Sub-regional snow cover distribution across the southern Appalachian Mountains

Abstract

Snowfall in the Southern Appalachian Mountain region of the eastern US is characterized by much spatiotemporal variability. Annual snowfall totals vary by up to 75 cm, and variations in snowfall intensity can lead to large differences in the local snowfall distribution. Research has shown that the synoptic pattern associated with the snowfall strongly influences the regional-scale distribution of snow cover. However, topographic variability results in locally complex snow cover patterns that are not well understood or documented. In this study, we characterize the snow covered area (SCA) and fractional snow cover associated with different synoptic patterns in 14 individual sub-regions. We analyze 63 snow events using Moderate-resolution Imaging Spectroradiometer standard snow cover products to ascertain both qualitative and quantitative differences in snow cover across sub-regions. Among sub-regions, there is significant variation in the snow cover pattern from individual synoptic classes. Furthermore, the percent SCA follows the regional snowfall climatology, and sub-regions with the highest elevations and northerly latitudes exhibit the greatest variability. Results of the sub-regional analysis provide valuable guidance to forecasters by contributing a deeper understanding of local snow cover patterns and their relationship to synoptic-scale circulation features.     

Regions and western europe

Abstract

Regional geography is undergoing important changes in its method of study in order to achieve a greater degree of relevancy in the context of a dynamic global system. Effective knowledge of regional identities can no longer be confined to facts that establish patterns, it also demands a critical appreciation of processes and spatial interrelationships. Western Europe is taken as a case study to reflect this new approach to regional geography, Despite the complexity of this major world region, two basic models are proposed as a basis on which to develop detailed study. Essential patterns of Western Europe are established through six generalizations: location; quality of the environment; industrialization; urban development and trade; population and culture; and the European Community/European Union. Processes and interrelations are reviewed through a core-periphery model. Changing regional patterns are highlighted which suggest a movement away from a national focus for regional study to one which is more international.     

Variable complexity of the US Continental Divide trace

Abstract

Map-view complexity of 65 contiguous segments of the conterminous US Continental Divide trace was evaluated by the divider method, with each segment’s geometry approximated by a fractal dimension (D) value, or two D values applying to fine and coarse scales of inspection. Results support a generalization that D values in the range 1.05–1.12 are typical for drainage divides viewed at regional to national scales. However about 20% of cases reviewed in this study are smoother (D = 1.01–1.04) or more complex (D = 1.13–1.18) traces. Complexities of these watershed boundary segments show no significant correlation with physiographic province or local relief. The primary influence of bedrock lithology and surface process is seen in zones of Quaternary volcanism, where uncommonly smooth and highly complex divide trace segments are more the rule than exception. Uncommonly smooth divide traces are also found descending mountain pediments in areas of parallel drainage, and some of the most tortuous traces are associated with drainage patterns disrupted by non-fluvial processes. Divide trace segments crossing terrain with uniform lithology show decreased complexity, but traces with the broadest range of complexity, including highest D values, occur in areas with moderate, not extreme, degrees of bedrock diversity.     

Relationships of Agricultural Land Use to an Expanded Road Network within Tropical Forest Landscapes of Cameroon and Republic of the Congo

Road building in Congo Basin forests has increased due to expansion of commercial logging, with potential to expose intact forests to greater establishment of agriculture. We developed new knowledge of agriculture clearing sizes, spatial patterns, and relationships with roads in seven case study sites comprising 7,529 km². Using very high spatial resolution satellite imagery, we mapped roads and rivers, plus clearings for agriculture, settlements, and logging. Mapped clearings (N = 1,781) ranged in size from 0.008 ha to more than 300 ha; most were smallholder agriculture, with 64 percent ≤ 1 ha. Statistical tests of spatial pattern confirmed that agriculture occurred in an inhomogeneous-aggregated pattern, suggesting interactions with other landscape elements. Proximity analyses showed that 76 percent of clearings were within 1 km of a road or river. Thirty-five percent of agriculture clearings were within 1 km of main public roads built before 1990, compared to 17 percent for logging roads built after 2000. Less than 6 percent of agriculture clearings were within 1 km of logging roads with overgrown canopies, suggesting transient relationships. Results based on fine-scale data provide new empirical support for understanding the interactions between agriculture and roads in one of the remaining relatively intact forest areas of the Congo Basin.     

