Land cover in Norway based on an area frame survey of vegetation types

The Norwegian area frame survey of land cover and outfield land resources (AR18X18), completed in 2014, provided unbiased statistics of land cover in Norway. The article reports the new statistics, discusses implications of the data set, and provides potential value in terms of research, management, and monitoring. A gridded sampling design for 1081 primary statistical units of 0.9 km² at 18?km intervals was implemented in the survey. The plots were mapped in situ, aided by aerial photos, and all areas were coded following a vegetation type system. The results provide new insights into the cover and distribution of vegetation and land cover types. The statistic for mire and wetlands, which previously covered 5.8%, has since been corrected to 8.9%. The survey results can be used for environmental and agricultural management, and the data can be stratified for regional analyses. The survey data can also serve as training data for remote sensing and distribution modelling. Finally, the survey data can be used to calibrate vegetation perturbations in climate change research that focuses on atmospheric–vegetation feedback. The survey documented novel land cover statistics and revealed that the national cover of wetlands had previously been underestimated.     

Mapping the hotspots and coldspots of ecosystem services in conservation priority setting

Spatial-explicitly mapping of the hotspots and coldspots is a vital link in the priority setting for ecosystem services (ES) conservation. However, little research has identified and tested the compactness and efficiency of their ES hotspots and coldspots, which may weaken the effectiveness of ecological conservation. In this study, based on the RUSLE model and Getis-Ord Gi* statistics, we quantified the variation of annual soil conservation services (SC) and identified the statistically significant hotspots and coldspots in Shaanxi Province of China from 2000 to 2013. The results indicate that, 1) areas with high SC presented a significantly increasing trend as well, while areas with low SC only changed slightly; 2) SC hotspots and coldspots showed an obvious spatial differentiation—the hotspots were mainly spatially aggregated in southern Shaanxi, while the coldspots were mainly distributed in the Guanzhong Basin and Sand-windy Plateau; and 3) the identified hotspots had the highest capacity of providing SC, with 29.6% of the total area providing 59.7% of the total service. In contrast, the coldspots occupied 46.3% of the total area, but only provided 17.2% of the total SC. In addition to conserving single ES, the Getis-Ord Gi* statistics method can also help identify multi-functional priority areas for conserving multiple ES and biodiversity.     

The Role Of The Geographer On Multidisciplinary Resource Surveys

Turning and turning in the widening gyre The falcon cannot hear the falconer; Things fall apart; the centre cannot hold; Mere anarchy is loosed upon the world ….

“The Second Coming,” W. B. Yeats 1921     

Estimation of the Bingham distribution function on nearly two-dimensional data sets

Summary. In cases where directional data, such as palaeomagnetic directions, lie nearly along a great circle, a good approximation to the maximum likelihood estimate of the intermediate concentration parameter k ₂ in the Bingham probability distribution is given by: 2( t ₂/ N ) – 1 = I ₁(1/2 k ₂)/ I ₀(1/2 k ₂), where t ₂ is the intermediate eigenvalue, N is the number of samples, and the I_i are the appropriate modified Bessel functions of the first kind. This estimate, the asymptotic limit as the smallest eigenvalue t ₁→ 0, corresponds to restricting all points to lie on a great circle. The limit is also useful as an endpoint for interpolation, especially since numerical calculation in this region is difficult.     

SOFTWARE REVIEWS

ATLAS*GIS , Version 1.0. ATLAS*MapMaker , Version 4.0. FIVFIV-SINSIN , Release 9.0. Geo-EAS , Version 1.2.1. Evan Englund Sim City , Version 1.0 Statistix , Version 3.1.     

Transcribing from the Mind To the Map: Tracing the Evolution of a Concept

Transcribing what is held in one's mind to a tangible map is experiencing a multidisciplinary renewal. Sketch mapping is being utilized to identify a range of community concerns, as well as for more generally revealing otherwise invisible landscapes. Whether the aim is to understand preference, perception, knowledge, or behavior, the result is some form of map. The genesis of this concept is usually attributed to seminal work in the 1960s and 1970s geography, planning, and environmental psychology. However, its resurgence in the past decade has been driven by a confluence of recent methodological and epistemological developments across numerous disciplines surrounding the role of local knowledge in ecological frameworks and how this can be mapped and analyzed with and without geospatial technologies. With growing adoption of sketch mapping well beyond its initial disciplinary niches, it is appropriate to review its evolution in order to inform ongoing and future research.     

