A new pseudocylindrical equal-area projection for adaptive composite map projections

The recently introduced adaptive composite map projection technique changes the projection to the geographic area shown on a map. It is meant as a replacement for the commonly used web Mercator projection, which grossly distorts areas when representing the entire world. The original equal-area version of the adaptive composite map projection technique uses the Lambert azimuthal projection for regional maps and three alternative projections for world maps. Adaptive composite map projections can include a variety of other equal-area projections when the transformation between the Lambert azimuthal and the world projections uses Wagner’s method. To select the most suitable pseudocylindrical projection, the distortion characteristics of a pseudocylindrical projection family are analyzed, and a user study among experts in the area of map projections is carried out. Based on the results of the distortion analysis and the user study, a new pseudocylindrical projection is recommended for extending adaptive composite map projections. The new projection is equal-area throughout the transformation to the Lambert azimuthal projection and has better distortion characteristics then small-scale projections currently included in the adaptive composite map projection technique.     

平面影像到QTM像元的转换算法及精度分析

平面影像数据到四元三角网(Quaternary Triangular Mesh,QTM)像元的转换是实现全球QTM格网影像无缝建模的首要任务。提出基于面积权的数据转换方法,给出不同类型的权重及格网值的计算,并利用ArcGIS中256级灰度的Wsiearth.tif图像数据分析了转换精度。结果表明:将4 km分辨率的影像数据转换到12层的QTM像元时,转换误差在0~2灰度内占96.27%,对一般应用的影响可以忽略不计。     

A compromise aspect-adaptive cylindrical projection for world maps

There are two problems with current cylindrical projections for world maps. First, existing cylindrical map projections have a static height-to-width aspect ratio and do not automatically adjust their aspect ratio in order to optimally use available canvas space. Second, many of the commonly used cylindrical compromise projections show areas and shapes at higher latitudes with considerable distortion. This article introduces a new compromise cylindrical map projection that adjusts the distribution of parallels to the aspect ratio of a canvas. The goal of designing this projection was to show land masses at central latitudes with a visually balanced appearance similar to how they appear on a globe. The projection was constructed using a visual design procedure where a series of graphically optimized projections was defined for a select number of aspect ratios. The visually designed projections were approximated by polynomial expressions that define a cylindrical projection for any height-to-width ratio between 0.3:1 and 1:1. The resulting equations for converting spherical to Cartesian coordinates require a small number of coefficients and are fast to execute. The presented aspect-adaptive cylindrical projection is well suited for digital maps embedded in web pages with responsive web design, as well as GIS applications where the size of the map canvas is unknown a priori. We highlight the projection with a height-to-width ratio of 0.6:1, which we call the Compact Miller projection because it is inspired by the Miller Cylindrical projection. Unlike the Miller Cylindrical projection, the Compact Miller projection has a smaller height-to-width ratio and shows the world with less areal distortion at higher latitudes. A user study with 448 participants verified that the Compact Miller – together with the Plate Carrée projection – is the most preferred cylindrical compromise projection.     

Equal arc ratio projection and a new spherical triangle quadtree model

A projection family, named Equal Arc Ratio Projection (EARP), is proposed in this paper, which has two kinds of geometric cases. Coordinates in the projections are determined by the ratios between four special arcs. The projection for spherical octahedron is derived, which is available for Dutton's Quaternary Triangular Mesh (QTM), and both projections of Goodchild's and Otoo's for QTM are found to be two special implementations of EARP. The icosahedral projection and thus the corresponding spherical triangle quadtree partition model are also developed. The partition model is compared with several other global grid models.     

NASA无人机交通管理系统飞行验证试验概述

随着民用无人机在物流配送、地理信息探测和应急救援等领域的快速发展,美国联邦航空局(FAA)和美国航空航天局(NASA)合作开发了无人机交通管理系统(UTM),并开展了大量的验证试验。根据技术难度,NASA将运行技术和相关的飞行验证试验分为4个技术能力水平阶段,其中第三和第四阶段是UTM试验的核心阶段,也是技术难度最高的2个阶段。论文整理了美国无人机交通管理系统第三和第四技术能力水平阶段的飞行验证试验,根据各项关键技术,对试验内容及运行场景等进行了概述,总结了相关试验经验,对中国无人机运行管理系统的试验设计提出了建议。     

A discrete global grid system for earth system modeling

To support Earth system modeling, we propose a discrete global grid system that expresses multi-resolution spatial data. Specifically, a unified coding model that expresses a grid of nodes, edges, and cells is constructed for a triangular discrete global grid system. To fulfill the requirements of practical applications, we design a code-based topological query method for this grid system and an algorithm to transform between grid codes and geographic coordinates. We evaluate the Global Finite Volume Community Ocean Model (Global-FVCOM) on the triangular discrete global grid system in the proposed uniform coding model. The ocean tidal waves simulated by the Global-FVCOM running on the coded grid are then compared with results obtained using a traditional irregular spherical grid system, and the results display comparable accuracy. The uniform coding model proposed in this paper provides a triangular discrete global grid system that can represent multi-resolution spatial data and can be used in Earth system models. This unified coding model can also be applied to the geographic coordinate system made up of latitudes and longitudes, as well as diamond and hexagonal grids.     