Spatial structure analysis of a reptile community with airborne LiDAR data

The analysis of the spatial structure of animal communities requires spatial data to determine the distribution of individuals and their limiting factors. New technologies like very precise GPS as well as satellite imagery and aerial photographs of very high spatial resolution are now available. Data from airborne LiDAR (Light Detection and Ranging) sensors can provide digital models of ground and vegetation surfaces with pixel sizes of less than 1 m. We present the first study in terrestrial herpetology using LiDAR data. We aim to identify the spatial patterns of a community of four species of lizards (Lacerta schreiberi, Timon lepidus, Podarcis bocagei, and P. hispanica), and to determine how the habitat is influencing the distribution of the species spatially. The study area is located in Northern Portugal. The position of each lizard was recorded during 16 surveys of 1 h with a very precise GPS (error < 1 m). LiDAR data provided digital models of surface, terrain, and normalised height. From these data, we derived slope, ruggedness, orientation, and hill-shading variables. We applied spatial statistics to determine the spatial structure of the community. We computed Maxent ecological niche models to determine the importance of environmental variables. The community and its species presented a clustered distribution. We identified 14 clusters, composed of 1–3 species. Species records showed two distribution patterns, with clusters associated with steep and flat areas. Cluster outliers had the same patterns. Juveniles and subadults were associated with areas of low quality, while sexes used space in similar ways. Maxent models identified suitable habitats across the study area for two species and in the flat areas for the other two species. LiDAR allowed us to understand the local distributions of a lizard community. Remotely sensed data and LiDAR are giving new insights into the study of species ecology. Images of higher spatial resolutions are necessary to map important factors such as refuges.     

Scale variance analysis coupled with Moran's I scalogram to identify hierarchy and characteristic scale

Scale variance is highly sensitive to multi-scale patterns of variables, which is advantageous in identifying spatial hierarchy and characteristic scale(s). However, the significance of peak(s) in scale variance cannot be statistically tested, and different spatial patterns may be obtained when different zoning systems are used to calculate scale variance. To address these two problems, this study compared the scale levels with peaks in scale variance and the scale levels at which there were breaks in the nature of spatial autocorrelation as identified by shifts in Moran's I scalogram. The estimates for three simulated landscapes showed that accordance between scale levels identified employing the two methods can be used to evaluate the significance of peaks in scale variance and choose a more reasonable zoning system. The approach of scale variance analysis coupled with Moran's I scalogram was also applied to the Xilin River Basin of Inner Mongolia, China. The most vital characteristic scale (64 × 32 km) identified for the growing-season net ecosystem productivity (NEP) of the basin was validated by other spatial pattern analysis methods such as semi-variogram, Moran's I correlogram, and wavelet variance analyses, and the directionality of the chosen zoning systems was found to be similar to the orientation of actual dominant vegetation type patches. The results demonstrate that Moran's I scalogram can be used to improve the interpretation of the results of scale variance analysis and increase the reliability of scale variance analysis for landscapes having a repetitive patch pattern or gradient variation and that the proposed approach is suitable for identifying the hierarchy and the characteristic scales of patterns or processes. In summary, this study used a simple approach to solve two problems in scale variance analysis, thereby improving the methodology and enhancing the theoretical basis of multi-scale analysis.     

Mapping illegal domestic waste disposal potential to support waste management efforts in Queensland,Australia

