遥感数据时空尺度对地理要素时空变化分析的影响

地理要素的时空变化分析对于了解和掌握地表的规律性有着重要的作用。利用地面站点观测、实地调查等传统方式获取数据,对地理要素进行时空变化分析是最常用的方法。但该类方法往往表现的是"点尺度"观测,不能在大尺度情况下准确地反映地表的时空变化信息。遥感卫星能以一定的时间间隔获得空间连续的对地"面尺度"观测数据,然而其特定的空间和时间分辨率使其获取的地表信息仍十分有限。同时地表的空间异质性和个别地表短时间内的快速变化,使得利用遥感数据对地理要素进行时空变化分析时,时空变化分析结果会随观测尺度而发生改变。本文从空间尺度和时间尺度两方面综述遥感数据时空尺度对地理要素的时空变化分析产生的影响和原因,并针对这些问题总结了减小时空尺度对结果不确定性影响的现行方法。可以通过多源遥感协同观测和反演、尺度转换、空间建模等方法减小空间尺度引起的不确定性;通过联合多时相遥感数据的方法减小时间尺度引起的不确定性。在实际应用中,应根据所观测地理要素的实际情况,综合分析选择合适的方法。     

土地环境“天—地—生”要素时空数据的组织方法

结合土地环境演变的空间、时间和属性特征,以"天—地—生"要素框架为研究模式,进行土地环境影响要素时空数据组织方法研究。基于"天—地—生"模式的土地环境要素时空数据模型表达了土地环境天、地、生要素的时空逻辑关系,反映了影响土地环境演变的多维要素之间的多层次关联关系,并能减少数据访问的复杂度,又确保地理实体对象中影响要素间的有机耦合作用。     

基于线平衡点的时空演化分析

时空演化分析是时空数据挖掘和知识发现的研究热点之一。为实现定量表达线要素地理属性的时空演化特征,在力矩平衡原理的基础上,提出一种基于线平衡点的时空演化分析定量表达方法。该方法将地理属性力矩定义为线要素上各点地理属性值与该点到平衡点的线上距离的向量乘积,然后利用物理学力矩平衡计算公式求得力矩平衡点的位置。当不同时刻各点的地理属性值发生变化时,平衡点位置亦随之不断移动,进而利用平衡点与均质平衡点的偏移向量以及相邻时刻之间平衡点的转移向量,定量地表达线要素地理属性的时空演化特征。最后,通过实验验证了该方法的可行性以及有效性。     

一种面向Stop/Move抽象的轨迹时空关系

从轨迹Stop/Move模型出发,基于Stop/Move对象来分析轨迹之间复杂的时空关系。首先扩展Stop/Move模型,提出关联于地理空间要素的时空关联Stop/Move模型,在此基础上,以Stop/Move对象为分析粒度,分析Stop/Move对象在地理空间中的拓扑关系,提出轨迹主体相对于地理空间要素的时空模式,接着从Stop-Stop、Stop-Move和Move-Move三方面重点研究轨迹时空模式之间的关联关系,最后以两个典型检索请求为例讨论该模式在轨迹时空关系分析方面的应用。     

面向地理空间信息的轨迹模型及时空模式查询

轨迹数据处理与分析是目前空间信息和数据库等相关领域的研究热点之一。本文从Stop-Move轨迹模型出发,通过集成地理空间上下文信息来建模轨迹数据,并研究轨迹时空模式的查询处理技术。首先分析Stop/Move对象与点/线/面地理空间要素之间的时空关联关系,据此提出显式表达该关联语义的地理关联轨迹模型,在此基础上利用关系-对象数据库技术,为地理关联轨迹模型设计独立于应用的关系模式,接着定义轨迹时空模式查询,并提出基于地理关联轨迹关系模式的SQL处理框架,最后以典型性检索请求为例,讨论分析位置-时间、位置-顺序和位置-关系等三类轨迹时空模式查询的纯SQL处理技术,并以样例轨迹数据验证了本文方法的可行性。     

面向对象的地籍时空过程表达与数据更新模型研究

对地籍时空数据库持续更新,保持地籍时空数据库的现势性、拓扑一致性和完整性是现代地籍管理的生命所在.通过分析地籍对象变更过程中各类要素的联动变更行为,结合面向对象建模技术与时空演变过程表达思想,建立契合人们思维的以过程为核心的地籍时空数据更新模型.模型制定符合地籍对象时空拓扑演变规律的变更规则,实现地籍要素、土地利用要素和房屋的联动更新,并在地籍管理系统REGIS中得到实现.     