Assessing vegetation cover and biomass in restored erosion areas in Iceland using SPOT satellite data

Due to highly erodible volcanic soils and a harsh climate, livestock grazing in Iceland has led to serious soil erosion on about 40% of the country's surface. Over the last 100 years, various revegetation and restoration measures were taken on large areas distributed all over Iceland in an attempt to counteract this problem. The present research aimed to develop models for estimating percent vegetation cover (VC) and aboveground biomass (AGB) based on satellite data, as this would make it possible to assess and monitor the effectiveness of restoration measures over large areas at a fairly low cost. Models were developed based on 203 vegetation cover samples and 114 aboveground biomass samples distributed over five SPOT satellite datasets. All satellite datasets were atmospherically corrected, and digital numbers were converted into ground reflectance. Then a selection of vegetation indices (VIs) was calculated, followed by simple and multiple linear regression analysis of the relations between the field data and the calculated VIs.Best results were achieved using multiple linear regression models for both %VC and AGB. The model calibration and validation results showed that R² and RMSE values for most VIs do not vary very much. For percent VC, R² values range between 0.789 and 0.822, leading to RMSEs ranging between 15.89% and 16.72%. For AGB, R² values for low-biomass areas (AGB < 800 g/m²) range between 0.607 and 0.650, leading to RMSEs ranging between 126.08 g/m² and 136.38 g/m². The AGB model developed for all areas, including those with high biomass coverage (AGB > 800 g/m²), achieved R² values between 0.487 and 0.510, resulting in RMSEs ranging from 234 g/m² to 259.20 g/m². The models predicting percent VC generally overestimate observed low percent VC and slightly underestimate observed high percent VC. The estimation models for AGB behave in a similar way, but over- and underestimation are much more pronounced.These results show that it is possible to estimate percent VC with high accuracy based on various VIs derived from SPOT satellite data. AGB of restoration areas with low-biomass values of up to 800 g/m² can likewise be estimated with high accuracy based on various VIs derived from SPOT satellite data, whereas in the case of high biomass coverage, estimation accuracy decreases with increasing biomass values. Accordingly, percent VC can be estimated with high accuracy anywhere in Iceland, whereas AGB is much more difficult to estimate, particularly for areas with high-AGB variability.     

二战期间美国地缘战略空间观念变迁 ——基于地图投影的视角

在地图投影变换影响下,得益于多样化的地图服务,二战期间美国地缘战略空间观念经历了从孤立主义向干涉主义的转变,推动了美国的参战与具体战略展开。这一空间逻辑在战时地图投影的选择上表现为从圆柱投影下的二维“矩形世界”向等距方位投影下的“圆形世界”和正射投影下的三维“球体世界”“鸟瞰世界”转变,折射出空中时代下的全球一体观。通过不同投影下“地图空间”的调整,二战期间美国地缘战略空间观念逐渐接近现实地球空间,这无疑增强了美国参战的合理性和战略决策的正确性。作为认知话语和实践话语的统一,地图投影通过地图服务反映并参与到了二战的地缘政治发展进程。伴随着美国地缘战略空间观念的变迁,美国也由此从世界舞台的边缘走向国际体系的中心。在当前中国和平崛起和全球地缘调整的大背景下,地图投影创新也为今后的地缘关系研究提供了诸多启示。     

Mapping Systems and GIS: A Case Study using the Ghana National Grid

The problem of incompatible projections and conversion between mapping systems is of general concern to those involved in the collection of natural resources data. The Ghana National Grid (GNG) is an example of a mapping system that is not defined in image processing and GIS software and for which the transformation parameters are not readily available in the literature. Consequently, integrating GNG topographic map data within a GIS with data derived from other sources can be problematic. In this paper a practical solution for deriving the required transformation parameters to convert from the World Geodetic System of 1984 (WGS84) to the GNG system is demonstrated. The method uses a single geodetic control point, available 1:50 000 topographic maps and a SPOT satellite panchromatic image geo-referenced to GNG. The resultant parameters are applied to road survey data in Universal Transverse Mercator (UTM) format for overlay with the SPOT image. Despite the approximations made in applying the method, when compared against official estimates of the datum transformation parameters, this relatively simple procedure resulted in estimates that appear acceptable in regard to combining data sets at a nominal scale of 1:50000.     