Illegal disposal of waste is a significant management issue for contemporary governments because of the hazards posed to both human and ecosystem health. Understanding the complex distribution pattern of illegal waste and the range of economic, environmental and social factors influencing this distribution is valuable for improving the effectiveness and efficiency of waste management efforts. This article examines the applicability of mapping illegal waste disposal in the Sunshine Coast (Queensland, Australia) through the identification and integration of predictive spatial data in a geographic information system. A statistical model of illegal waste disposal was developed using a binary logistic regression analysis to identify explanatory variables suitable for predicting the distribution of illegal waste. Five statistically significant explanatory variables were identified through this analysis: population density, primary land use, distance to the nearest road, waste facility and roadside amenity. The generated statistical model had a predictive success of 86.1% with all indicators suggesting good model fit (χ² = 474.3, P = 0 with df = 22) across the study area. Standardised spatial data on each explanatory variable were combined using a weighted linear combination analysis and the results were classified into five categories from very low to very high illegal waste disposal potentials using the equal interval method. The resultant mapping identified 6.9% of the study area as having very high illegal waste disposal potential, and subsequent validation indicated that 32.9% of known illegal waste disposal sites were located within these areas.     

Spatial distribution and morphologic characteristics of gullies in the Black Soil Region of Northeast China: Hebei watershed

Gully erosion in the Black Soil Region of China has posed a threat to food security. This study aimed to determine the spatial distribution and morphologic characteristics of gullies in the region and their topographic thresholds. A 28 km² watershed was surveyed and 117 gullies measured. The results showed that: (1) Gullies were distributed equally on both hillslope and valley floor positions, with a total gully density of .66 km/km². (2) The mean depth, width, and cross-sectional area of gullies were .74 m, 2.39 m, and 2.43 m², respectively. These characteristics varied among gullies according to their topographic positions and slope gradients. Individual gully volume (V) was well predicted from gully length (L) by V = 2.08L^0.96 (r² = .66). Total gully volume (V) of each sub-watershed was predicted from mean slope gradient (S) and drainage area (A) as V = 275800S ? 8600A (r² = .73). (3) Gully erosion was more serious in steeper sub-watersheds and steeper hillslope positions. Gullies were wider in regions with relatively larger drainage areas, except for those developed in the main valley. The topographic threshold for gully initiation was S = .10A^?0.34, which indicated gully erosion was dominated by surface runoff. (4) Human activities, such as road construction, played a significant role in gully erosion.     

Storage-efficient method for generating contours focusing on roundness

A storage-efficient contour generation method, focusing on planar contours, is developed. Given cartographic elevations on a rectangular lattice, a continuous bivariate function, z = f(x, y), is determined by interpolating the elevation values. Then, we focus on a contour determined by z = constant. The contour curve is partitioned into multiple sections, each of which is exactly or approximately round. Three curvature types are introduced to evaluate the roundness of each section. The area and perimeter of the contour are computed by one-dimensional line integration using Green’s theorem. If the contour is open, it is divided into two curves starting from the same initial point, with the control points advancing in opposite directions. Two types of numerical experiments are performed to validate the effectiveness of the proposed method. One experiment uses an analytically defined elevation function and investigates the number of control points and computation time for a resulting computation error. The second experiment uses actual digital elevation model data of an isolated island in Japan and compares the proposed method with existing ones. Because the algorithm does not require lattice subdivision and the number of control points is drastically reduced, the proposed method is storage efficient.     

区域经济协同发展及其理论依据与实施途径

该文指出区域经济协同发展应以协同学原理为基本理论依据,遵循比较优势与互利共赢原则、科学性与超前性原则、主导内容优先整合下的比较优势全面整合原则、组织实施的可操作性与可调控性原则、协同发展下的效率与公平兼顾原则,建立跨行政区组织协调机构及其运行机制,加强在宏观发展框架下的区域规划工作和规划实施体系建设,有效激活与加快构建行业与企业的自组织协调机制;建立跨行政区点轴开发的经济地域系统;建立衡量地方经济发展与考核政府政绩的区际协调与保障机制,并提出区域经济协同发展实施与监督调控的基本途径。     

Computational reproducibility in geoscientific papers: Insights from a series of studies with geoscientists and a reproduction study

Reproducibility is a cornerstone of science and thus for geographic research as well. However, studies in other disciplines such as biology have shown that published work is rarely reproducible. To assess the state of reproducibility, specifically computational reproducibility (i.e. rerunning the analysis of a paper using the original code), in geographic research, we asked geoscientists about this topic using three methods: a survey (n = 146), interviews (n = 9), and a focus group (n = 5). We asked participants about their understanding of open reproducible research (ORR), how much it is practiced, and what obstacles hinder ORR. We found that participants had different understandings of ORR and that there are several obstacles for authors and readers (e.g. effort, lack of openness). Then, in order to complement the subjective feedback from the participants, we tried to reproduce the results of papers that use spatial statistics to address problems in the geosciences. We selected 41 open access papers from Copernicus and Journal of Statistical Software and executed the R code. In doing so, we identified several technical issues and specific issues with the reproduced figures depicting the results. Based on these findings, we propose guidelines for authors to overcome the issues around reproducibility in the computational geosciences.     