利用时空立方体挖掘小微地震时空演变模式

挖掘分析小微地震的时空演变模式，可为地震灾害的分析与预报提供辅助决策参考。本文以四川地区的地震监测数据为基础，利用时空立方体融合地震点的空间、时间与属性数据，基于时空热点统计分析方法挖掘小微地震的时空冷热点分布模式。试验结果表明：在试验数据的时域内，四川地区小微地震的热点模式主要表现为连续热点、逐渐减少热点和振荡热点。冷点模式主要是连续冷点，且冷点覆盖范围比热点覆盖范围广。基于时空立方体的时空热点分析方法能够发挥时空统计学的优势，可有效挖掘分析小微地震的时空演变趋势。     

多级格网时空索引

在时空数据库中,地理实体模型包括地理对象空间信息和时态信息。为了快速查询实体的空间和时间信息,这就需要一个高效的时空索引机制。本文在分析和参考目前几种时空索引方法的基础上提出了一种新的时空索引方法———多级格网时空索引,并介绍了多级格网时空索引的算法。     

序列状态的林业资源时空数据模型研究

对林业地理实体时空演变过程进行分析,认为林业地理实体的演变总体上是渐变和突变交替的时空过程,而且各专题属性和空间分布的演变类型和演变频率不尽相同。在此基础上,提出由序列快照和事件方法组合而成的序列状态时空表达方法,以状态集表达时空对象在生命周期内的演化历程,并针对林业数据的特点,采用面向对象的数据组织方式设计了林业资源时空数据模型。模型可对不同演变类型进行组合,并实现了对渐变和突变的统一表达,另外,模型也允许采用不确定数据以加强对渐变过程的表达。通过原型系统验证了模型的可行性。     

基于时空主题模型的微博主题提取

已有地理主题模型没有考虑不同区域对微博主题影响程度的差异性,同时他们将时间要素离散化,难以得到连续时间上的微博主题强度。提出了一种顾及连续时间及区域影响力因素的时空主题模型。该方法将城市划分为多个区域,依据各兴趣点类型及数量对区域赋予权重以表达区域社会功能对微博主题的影响程度,基于稀疏增量式生成模型表达微博主题分布,利用Beta分布描述主题在连续时间中的强度,最终通过Gibbs采样得到时空主题模型各参数。实验表明,本文方法能发现连续时间上微博主题的演变,与已有地理主题模型相比,能更加准确地提取微博主题。     

一种基于对象和快照的混合地表覆盖时空数据存储模型

时空数据模型是数据库和时空数据分析研究热点之一。由于时空数据变化类型多、分析计算复杂及应用范围广,一种观点认为建立通用的时空数据模型具有高度复杂性。本文针对地表覆盖变化时空数据建库和时空分析应用需求,提出了基于对象和快照的混合时空数据模型。该模型用面向对象描述地表覆盖的斑块对象时空过程,组织管理斑块对象时空事件和空间、属性信息,同时用快照描述地表覆盖整体时空分布,组织管理栅格快照,两者通过基于时间和空间位置的逻辑关联关系形成混合模型。模型在表达对象自身变化的时空事件类型基础上,增加了不同分类对象之间互相转变的时空事件表达。该模型既可以用于对地表覆盖历史观测数据组织存储建库,又可以用于支持时空统计分析、时空演变模拟和时空数据挖掘。通过对黑龙江地区地表覆盖时空数据建库、查询检索、整体格局演变分析和斑块变化时空过程检索与表达的试验,验证了模型的有效性。     

