Arctic sea-ice motion and its relation to pressure field

Daily Arctic sea-ice motion maps during the winter seasons (December–March) from December 1988 to March 2003 derived from NSCAT, QuikSCAT, SSM/I, and AMSRE data by a wavelet analysis method have been merged with those derived from buoy data. These merged sea-ice motion data have been used to study the circulation regimes and winter-to-winter variability of Arctic sea-ice motion. The relation between sea-ice motion and the pressure field in the Arctic Ocean was also studied by applying Principal Component Analysis (PCA) to the monthly merged sea-ice motion data and the monthly pressure field data from IABP. The mean Arctic sea-ice motion map of the 15 winter seasons has two distinct features: the Beaufort Gyre and a cyclonic circulation system in the Eurasian Basin, which moves ice from the Laptev Sea to Fram Strait. The strengths and sizes of the two features change from one winter season to another. Seasons with a strong or normal Beaufort Gyre alternate with seasons with a weak or no Beaufort Gyre every one to three seasons. The principal components of the first two modes of PCA of the monthly sea-ice motion are closely correlated with their counterparts of the monthly pressure field in the Arctic Ocean. The mode-one components of these two anomalies alternate between anticyclonic and cyclonic circulation systems. The correlation between Arctic Oscillation indexes and the principal components of the first mode of PCA of the monthly Arctic sea-ice motion is low but statistically significant.     

Recultivation of abandoned agricultural lands in Ukraine: Patterns and drivers

The recent rise in agricultural commodity prices and the expectation that high price will persist have triggered a wave of farmland expansion in regions where land resources are still available. One such region is the former Soviet Union, where the collapse of socialism caused massive agricultural abandonment and where some of these lands are now being brought back into production. Yet, the extent and spatial patterns of recultivation, and what determines these patterns, remains unclear. We examined the extent of recultivation of abandoned agricultural land in Ukraine since 2007 using a new, satellite-based recultivation map and assessed the effect of biophysical and socioeconomic determinants on recultivation patterns using boosted regression trees. We found key predictors of recultivation to be related to the suitability of land for agriculture (i.e., soil quality, temperature). Accessibility to major cities was also important, with most recultivation happening closer to settlements, but this influence varied across Ukraine. Variables related to agricultural management (fertilizer input, mechanization) and demography were negligible in explaining recultivation in our analyses. These factors suggest that recultivation patterns were primarily driven by factors related to land productivity, with recultivation focusing on the most promising areas. Given the remaining large amount of unused agricultural land in Eastern Europe and the former Soviet Union, and considering that much abandonment occurred in areas only marginally suited to agriculture, our findings provide important insights into where recultivation can be expected to happen and thus for assessing the potential socioeconomic and environmental impacts of recultivation.     

Book Review

In this paper, we examine the applicability of spatial optimization as a generative modelling technique for sustainable land‐use allocation. Specifically, we test whether spatial optimization can be used to generate a number of compromise spatial alternatives that are both feasible and different from each other. We present a new spatial multiobjective optimization model, which encourages efficient utilization of urban space through infill development, compatibility of adjacent land uses, and defensible redevelopment. The model uses a density‐based design constraint developed by the authors. The constraint imposes a predefined level of consistent neighbourhood development to promote contiguity and compactness of urban areas. First, the model is tested on a hypothetical example. Further, we demonstrate a real‐world application of the model to land‐use planning in Chelan, a small environmental amenity town in the north‐central region of the State of Washington, USA. The results indicate that spatial optimization is a promising method for generating land‐use alternatives for further consideration in spatial decision‐making.     

RS与GIS集成环境下的遥感图像分析技术

通过多源数据融合，将目前GIS中包含的地理信息作为辅助数据，引入到RS图像分析过程中。GIS数据在空间信息、目标属性和目标范围等方面对RS图像分析具有重要的引导作用。     

Spatial Variation of Sea Level Trend Along the Bangladesh Coast

The Bangladesh coast is threatened by rising sea level due to various factors. The results based on the analysis of past 22 years of tidal data of the Bangladesh coast reveal that the annual mean tidal level in the eastern Bangladesh coast is rising at an alarmingly high rate of 7.8 mm/year, which is almost twice the observed rate in the western region. This type of sea level trend seems to be the result of changing local conditions like increased precipitation and land subsidence during the recent decades. It seems that the higher rate of land subsidence in the eastern Bangladesh coast is the main causative factor for the steeper sea level trends there. The differential sea level trends show that the subsidence component in the sea level rise may be as high as 4 mm/year in the eastern Bangladesh coast. However, this needs to be verified with actual geological observations.     