Determination of grid size for digital terrain modelling in landscape investigations—exemplified by soil moisture distribution at a micro-scale

The central problem of a combined analysis of digital terrain models (DTMs) and other landscape data is determination of a DTM grid size (w) providing a correct study of relationships between topographic variables and landscape properties. Generally, an adequate w is determined by an expert estimate, and solutions are largely subjective. We developed an experimental statistical method to determine an adequate w for DTMs applied to landscape studies. The method includes the following steps: (a) derivation of a DTM set using a series of w_i , (b) performance of a correlation analysis of data on a landscape property and a topographic variable estimated with various w_i , (c) plotting of correlation coefficients obtained versus w, and (d) determination of smoothed plot portions indicating intervals of an adequate w. We applied the method developed to study the ifluence of topography on the spatial distribution of soil moisture (M) at a micro-scale. We investigated the dependence of M on gradient (G), horizontal (k_h ), vertical (k_v ), and mean (H) landsurface curvatures. For DTM derivation, we used 13 values of w_i from 1 to 7m. An interval of adequate w_i for M falls between 2.25 and 3.25m in the given terrain conditions. In absolute magnitudes, correlation coefficients are largest within this interval; correlation coefficients of M with G, k_h , k_v and H are 0.28, 0.52, 0.50 and 0.60, respectively, for w = 3m. The results obtained demonstrate that the method actually works to identify an adequate w at a micro-scale. The method developed allows estimation of an adequate area of landform which realise a topographic control of landscape properties.     

Mapping ecosystem services at the regional scale: the validity of an upscaling approach

Mapping ecosystem services (ES) over large scales is important for environmental monitoring but is often prohibitively expensive and difficult. We test a hybrid, low-cost method of mapping ES indicators over large scales in Pará State, Brazil. Four ES indicators (vegetation carbon stocks, biodiversity index, soil chemical quality index and rates of water infiltration into soil) were measured in the field and then summarized spatially for regional land-cover classes derived from satellite imagery. The regionally mapped ES values correlated strongly with independent and local measures of ES. For example, regional estimates of the vegetation carbon stocks are strongly correlated with actual measures derived from field samples and validation data (significant anova test – p-value = 4.51^e?9) and differed on average by only 20 Mg/ha from the field data. Our spatially-nested approach provides reliable and accurate maps of ES at both local and regional scales. Local maps account for the specificities of an area while regional maps provide an accurate generalization of an ES’ state. Such up-scaling methods infuse large-scale ES maps with localized data and enable the estimation of uncertainty of at regional scales. Our approach is first step towards the spatial characterization of ES at large and potentially global scales.     

中国东北地区侵蚀产沙尺度效应的空间分异

对中国东北地区侵蚀产沙尺度效应的空间变化进行了探讨。基于气候、下垫面的一致性和流域的完整性,对整个研究区域进行了分区研究。结果表明,尺度效应同时受到地形、坡度、土地利用和地表覆盖物质等因素的影响,不同分区因素因素组合不同,其产沙模数随流域面积的变化趋势亦不相同,可以分为三类:(1) 产沙模数随流域面积增大而增大;(2) 产沙模数随流域面积的增大基本保持不变;(3) 产沙模数随流域面积的增大而减小。基于各分区尺度效应,进行了不同标准面积下产沙模数图的校正,并使用空间插值方法,编制不同标准面积下产沙模数图。     

