆铁路沿线的5个中心城市为基本单元,根据1993—2008年的城市化与城市建设用地结构方面的数据,分析了5个中心城市的城市化与城市建设用地之间的相关性。南疆铁路沿线5个中心城市目前的平均城市化率为48%,已进入了快速城市化发展阶段。研究结果表明,随着城市化的发展,城市建设用地结构也发生相应的变化。在用地结构中,居住用地、工业用地比例降低;公共设施用地、道路广场用地、绿地比例增加,仓储用地、对外交通用地和特殊用地比例呈现基本稳定趋势。城市建设的不断完善、城市化率的提高是促进建设用地结构变化的主要因素。     

Agricultural land use dynamics in the Brazilian Amazon based on remote sensing and census data

The potential impact of deforestation in the Brazilian Amazon on greenhouse gas emissions to the atmosphere calls for policies that take account of changes in forest cover. Although much research has focused on the location and effects of deforestation, little is known about the distribution and reasons for the agricultural uses that replace forest cover. We used Landsat TM-based deforestation and agricultural census data to generate maps of the distribution and proportion of four major agricultural land uses throughout the Brazilian Amazon in 1997 and 2007. We built linear and spatial regression models to assess the determinant factors of deforestation and those major agricultural land uses - pasture, temporary agriculture and permanent agriculture - for the states of Pará, Rondônia, and Mato Grosso. The data include 30 determinant factors that were grouped into two years (1996 and 2006) and in four categories: accessibility to markets, public policies, agrarian structure, and environment. We found an overall expansion of the total agricultural area between 1997 and 2007, and notable differences between the states of Pará, Rondônia, and Mato Grosso in land use changes during this period. Regression models for deforestation and pasture indicated that determinant factors such as distance to roads were more influential in 1997 than in 2007. The number of settled families played an important role in the deforestation and pasture, the effect was stronger in 2007 than 1997. Indigenous lands were significant in preventing deforestation in high-pressure areas in 2007. For temporary and permanent agricultures, our results show that in 1997 the effect of small farms was stronger than in 2007. The mapped land use time series and the models explain empirically the effects of land use changes across the region over one decade.     

2011—2020年黄淮海平原冬小麦低温冷害与气象要素变化的时空分析（英文）

黄淮海平原是我国典型的农田生态系统之一,频发的低温冷害对该区域的冬小麦种植业造成了巨大的经济损失。为了有效、大范围地监测冷害的时空变化情况及其气象成因,利用2005–2015年来源于气象站点的逐日最低气温和MODIS的NDVI和FPAR数据,结合逻辑回归模型构建了黄淮海平原冬小麦低温冷害监测模型,并分析了2011–2020年黄淮海平原冬小麦冷害的时空变化。将其与气象要素的时空变化进行相关性分析,了解气象要素对冬小麦低温冷害发生情况的影响。结果表明,2011–2020年冬小麦冷害的危害性逐渐降低,且冷害发生高概率、高频区域由北向南移动。同时,气象要素对冬小麦受害程度的影响从高到低分别为热量、降水和日照时长,但这些要素的影响具有一定的空间异质性。     

东北地区城市民生质量测度与空间分析

民生问题是当今中国政府和民众高度关注的热点问题,也是全面建成小康社会进程中需要迫切解决的关键科学问题。借鉴当代中国人的价值观结构,构建了民生质量评估指标体系,定量测度了东北地区34个地级市的民生质量指数,并采用ESDA和多元线性回归模型探讨其空间分异特征及其影响因素。研究结果表明：① 东北地区城市民生质量呈等级分布特征,且“两极分化”明显。② 经济实力、产业结构、城市化和地理邻近性对民生质量空间分异有重要影响。     

A Statistical Analysis of Trends for Warm and Cold Spells in Uppsala by Means of Counts

Statistical studies of extremes are of interest in the climatic sciences, in particular trends of periods of unusually warm or cold weather, which could be labelled warm and cold spells, respectively. We study the yearly number of spells in Uppsala, Sweden which from a data‐analytic point of view truly are counts, and employ theory and methods from the field of regression models for counts. A possible trend for the period 1840–2012 was investigated. The trend for warm spells is positive and demonstrated to be larger in magnitude compared with the one for cold spells, and is found to be statistically significant. The methodology could be extended to analyse other climate indicators.     

基于地貌单元的小区域地质灾害易发性分区方法研究

以汶川县城周边区域为研究区,分别以栅格单元与地貌单元作为单位评价单元,以信息量法与逻辑回归法两种评价模型对研究区进行地质灾害易发性评价分区。根据对评价结果的比较分析,在小区域范围内,基于地貌单元的区域易发性分区不仅仅能够更好地体现出区域内局部综合特性,而且评价分区结果与地质灾害实际分布情况更加吻合,分级层次更加明显,数学模型的适用效率很好。由此可见,在小范围区域内,基于地貌单元的地质灾害易发性评价分区具有良好的适用性与可塑性,在大比例尺地质灾害易发性和危险性制图中是一个有益的尝试与启发。     

鄱阳湖区南昌县血吸虫疫情空间分布及 其流行因素分析

南昌县是鄱阳湖沿岸血吸虫流行区最主要的区域之一,是江西省血防工作的重点区域。结合疫水接触强度、村内耕牛数量、村到鄱阳湖边界的距离、村内湖岸线的长度等数据,通过传统线性回归、空间滞后回归模型、空间误差回归模型研究了2009年南昌县血吸虫疫情空间分布特点及其流行因素。结果表明：1）2009年南昌县血吸虫疫情主要分布在东北、东南部鄱阳湖沿岸、赣江流域沿岸等村域,疫水接触强度空间分布与疫情分布具有明显的一致性;2）单因素分析表明村内居民的疫水接触强度、村内耕牛数量、村内湖岸线长度、村到鄱阳湖边界的平均距离与病人数都具有明显的相关性,其中病人数和行政村到鄱阳湖沿岸的距离呈负相关性;3）3种回归模型拟合结果表明居民的疫水接触强度、村内耕牛数量、村到鄱阳湖边界的距离是影响南昌县血吸虫病人数分布的主要因子,以上3个指标可以解释总变异的81%。