烟台市海岸地区土地利用变化时空分异研究

海岸线的大规模开发利用活动,加剧了海岸带土地利用/覆被变化,这种变化因离海岸线距离的不同而呈现出明显差异。以烟台市海岸地区为例,利用遥感和GIS空间分析方法揭示这种因海岸区位差异引起的土地利用变化时空格局特征,以期为地方土地资源与海岸线资源合理开发利用提供参考。结果表明:①近20年来烟台海岸地区土地利用变化较为活跃,城镇和其他建设用地扩展明显;海岸区位深刻影响着海岸地区土地利用动态变化率和不同用地类型间的转移特征;②与海岸区位密切相关的自然地理条件和岸线开发利用活动,以及人口增加、经济增长、政策与管理因素是导致烟台海岸地区土地利用变化产生时空分异的主要因素。     

一种时空过程的梯形分级描述框架及其建模实例

以对象建模视图和事件模型为基础的自底向上的时空过程表达方法,缺少对地理时空现象的显式定义,在时空因果链的细化表达方面存在不足。本文设计一种时空过程的梯形分级描述框架STP-TRAP,对时空过程进行自顶向下的显式化建模和集成时空因果链的分级描述,并在事件模型基础上,通过引入约束关系描述扩展时空因果链的表达模式。土地利用变迁过程建模实例与土地利用管理信息系统的设计和实现证明,该框架对土地利用变迁时空过程表达效果较好,为土地利用变更数据管理提供了新的思路。     

时间序列空间数据可视化中有关问题的研究

就土地利用变化可视化这一实例 ,对时间序列空间数据可视化的图形关系分析和图形内插等问题进行了深入的研究 ,得出了土地利用变化中图形关系变化的四种基本形式 ,并针对这四种基本图形的变化情形研究出了相应的内插策略 ;在对现有的图形内插算法研究的基础上 ,提出了基于物理场模型的整体内插算法 ,该算法能够较好地解决文中的图形内插问题。     

An assessment of the impact of urbanization and land use changes in the fast-growing cities of Saudi Arabia

Understanding rates, patterns and types of land use and land cover (LULC) changes are essential for various decision-making processes. This study quantified LULC changes and the effect of urban expansion in three Saudi Arabian cities: Riyadh, Jeddah and Makkah using Landsat images of 1985, 2000 and 2014. Seasonal change of vegetation cover was conducted using normalised difference vegetation index, and object-based image analysis was used to classify the LULC changes. The overall accuracies of the classified maps ranged from 84 to 95%, which indicated sufficiently robust results. Urban area was the most changed land cover, and most of the converted land to urban was from bare soil. The seasonal analysis showed that the change of vegetation cover was not constant due to climatic conditions in these areas. The agricultural lands were significantly decreased between 1985 and 2014, and most of these lands were changed to bare soil due to dwindling groundwater resources.     

Soil characterization based on land cover heterogeneity over a tropical landscape: an integrated approach using earth observation data-sets

Soil is a vital part of the natural environment and is always responding to changes in environmental factors, along with the influences of anthropogenic factors and land use changes. The long-term change in soil properties will result in change in soil health and fertility, and hence the soil productivity. Hence, the main aim of this paper focuses on the analysis of land use/land cover (LULC) change pattern in spatial and temporal perspective and to present its impact on soil properties in the Merawu catchment over the period of 18?years. Post classification change detection was performed to quantify the decadal changes in historical LULC over the periods of 1991, 2001 and 2009. The pixel to pixel comparison method was used to detect the LULC of the area. The key LULC types were selected for investigation of soil properties. Soil samples were analysed in situ to measure the physicochemical soil properties. The results of this study show remarkable changes in LULC in the period of 18?years. The effect of land cover change on soil properties, soil compaction and soil strength was found to be significant at a level of <0.05.     