Uncertainty due to DEM error in landslide susceptibility mapping

Terrain attributes such as slope gradient and slope shape, computed from a gridded digital elevation model (DEM), are important input data for landslide susceptibility mapping. Errors in DEM can cause uncertainty in terrain attributes and thus influence landslide susceptibility mapping. Monte Carlo simulations have been used in this article to compare uncertainties due to DEM error in two representative landslide susceptibility mapping approaches: a recently developed expert knowledge and fuzzy logic-based approach to landslide susceptibility mapping (efLandslides), and a logistic regression approach that is representative of multivariate statistical approaches to landslide susceptibility mapping. The study area is located in the middle and upper reaches of the Yangtze River, China, and includes two adjacent areas with similar environmental conditions – one for efLandslides model development (approximately 250 km²) and the other for model extrapolation (approximately 4600 km²). Sequential Gaussian simulation was used to simulate DEM error fields at 25-m resolution with different magnitudes and spatial autocorrelation levels. Nine sets of simulations were generated. Each set included 100 realizations derived from a DEM error field specified by possible combinations of three standard deviation values (1, 7.5, and 15 m) for error magnitude and three range values (0, 60, and 120 m) for spatial autocorrelation. The overall uncertainties of both efLandslides and the logistic regression approach attributable to each model-simulated DEM error were evaluated based on a map of standard deviations of landslide susceptibility realizations. The uncertainty assessment showed that the overall uncertainty in efLandslides was less sensitive to DEM error than that in the logistic regression approach and that the overall uncertainties in both efLandslides and the logistic regression approach for the model-extrapolation area were generally lower than in the model-development area used in this study. Boxplots were produced by associating an independent validation set of 205 observed landslides in the model-extrapolation area with the resulting landslide susceptibility realizations. These boxplots showed that for all simulations, efLandslides produced more reasonable results than logistic regression.     

Spatial co-location pattern mining of facility points-of-interest improved by network neighborhood and distance decay effects

The aim of mining spatial co-location patterns is to find the corresponding subsets of spatial features that have strong spatial correlation in the real world. This is an important technology for the extraction and comprehension of implicit knowledge in large spatial databases. However, existing methods of co-location mining consider events as taking place in a homogeneous and isotropic context in Euclidean space, whereas the physical movement in an urban space is usually constrained by a road network. Furthermore, previous works do not take the ‘distance decay effect’ of spatial interactions into account, which may reduce the effectiveness of the result. Here we propose an improved spatial co-location pattern mining method, including the network-constrained neighborhood and addition of a distance-decay function, to find the spatial dependence between network phenomena (e.g. urban facilities). The underlying idea is to utilize a model function in the interest measure calculation to weight the contribution of a co-location to the overall interest measure instance inversely proportional to the separation distance. Our approach was evaluated through extensive experiments using facility points-of-interest data sets. The results show that the network-constrained approach is a more effective method than the traditional one in network-structured space. The proposed approach can also be applied to other human activities (e.g. traffic accidents) constrained by a street network.     

Evaluating the Temporal and Spatial Urban Expansion Patterns of Guangzhou from 1979 to 2003 by Remote Sensing and GIS Methods

China has experienced and is experiencing expeditious urban expansion in the recent decades, especially in the coastal areas and big cities. Rapid urban expansion and dramatic changes of landscape have caused great economic, environmental and social impacts consequently. It is crucial to understand urban temporal, spatial expansion patterns and their related effects. In this paper, urban expansion of Guangzhou, a rapid growing city in south‐east China, from 1979 to 2003 is studied temporally and spatially. Four time ranges including 1979–1990, 1990–1995, 1995–2000 and 2000–2003 are designed and the urban expansion area, expansion rate and the spatial expansion pattern are discussed by using remote sensing data and Geographical Information System (GIS) tool. Two transects are designed along two axes of Guangzhou expansion and the structural of urban expansion patches at different orientations are compared in order to quantitively understand the urban expansion of Guangzhou during the past 24 years. The gradient analysis integrating multi‐temporal data is performed in order to analyze and compare the spatial and temporal dynamics of urban expansion. Two indices of compactness and fractal dimensional index are used to describe the urban developing pattern in the study time durations. And the influence of different types of traffic roads to urban expansion is evaluated using the buffer analysis of GIS. The results show that: (1) temporally, urban area of Guangzhou increase 296.54 km² from 141.15 km² in 1979 to 437.70 km² in 2003 and the increasing rate is up to 210.08%; (2) spatially, Guangzhou has different urban expanding directions in different stages and the general expanding directions are towards northeast, north, southeast and north in four studied time ranges; (3) transportation lines play a very important role in urban expansion of Guangzhou, but different types of road have different impacts. National roads and highways exhibit stronger control to urban expansion than provincial roads; and (4) expansion of Guangzhou has gradually changed from a compact pattern to leapfrogging and disordering patterns.     