Complementary Use of Scalar,Directional, and Vector Statistics with an Application to Surface Winds

Vector data are not uncommon in geography, and include examples such as transportation flows, particulate transport, and cartographic distortion. The directional and vector means and variances of these types of data are easily computed using a complex-arithmetic extension of the equations for scalar mean and variance. The January surface wind field over the contiguous United States provides an example with which to compare the information provided by scalar, directional and vector-based statistics. Spatial patterns of the mean and variance of January wind velocity (the wind vector) resemble patterns of wind speeds and directions but are not a simple superposition of the two, and one cannot necessarily infer the nature of the velocity field from separately computed salar and directional statistics. However, scalar and directional means and variances can lend insight into the features contributing to the velocity mean and variance. Scalar, directional, and vector-based analyses thus provide complementary methods with which to examine the spatial patterns of wind, or of any flow field that can be represented as a vector.     

Complementary Use of Scalar,Directional, and Vector Statistics with an Application to Surface Winds

Vector data are not uncommon in geography, and include examples such as transportation flows, particulate transport, and cartographic distortion. The directional and vector means and variances of these types of data are easily computed using a complex-arithmetic extension of the equations for scalar mean and variance. The January surface wind field over the contiguous United States provides an example with which to compare the information provided by scalar, directional and vector-based statistics. Spatial patterns of the mean and variance of January wind velocity (the wind vector) resemble patterns of wind speeds and directions but are not a simple superposition of the two, and one cannot necessarily infer the nature of the velocity field from separately computed salar and directional statistics. However, scalar and directional means and variances can lend insight into the features contributing to the velocity mean and variance. Scalar, directional, and vector-based analyses thus provide complementary methods with which to examine the spatial patterns of wind, or of any flow field that can be represented as a vector.     

Quantifying the spatial heterogeneity of points

Variation in the spatial heterogeneity of points reflects the evolutionary process or mechanism of geographical events. The key to depicting this variation is quantifying spatial heterogeneity. In this paper, the spatial heterogeneity of a point pattern is defined as the degree of aggregation-type deviation from complete spatial randomness. In such a case, a goodness-of-fit-type statistic based on the distribution of nearest-neighbor distances called the level of heterogeneity (LH*) is regarded as a standard measurement, and a normalized version called the normalized level of heterogeneity (NLH*) is proposed for datasets with different point numbers and study region areas. Considering the complex integration calculation of LH* and NLH*, simulation experiments are implemented to test the capability of some classic nearest-neighbor statistics in quantifying spatial heterogeneity. The results showed that except for the standard LH* statistic, only Clark and Evans’ statistic (A-w) and Byth and Ripley’s statistic (H-xw) are robust. Statistics NLH*, (A-w) and (H-xw) are validated by quantifying the spatial heterogeneity of two-dimensional crime events, three-dimensional earthquake events and four-dimensional origin-destination (OD) events. The results indicate that these statistics all have a reasonable explanation in quantifying spatial heterogeneity for real-world geographical events of different types and with different dimensions. Compared with NLH*, Clark and Evans’ (A-w) statistic and Byth and Ripley’s (H-xw) statistic are recommended from the perspective of accessibility.     

Guest editorial

The past decade has witnessed extensive development of measures that examine characteristics of spatial subsets (local spaces) defined with respect to a complete data set (global space). Such procedures have evolved independently in fields such as geography, GIS, cartography, remote sensing, and landscape ecology. Collectively, we label these procedures as local spatial methods. We focus on those methods that share a common goal of identifying subsets whose characteristics are statistically ‘significant’ in some way. We propose the concept of local spatial statistical analysis (LoSSA) both as an integrative structure for existing methods and as a framework that facilitates the development of new local and global statistics. By formalizing what is involved when a particular local statistic is used, LoSSA helps to reveal the key features and limitations of the procedure. These include a consideration of the nature of the spatial subsets, their spatial relationship to the complete data set, and the relationship between a given global statistic and the corresponding local statistics computed for the data set.     

Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization

An origin-destination (OD) flow can be defined as the movement of objects between two locations. These movements must be determined for a range of purposes, and strong interactions can be visually represented via clustering of OD flows. Identification of such clusters may be useful in urban planning, traffic planning and logistics management research. However, few methods can identify arbitrarily shaped flow clusters. Here, we present a spatial scan statistical approach based on ant colony optimization (ACO) for detecting arbitrarily shaped clusters of OD flows (AntScan_flow). In this study, an OD flow cluster is defined as a regional pair with significant log likelihood ratio (LLR), and the ACO is employed to detect the clusters with maximum LLRs in the search space. Simulation experiments based on AntScan_flow and SaTScan_flow show that AntScan_flow yields better performance based on accuracy but requires a large computational demand. Finally, a case study of the morning commuting flows of Beijing residents was conducted. The AntScan_flow results show that the regions associated with moderate- and long-distance commuting OD flow clusters are highly consistent with subway lines and highways in the city. Additionally, the regions of short-distance commuting OD flow clusters are more likely to exhibit ‘residential-area to work-area’ patterns.     

Place matters in sports: effects of the length of championship series on winning probabilities for the team with home field advantage

In this paper, I address the question of how the length of championship series between two teams can affect the probability that a team wins the series. The geographical element of the question enters through consideration of ‘home-field advantage’. This refers to the fact that in championship series, one of the teams has the benefit of one additional game that is scheduled to be played at home. This, coupled with the fact that teams typically have a higher likelihood of winning at home, leads to an interesting and surprisingly complex relationship between the length of a series and the probability of winning that series. Conclusions include the facts that (1) when the team with home-field advantage has a relatively small probability of winning away from home, it will fare relatively better in shorter series, and (2) the probability of winning a series can first become lower, but then become higher, as one progresses from 1-game series to 3-, 5- and 7-game series.     

THE GEOGRAPHY OF MASTODON EXTINCTION

Geographic Software Reviewed in this article:

LIFE TABLES and the LESLIE MATRIX. CONDUIT

MENTMAP2. Lawrence W. Carstensen Jr.

PC-MATLAB, Version 1.0. The Math Works, Inc.

QUICKMAP, version 1.0. Sammamish Data Systems, Inc.

SYSTAT: THE SYSTEM FOR STATISTICS, Version 2.1, Systat Inc.

USA DISPLAY. Instant Tecall     

How many Stakes are Required to Measure the Mass Balance of a Glacier?

Glacier mass balance is estimated for South Cascade Glacier and Maclure Glacier using a one-dimensional regression of mass balance with altitude as an alternative to the traditional approach of contouring mass balance values. One attractive feature of regression is that it can be applied to sparse data sets where contouring is not possible and can provide an objective error of the resulting estimate. Regression methods yielded mass balance values equivalent to contouring methods. The effect of the number of mass balance measurements on the final value for the glacier showed that sample sizes as small as five stakes provided reasonable estimates, although the error estimates were greater than for larger sample sizes. Different spatial patterns of measurement locations showed no appreciable influence on the final value as long as different surface altitudes were intermittently sampled over the altitude range of the glacier. Two different regression equations were examined, a quadratic, and a piecewise linear spline, and comparison of results showed little sensitivity to the type of equation. These results point to the dominant effect of the gradient of mass balance with altitude of alpine glaciers compared to transverse variations. The number of mass balance measurements required to determine the glacier balance appears to be scale invariant for small glaciers and five to ten stakes are sufficient.     

地理空间分布整体统计研究进展

利用统计学方法研究社会经济与自然等要素的地理空间分布在最近几十年来已引起许多学者的关注.地理空间分布的整体性就像它的局部性一样,是空间统计分析的主要对象.本文目的是综述各种地理空间分布整体性特征的统计研究进展.在这里,地理空间分布的整体性特征是指它在二维空间上的中心和方位以及它自身的地理范围、空间密集度和形状.文中介绍了对这些整体性特征进行统计描述、预测和估计的方法.已有近20个空间统计指标用于描述社会经济和自然地理空间分布的各种整体性特征,分析和预测它们的时空演化过程.如空间移动、扩张、加密、旋转,并确定不同空间分布的相关关系.文中探讨了地理空间分布整体统计目前存在的主要科学问题.如空间独立性假设、空间随机抽样、时空过程分析(包括时空稳态随机过程1、空间统计描述方法和空间分布函数等.     

REVIEWS OF GEOGRAPHIC SOFTWARE

Geographic Software Reviewed in this article: LIFE TABLES and the LESLIE MATRIX. CONDUIT MENTMAP2 . Lawrence W. Carstensen Jr . PC-MATLAB , Version 1.0. The Math Works, Inc. QUICKMAP , version 1.0. Sammamish Data Systems, Inc. SYSTAT: THE SYSTEM FOR STATISTICS , Version 2.1, Systat Inc. USA DISPLAY . Instant Tecall