Spatial and temperal patterns in bacterioplankton communities across a river-lake continuum

Bacterioplankton play critical roles in biogeochemical cycling. Although spatial and temporal variations in bacterioplankton community compositions (BCCs) within individual habitat have been reported, knowledge gaps remain for studies conducted within different habitats. In this work, we examined the seasonal and spatial variability of BCCs in Nanfei River and Lake Chaohu which had significant environmental heterogeneity using a high-throughput sequencing technique of 16S rRNA gene amplicons. The results showed that spatial variation has a more obvious impact on the BCCs than seasonal changes. The microbial diversity gradually decreased and BCCs changed obviously along water flow direction from Nanfei River to the western and estern parts of Lake Chaohu over all seasons. LEfSe analysis showed that Nanfei River had higer abundance of species belonging to the orders Rhodocyclales, Methylococcales, Campylobacterales and Flavobacteriales, samples from eastern part of Lake Chaohu were abundant in taxonomies including the order Rickettsiales, while the western part had high abundance of taxonomies belonging to the order Chroococcales. The redundancy analysis (RDA) indicated that BCCs in Nanfei River were associated with high nutrient (TP, PO₄-P, TN, NH₃-N, NO₂-N and NO₃-N) concentrations and electrical conductivity. Variance partitioning RDA analysis indicated that the combined effects of all variables may be most important affecting BCCs. This study may provide a framework for modeling the change in bacterioplankton communities through different habitats from a river to lake.     

Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview

The aim of this paper is to discuss a number of issues related to the use of spatial information for landslide susceptibility, hazard, and vulnerability assessment. The paper centers around the types of spatial data needed for each of these components, and the methods for obtaining them. A number of concepts are illustrated using an extensive spatial data set for the city of Tegucigalpa in Honduras. The paper intends to supplement the information given in the “Guidelines for Landslide Susceptibility, Hazard and Risk Zoning for Land Use Planning” by the Joint ISSMGE, ISRM and IAEG Technical Committee on Landslides and Engineered Slopes (JTC-1). The last few decades have shown a very fast development in the application of digital tools such as Geographic Information Systems, Digital Image Processing, Digital Photogrammetry and Global Positioning Systems. Landslide inventory databases are becoming available to more countries and several are now also available through the internet. A comprehensive landslide inventory is a must in order to be able to quantify both landslide hazard and risk. With respect to the environmental factors used in landslide hazard assessment, there is a tendency to utilize those data layers that are easily obtainable from Digital Elevation Models and satellite imagery, whereas less emphasis is on those data layers that require detailed field investigations. A review is given of the trends in collecting spatial information on environmental factors with a focus on Digital Elevation Models, geology and soils, geomorphology, land use and elements at risk.     

引入差比关系法分析西北太平洋TOPEX/POSEIDON卫星高度计测高数据

TOPEX/POSEIDON(T/P)卫星高度计数据信息中存在周期成分混淆问题.对其中的一类混淆引入差比关系方法对混淆的分潮进行分离.卫星轨道交叉点资料包括升轨和降轨资料,资料量比沿轨点资料多1倍,经分析发现:在已有为期6a多的观测资料时间序列中,在沿轨处混淆的分潮如K₁和SSA在交叉点处不再混淆,可以直接分离.因此首先对交叉点资料进行调和分析.然后由交叉点的分析结果得到分潮间的差比关系,处理到相近的沿轨点处,从而得到沿轨点的调和常数.用引入差比关系方法,对西北太平洋海区6a多的T/P卫星高度计资料进行了潮汐分析,并与沿岸及岛屿验潮站资料进行了比较,所得结果较满意.     

层次分析及 GIS空间分析在矿山岩溶塌陷预测评估中的应用--以某大理石矿为例

以某大理石矿矿山地质环境调查资料为基础,通过对矿山岩溶塌陷的机理分析,采用层次分析法,选取地下水活动、覆盖层特征、岩溶发育程度和人类活动强度四个方面,共6个评价指标,建立某大理石矿岩溶塌陷预测评估体系。在确定各评价指标权重和各评价因子分级标准的基础上,以 MAPGIS 空间分析作为数据处理工具和系统运行平台,生成某大理石矿岩溶塌陷易发性分区图。     

STAMP: spatial–temporal analysis of moving polygons

Research questions regarding temporal change in spatial patterns are increasingly common in geographical analysis. In this research, we explore and extend an approach to the spatial–temporal analysis of polygons that are spatially distinct and experience discrete changes though time. We present five new movement events for describing spatial processes: displacement, convergence, divergence, fragmentation and concentration. Spatial–temporal measures of events for size and direction are presented for two time periods, and multiple time periods. Size change metrics are based on area overlaps and a modified cone-based model is used for calculating polygon directional relationships. Quantitative directional measures are used to develop application specific metrics, such as an estimation of the concentration parameter for a von Mises distribution, and the directional rate of spread. The utility of the STAMP methods are demonstrated by a case study on the spread of a wildfire in northwestern Montana.