Research on spatial calculating analysis model of landuse change

The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we can evaluate the numerical model and dynamic degree model for calculating land-use change rates. Furthermore, the paper raises the possibility of revising the calculating analysis model of spatial information in order to predicate more precisely the dynamic changing level of all types of land uses. In the most concrete terms, the model is used mainly to understand changed area and changed rates (increasing or decreasing) of different land types from microcosmic angle and establish spatial distribution and spatio-temporal principles of the changing urban lands. And we will try to find out why the situation can take place by combining social and economic situations. The result indicates the calculating analysis model of spatial information can derive more accurate procedure of spatial transference and increase of all kinds of land from microcosmic angle. By this model and technology we can conduct the research of land-use spatio-temporal structure evolution more systematically and more deeply, and can obtain a satisfactory result. The result will benefit the rational planning and management of urban land use of developed coastal areas in China in the future.     

Geography Education: The Glass Is Half Full and It's Getting Fuller

This article examines the recent progress of geography education as an academic subfield of geography and as an area of activity in K–12 education. Challenges to both endeavors are described. A restructuring of geography education's research program that focuses on spatial thinking and reasoning and merges applied and theoretical research is proposed.     

Effects of spatially structured vegetation patterns on hillslope erosion in a semiarid Mediterranean environment: a simulation study

A general trend of decreasing soil loss rates with increasing vegetation cover fraction is widely accepted. Field observations and experimental work, however, show that the form of the cover‐erosion function can vary considerably, in particular for low cover conditions that prevail on arid and semiarid hillslopes. In this paper the structured spatial distribution of the vegetation cover and associated soil attributes is proposed as one of the possible causes of variation in cover–erosion relationships, in particular in dryland environments where patchy vegetation covers are common. A simulation approach was used to test the hypothesis that hillslope discharge and soil loss could be affected by variation in the spatial correlation structure of coupled vegetation cover and soil patterns alone. The Limburg Soil Erosion Model (LISEM) was parameterized and verified for a small catchment with discontinuous vegetation cover at Rambla Honda, SE Spain. Using the same parameter sets LISEM was subsequently used to simulate water and sediment fluxes on 1 ha hypothetical hillslopes with simulated spatial distributions of vegetation and soil parameters. Storms of constant rainfall intensity in the range of 30–70 mm h^?1 and 10–30 min duration were applied. To quantify the effect of the spatial correlation structure of the vegetation and soil patterns, predicted discharge and soil loss rates from hillslopes with spatially structured distributions of vegetation and soil parameters were compared with those from hillslopes with spatially uniform distributions. The results showed that the spatial organization of bare and vegetated surfaces alone can have a substantial impact on predicted storm discharge and erosion. In general, water and sediment yields from hillslopes with spatially structured distributions of vegetation and soil parameters were greater than from identical hillslopes with spatially uniform distributions. Within a storm the effect of spatially structured vegetation and soil patterns was observed to be highly dynamic, and to depend on rainfall intensity and slope gradient. Copyright © 2005 John Wiley & Sons, Ltd.     

The role of vegetation patterns in structuring runoff and sediment fluxes in drylands

The dynamics of vegetation‐driven spatial heterogeneity (VDSH) and its function in structuring runoff and sediment fluxes have received increased attention from both geomorphological and ecological perspectives, particularly in arid regions with sparse vegetation cover. This paper reviews the recent findings in this area obtained from field evidence and numerical simulation experiments, and outlines their implications for soil erosion assessment. VDSH is often observed at two scales, individual plant clumps and stands of clumps. At the patch scale, the local outcomes of vegetated patches on soil erodibility and hydraulic soil properties are well established. They involve greater water storage capacity as well as increased organic carbon and nutrient inputs. These effects operate together with an enhanced capacity for the interception of water and windborne resources, and an increased biological activity that accelerates breakdown of plant litter and nutrient turnover rates. This suite of relationships, which often involve positive feedback mechanisms, creates vegetated patches that are increasingly different from nearby bare ground areas. By this way a mosaic builds up with bare ground and vegetated patches coupled together, respectively, as sources and sinks of water, sediments and nutrients. At the stand scale within‐storm temporal variability of rainfall intensity controls reinfiltration of overland flow and its decay with slope length. At moderate rainfall intensity, this factor interacts with the spatial structure of VDSH and the mechanism of overland flow generation. Reinfiltration is greater in small‐grained VDSH and topsoil saturation excess overland flow. Available information shows that VDSH structures of sources and sinks of water and sediments evolve dynamically with hillslope fluxes and tune their spatial configurations to them. Rainfall simulation experiments in large plots show that coarsening VDSH leads to significantly greater erosion rates even under heavy rainfall intensity because of the flow concentration and its velocity increase. Copyright © 2005 John Wiley & Sons, Ltd.     