Quality assessment of linear data

This paper presents methods to evaluate the geometric quality of spatial data. Firstly, a point‐based method is presented, adapting conventional assessment methods whereby common points between datasets are compared. In our approach, initial matches are established automatically and refined further through interactive editing. Second, a line‐based method which uses correspondences between line segments is proposed. Here, the geometry of line segments in vector is transformed into a set of rasterized values so that their combination at each pixel can restore their original vector geometry. Matching is performed on rasterized line segments and their matching lengths and displacements are measured. Experimental results show that the line‐based approach proposed is efficient to evaluate the geometric quality of spatial data without requirements of topological relationships among line features.     

A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena

Volunteered geographic information (VGI) contains valuable field observations that represent the spatial distribution of geographic phenomena. As such, it has the potential to provide regularly updated low-cost field samples for predictively mapping the spatial variations of geographic phenomena. The predictive mapping of geographic phenomena often requires representative samples for high mapping accuracy, but samples consisting of VGI observations are often not representative as they concentrate on specific geographic areas (i.e. spatial bias) due to the opportunistic nature of voluntary observation efforts. In this article, we propose a representativeness-directed approach to mitigate spatial bias in VGI for predictive mapping. The proposed approach defines and quantifies sample representativeness by comparing the probability distributions of sample locations and the mapping area in the environmental covariate space. Spatial bias is mitigated by weighting the sample locations to maximize their representativeness. The approach is evaluated using species habit suitability mapping as a case study. The results show that the accuracy of predictive mapping using weighted sample locations is higher than using unweighted sample locations. A positive relationship between sample representativeness and mapping accuracy is also observed, suggesting that sample representativeness is a valid indicator of predictive mapping accuracy. This approach mitigates spatial bias in VGI to improve predictive mapping accuracy.     

基于支撑向量回归的二端元混合像元分解

针对遥感影像混合像元光谱复杂,其非线性特征,传统LSMM分解模型难以进行有效的混合像元分解的不足。通过基于SVR的二端元混合像元分解的研究,从真实遥感影像上获取典型的植被、非植被光谱信息,构造二端元混合光谱库,进行SVR模型的混合像元分解。当样本量为6%时,交叉验证获得最佳模型参数（C=1024.0和g=4.0）,进一步对全部混合像元进行混合像元分解。实验结果表明：SVR分解结果RMSE为5.95,R²为0.958,优于LSMM方法（RMSE=7.71,R²=0.932）,且在各个不同真值丰度下具有更好的稳定性,证明该方法对于非线性混合光谱具有很好的学习和推广能力。此外,该方法的精度不随训练样本量的增加呈明显变化,体现出SVR在有限样本情况下能够保证高效率的训练能力。     

Positional accuracy improvement: a comparative study in Shanghai,China

With the rapid development of geospatial data capture technologies such as the Global Positioning System, more and higher accuracy data are now readily available to upgrade existing spatial datasets having lower accuracy using positional accuracy improvement (PAI) methods. Such methods may not achieve survey-accurate spatial datasets but can contribute to significant improvements in positional accuracy in a cost-effective manner. This article addresses a comparative study on PAI methods with applications to improve the spatial accuracy of the digital cadastral for Shanghai. Four critical issues are investigated: (1) the choice of improvement model in PAI adjustment; five PAI models are presented, namely the translation, scale and translation, similarity, affine, and second-order polynomial models; (2) the choice of estimation method in PAI adjustment; three estimation methods in PAI adjustment are proposed, namely the classical least squares (LS) adjustment, which assumes that only the observation vector contains error, the general least squares (GLS) adjustment, which regards both the ground and map coordinates of control points as observations with errors, and the total least squares (TLS) adjustment, which takes the errors in both the observation vector and the design matrix into account; (3) the impact of the configuration of ground control points (GCPs) on the result of PAI adjustment; 12 scenarios of GCP configurations are tested, including different numbers and distributions of GCPs; and (4) the deformation of geometric shape by the above-mentioned transformation models is presented in terms of area and perimeter.