遥感和GIS技术应用于伊拉克南部Basrah省土地利用/覆盖变化及城市扩张研究(英文)

In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km² in 1990 to 3 794.9 km² in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of “returning farmland to transportation and huge expansion in military camps” was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time. Supported by the Al-Basrah University, Iraq, the Geo-information Science and Technology Program (No. IRT 0438)China).     

土地利用视角空气污染空间分异的地理分析

针对土地利用/覆盖（land-use and land-cover,LULC）方式是否影响城市空气污染空间分异特征形成的问题,利用遥感技术和景观生态学方法分别获取长株潭城市群核心城区LULC及其景观格局,绘制空气污染物浓度与气象影响因子空间分异图,引入地理探测器定量分析土地因子在融合气象要素前后对NO₂、PM₁₀、O₃、PM_2.5浓度空间分布差异的贡献强度。结果表明,建设用地面积比例越高,林地越低,NO₂、PM_2.5浓度越高,O₃越低。非建设用地区域,污染物浓度随着土地景观格局破碎度、多样性指数值增大而升高,建设用地区域反之。LULC和土地景观格局的复合因子贡献力（P0.03~0.28）高于两者任意单独因子贡献力（P:0.01~0.11）,融合气象要素后,LULC对空气污染物空间分异特征形成的因子贡献力（P:0.18~0.53）显著增强。     

基于时空自相关的建筑物变化检测

针对传统基于像素级的变化检测方法在变化分析中难以利用像元间的时空关系、变化检测结果精度低的问题,提出了一种基于时空自相关的建筑物变化检测方法。首先,利用形态学建筑指数(Morphological Building Index,MBI)进行建筑物提取,并通过长宽比、面积等剔除道路信息优化建筑物提取;其次,采用时空自相关模型分别构建两期MBI特征影像的时空自相关性指标值作为对应像元的相似性测度;最后,利用最大类间方差(otsu)法确定最优阈值,得到变化检测结果。实验表明,该方法所得变化检测结果更完整,漏检率和误检率均低于对比算法,该方法基本满足变化检测需求,为高分影像建筑物变化检测提供一种新的技术手段。     

Investigating relationships between Landsat-7 ETM data and spatial segregation of LULC types under shifting agriculture in southern Cameroon

This paper investigates statistical relationships between land use/land cover (LULC), Landsat-7 ETM⁺ imagery and landscape mosaic structure in southern Cameroon where the conversion of tropical rain forest to shifting cultivation leads to dynamic processes, acting on the spatial aggregation of various LULC types. A Global Positioning System (GPS) was used in the field to identify a total of 171 shifting cultivation patches representing eight LULC types in two sub-areas. Because of the lack of a cloud-free image for the date of field sampling, the ETM⁺ imagery was acquired 2 months after field survey, during which it was assumed that no significant changes in LULC occurred (all dry season). Per pixel correlations were developed between spectral reflectance data, vegetation indices and LULC. As an exploratory study, several statistical methods (analysis of variance, means separations (Tukey HSD), principal component analysis (PCA), geo-statistical analysis, image classification and landscape metrics) were applied on point data and sensor images for evaluating the spatial variability within the landscape. Most variables explained 30–72% of LULC variation in the whole dataset. Those variables with high information content of LULC (infrared bands 4, 5, 7 and derived indices and PC1) also showed long ranges (6 km) spatial dependence as compared to those varying only within 1 km range. The results of these statistical analyses suggested the need to group some LULC types and the application of the Maximum Likelihood Classifier (MLC) for supervised classification provided a LULC map with the highest accuracy (81%) after consolidation of perennial LULC types, such as bush fallow, forest fallow and cocoa plantations. Landscape metrics computed from this map showed a high level of patch diversity and connectivity within the landscape and provided input data that can further be used to simulate predictive maps as substitute to cloud-covered sensor imageries. Landsat-7 ETM⁺ imagery proved to be useful in discriminating (with about 80% accuracy) the most dynamic LULC types such cropped plots and young fallow patches (shifting every season) and the extension front of the agricultural landscape.