Morphology and controlling factors of step-pools in rills based on field investigation in the Yuanmou Dry-hot Valley,China

Rill erosion is well developed in Yuanmou Dry-hot Valley. The appearance of step-pools in rills (SPRs) is an early stage of erosion and necessary condition for rill development. We measured length, width, depth of plunge pools, and length, height, and slope of step walls. We observed the developmental environment of every SPR in the field. Through research on relationships among SPR parameters, morphological characteristics, and control factors, we conclude that (1) correlations of step slope with pool length and width, and of step length with pool width are not evident (p > 0.1); correlations of pool length with step height and length are evident (p < 0.1); correlations of step slope with pool depth, and of step height with pool width are significant (p < 0.05); and correlations of pool depth with step length and height are highly significant (p < 0.01). Plunge-pool length is affected by soil properties and step height, but not by step gradient. (2) SPR formation shows a coupling effect of a single factor or many factors, such as terrain conditions, vegetation, confluence area, soil properties, and boundary conditions, and the shapes and scales of SPRs notably change with differences of the main control factors.     

Spatialization of the SNOWPACK snow model for the Canadian Arctic to assess Peary caribou winter grazing conditions

Abstract

Peary caribou is the northernmost designatable unit for caribou species, and its population has declined by about 70% over the last three generations. The Committee on the Status of Endangered Wildlife in Canada identified difficult grazing conditions through the snow cover as being the most significant factor contributing to this decline. This study focuses on a spatially explicit assessment tool using snow model simulations (Swiss SNOWPACK model driven in an off-line mode by spatialized meteorological forcing data generated by the Canadian Regional Climate Model) to characterize snow conditions for Peary caribou grazing in the Canadian Arctic. The life cycle of Peary caribou has been subdivided into three critical periods: summer foraging and fall breeding (July–October), winter foraging (November–March), and spring calving (April–June). Winter snow conditions are analyzed and snow simulations compared to Peary caribou island counts to identify a snow parameter that could potentially act as a proxy for grazing conditions and explain fluctuations in Peary caribou numbers. This analysis concludes that caribou counts are affected by simulated snow density values >300 kg m^?3. A software tool mapping possibly favorable and unfavorable grazing conditions based on snow is proposed at a regional scale across the Canadian Arctic Archipelago. Specific output examples are given to show the utility of the tool, mapping pixels with cumulative snow thickness above densities of 300 kg m^?3, where cumulative seasonal thicknesses >7000 cm are considered unfavorable.     

A complete classification of spatial relations using the Voronoi-based nine-intersection model

In this article we show that the Voronoi-based nine-intersection (V9I) model proposed by Chen et al. (2001, A Voronoi-based 9-intersection model for spatial relations. International Journal of Geographical Information Science, 15 (3), 201–220) is more expressive than what has been believed before. Given any two spatial entities A and B, the V9I relation between A and B is represented as a 3 × 3 Boolean matrix. For each pair of types of spatial entities that is, points, lines, and regions, we first show that most Boolean matrices do not represent a V9I relation by using topological constraints and the definition of Voronoi regions. Then, we provide illustrations for all the remaining matrices. This guarantees that our method is sound and complete. In particular, we show that there are 18 V9I relations between two areas with connected interior, while there are only nine four-intersection relations. Our investigations also show that, unlike many other spatial relation models, V9I relations are context or shape sensitive. That is, the existence of other entities or the shape of the entities may affect the validity of certain relations.