The empirical experiment results for six test blocks in Shanghai demonstrated the following. (1) The translation model hardly improves the positional accuracy because it accounts only for the shift error within digital datasets. The other four models (i.e., the scale and translation, similarity, affine, and second-order polynomial models) significantly improve the positional accuracy, which is assessed at checkpoints (CKPs) by calculating the difference between the updated coordinates transformed from the map coordinates and the surveyed coordinates. On the basis of the refined Akaike information criterion, the two best optimal transformation models for PAI are determined as the scale and translation and affine transformation models. (2) The weighted sum of square errors obtained using the GLS and TLS methods are much less than those obtained using the classical least squares method. The result indicates that both the GLS and TLS estimation methods can achieve greater reliability and accuracy in PAI adjustment. (3) The configuration of GCPs has a considerable effect on the result of PAI adjustment. Thus, an optimal configuration scheme of GCPs is determined to obtain the highest positional accuracy in the study area. (4) Compared with the deformations of geometric shapes caused by the transformation models, the scale and translation model is found to be the best model for the study area.     

Sensitivity of a stochastic land-cover change model to pixel versus polygonal land units

Land-use/cover change (LUCC) projections can be generated by a variety of land-cover change models (LCMs) and applied to a range of ecological and environmental studies. Most existing spatially explicit LCMs represent land use or cover using either pixel or polygon/patch spatial units. However, the effects of the choice to use pixel versus polygonal land units on the outputs from any given model have not yet been systematically assessed. We evaluated the impacts of alternative land units on the performance of a LCM. A stochastic LCM based on a geostatistical algorithm was developed and applied using both pixel and polygons, which were derived from parcel maps. Nine possible parcel-change scenarios were generated to evaluate the effects of geometric change in management boundaries. The approach was tested through the simulation of multiple land-cover transitions in Medina County, Ohio, between 1992 and 2011. Performance of the simulations was assessed using a metric for the accuracy of spatial allocations (figure of merit (FoM)) and several landscape pattern metrics describing the shapes and sizes of resulting land-cover patches. Results support the notion that there is a clear trade-off between pixel and polygon land units: using polygon boundaries is helpful in obtaining more realistic spatial patterns, but at the cost of location accuracy. Significant differences were found among different parcel-change scenarios on both location accuracy and spatial patterns, with the primary effects being dependent on the type of land-cover transition and the resolution at which validation was assessed.     

Special Issue on parallel processing in GIS

This paper explores three theoretical approaches for estimating the degree of correctness to which the accuracy figures of a gridded Digital Elevation Model (DEM) have been estimated depending on the number of checkpoints involved in the assessment process. The widely used average‐error statistic Mean Square Error (MSE) was selected for measuring the DEM accuracy. The work was focused on DEM uncertainty assessment using approximate confidence intervals. Those confidence intervals were constructed both from classical methods which assume a normal distribution of the error and from a new method based on a non‐parametric approach. The first two approaches studied, called Chi‐squared and Asymptotic Student t, consider a normal distribution of the residuals. That is especially true in the first case. The second case, due to the asymptotic properties of the t distribution, can perform reasonably well with even slightly non‐normal residuals if the sample size is large enough. The third approach developed in this article is a new method based on the theory of estimating functions which could be considered much more general than the previous two cases. It is based on a non‐parametric approach where no particular distribution is assumed. Thus, we can avoid the strong assumption of distribution normality accepted in previous work and in the majority of current standards of positional accuracy. The three approaches were tested using Monte Carlo simulation for several populations of residuals generated from originally sampled data. Those original grid DEMs, considered as ground data, were collected by means of digital photogrammetric methods from seven areas displaying differing morphology employing a 2 by 2 m sampling interval. The original grid DEMs were subsampled to generate new lower‐resolution DEMs. Each of these new DEMs was then interpolated to retrieve its original resolution using two different procedures. Height differences between original and interpolated grid DEMs were calculated to obtain residual populations. One interpolation procedure resulted in slightly non‐normal residual populations, whereas the other produced very non‐normal residuals with frequent outliers. Monte Carlo simulations allow us to report that the estimating function approach was the most robust and general of those tested. In fact, the other two approaches, especially the Chi‐squared method, were clearly affected by the degree of normality of the residual population distribution, producing less reliable results than the estimating functions approach. This last method shows good results when applied to the different datasets, even in the case of more leptokurtic populations. In the worst cases, no more than 64–128 checkpoints were required to construct an estimate of the global error of the DEM with 95% confidence. The approach therefore is an important step towards saving time and money in the evaluation of DEM accuracy using a single average‐error statistic. Nevertheless, we must take into account that MSE is essentially a single global measure of deviations, and thus incapable of characterizing the spatial variations of errors over the interpolated surface.