Changes in the spatial scale of Beijing UHI and urban development

The seasonal and interannual variations of Beijing urban heat island (UHI) are investigated in this paper using the temperature data from 1960 to 2000 at 20 meteorological stations in the Beijing region, and then the relationship between the intensity and spatial scale of UHI and Beijing urbanization indices is analyzed and discussed. Main conclusions are the followings. First, Beijing UHI shows obvious seasonal variations, and it is strongest in winter, next in spring and autumn, and least in summer. The seasonal variation of the UHI mainly occurs in the urban area. The UHI intensity at the center of Beijing is more than 0.8℃ in winter, and only 0.5℃ in summer. Second, the intensity of Beijing HUI exhibits a clear interannual warming trend with its mean growth rate (MGR) being 0.3088℃/10 a. The MGR of HUI is largest in winter, next in spring and autumn, and least in summer, and the urban temperature increase makes a major contribution to the growth of HUI intensity. Third, since the Reform and Opening, the urbanization indices have grown several ten times or even one hundred times, the intensity of HUI has increased dramatically, and its spatial scale also expanded distinctively along with the expansion of urban architectural complexes. Fourth, the interannual variation of urbanization indices is very similar with that of HUI intensity, and their linear correlation coefficients are significant at a more than 0.001 confidence level.     

Incorporating Spatial Dependence in Predictive Vegetation Models: Residual Interpolation Methods*

Predictive vegetation modeling can be used statistically to relate the distribution of vegetation across a landscape as a function of important environmental variables. Often these models are developed without considering the spatial pattern that is inherent in biogeographical data, resulting from either biotic processes or missing or misspecified environmental variables. Including spatial dependence explicitly in a predictive model can be an efficient way to improve model accuracy with the available data. In this study, model residuals were interpolated and added to model predictions, and the resulting prediction accuracies were assessed. Adding kriged residuals improved model accuracy more often than adding simulated residuals, although some alliances showed no improvement or worse accuracy when residuals were added. In general, the prediction accuracies that were not increased by adding kriged residuals were either rare in the sample or had high nonspatial model accuracy. Regression interpolation methods can be an important addition to current tools used in predictive vegetation models as they allow observations that are predicted well by environmental variables to be left alone, while adjusting over‐ and underpredicted observations based on local factors.     

空间信息网格中动态复制策略的研究

空间信息网格项目数据量大，用户遍及各地，对数据文件的请求延时大、占大量带宽。复制可以节省带宽、减少时延、均衡负载、改善系统可靠性。采用动态复制技术可以使用户有效地获得所需的数据。详细地论述了动态复制策略以及空间信息网格中的复制管理机制、复制服务流程和具体实施。     

空间运动对象与时空数据类型研究

当前时空数据模型多以描述空间实体的离散变化为主。该文中对空间运动对象在抽象层次的无限连续空间、离散层次的有限离散空间上的数据类型进行分析和定义，将其分别划分为时间类型、空间类型和时态类型来研究，并提出支持空间运动对象的表示方法和操作方式。该方法既能表示空间实体的连续运动，也能表示其离散变化，为空间运动对象时空数据模型的建立奠定了基础。     

天津地区表土PAHs含量的多尺度空间相关性

本文应用因子克立格分析方法,分析了天津表土16种PAHs之间多尺度空间结构特征。分析结果显示,天津表土PAHs在空间上可以划分三种尺度:块金尺度(0～5km),小空间尺度(5～10km)和大空间尺度(10～50km)。在不同的空间尺度上,16种PAHs之间表现出不同的空间相关性,具有空间尺度相关性。这种空间尺度相关性,是由于不同的空间污染过程造成的,有助于下一步的多尺度空间污染源的判断和污染物迁移转化规律的识别。