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.     

“These Maps Talk for Us:” Participatory Action Mapping as Civic Engagement Practice

Geographers have long been associated with mapping and cartography, because the visual representation of space fits neatly into the wide-ranging discipline that engages both the physical and the social worlds. Mapmaking remained in the domain of experts for centuries until the advent of new mapping technologies, which have widened the possibilities for mapmaking from experts and nonexperts alike. Simply widening participation in mapmaking does not necessarily democratize the knowledge-production process, however, as scholars have recently argued. What is required, we suggest, are critically trained geographers who take seriously both the conventions of professional cartography and the power relations embedded in and reflected in the map-making process and in maps themselves. We name participatory action mapping (PAM) as a methodology that seeks to be as effective in advancing the mapping needs of the public as it is critical in evaluating the processes through which maps are produced. PAM is a practice of civic engagement that borrows from community mapping and public participatory geographic information systems and that is deeply informed by participatory action research. We highlight the contours of PAM through a case study of our work with the Westside Atlanta Land Trust in Atlanta, Georgia.     

中国现代地貌制图研究的薄弱环节

本文从六个方面:规范化研究、制图时段、地貌图的种类、制图区域、地貌分类与图例系统、地貌图图型和表示方法研究,讨论了中国现代地貌制图研究中存在的问题和不足,提出了改进意见.     

顾及语义差异的基础地理信息客户数据库更新实施模型

客户数据库更新就是利用新版基础地理数据库中更新变化的要素信息,对客户数据库进行相应的级联更新,以使其具有良好现势性的过程。现有研究大多侧重于基础地理数据库更新信息的分发与提供,而没有充分考虑语义差异环境下如何高效实施客户数据库更新的具体问题。针对此,该文概括了基础地理数据库与其客户数据库之间潜在的各种语义差异;从实施效率、数据完备性、一致性、正确性等方面,分析描述了语义差异给更新实施过程带来的不利影响;最后依据语义映射和转换理论,提出了由语义匹配、变化提取、更新集成3种基本操作组成的更新实施模型,并阐述了3种基本操作的执行策略和关键环节。     

ERS SAR干涉测量技术用于区域尺度森林制图研究

光学遥感数据由于受云雾的影响，很难在区域尺度上获得时间一致的图像，而微波遥感数据又一直无法提供足够的类型信息。雷达干涉测量技术的出现解决了这一瓶颈问题，雷达干涉相关值影像已经成功地用于土地利用分类。该文论述了干涉土地利用影像(ILU)的生成、基于ILU影像的森林分类方法、大区域ILU影像的几何纠正及镶嵌技术，并利用ERS SAR串行轨道数据生成的ILU影像成功地对我国东北三省进行了森林制图，其分类平均精度在82％以上。     

Bridging theory and implementation – Testing an abstract classification system for practical mapping by field survey and 3D aerial photographic interpretation

ABSTRACT

The abstract classification system Nature in Norway (NiN) has detailed ecological definitions of a high number of ecosystem units, but its applicability in practical vegetation mapping is unknown because it was not designed with a specific mapping method in mind. To investigate this further, two methods for mapping – 3D aerial photographic interpretation of colour infrared photos and field survey – were used to map comparable neighbouring sites of 1 km² in Hvaler Municipality, south-eastern Norway. The classification accuracy of each method was evaluated using a consensus classification of 160 randomly distributed plots within the study sites. The results showed an overall classification accuracy of 62.5% for 3D aerial photographic interpretation and 82.5% for field survey. However, the accuracy varied for the ecosystem units mapped. The classification accuracy of ecosystem units in acidic, dry and open terrain was similar for both methods, whereas classification accuracy of calcareous units was highest using field survey. The mapping progress using 3D aerial photographic interpretation was more than two times faster than that of field survey. Based on the results, the authors recommend a method combining 3D aerial photographic interpretation and field survey to achieve effectively accurate mapping in practical applications of the NiN system.     

The fractal nature of maps and mapping

A fractal can be simply understood as a set or pattern in which there are far more small things than large ones, for example, far more small geographic features than large ones on the earth surface, or far more large-scale maps than small-scale maps for a geographic region. This article attempts to argue and provide evidence for the fractal nature of maps and mapping. It is the underlying fractal structure of geographic features, either natural or man-made, that make reality mappable, large-scale maps generalizable, and cities imageable. The fractal nature is also what underlies the beauty of maps. After introducing some key fractal concepts such as recursion, self-similarity, scaling ratio, and scaling exponent, this article demonstrates that fractal thought is rooted in long-standing map-making practices such as series maps subdivision, visual hierarchy, and Töpfer’s radical law. Drawing on previous studies on head/tail breaks, mapping can be considered a head/tail breaks process; that is to divide things around an average, according to their geometric, topological and/or semantic properties, into the head (for those above the average) and the tail (for those below the average), and recursively continue the dividing process for the head for map generalization, statistical mapping, and cognitive mapping. Given the fractal nature of maps and mapping, cartography should be considered a perfect combination of science and art, and scaling must be formulated as a law of cartography or that of geography in general.     

Classification of Soil Groups Using Weights-of-Evidence-Method and RBFLN-Neural Nets

Weights-of-Evidence (WofE) and Radial Basis Function Link Net (RBFLN) were applied to soil group mapping in eastern Finland. The data consisted of low altitude airborne geophysical measurements, Landsat 5 TM-satellite image, and digital elevation model (DEM) and slope information derived from it. Probability maps were constructed for each soil group one by one and combined into a prediction map of soil groups using maximum posterior probability (WofE) or pattern membership (RBFLN). Self-Organizing Map (SOM) and Sammon’s Mapping were applied for selecting the data sets for modeling and visualizing the data. The soil types belonging to each soil group used in the Arc-SDM modeling were defined by clusters revealed by the SOM and Sammon’s Mapping algorithms. The soil types with similar characters were collected in the same cluster. Numerical evaluation of the models’ performance was performed using the confusion matrix. The Ratio of Correct Classifications (RCC) for the best WofE model was 0.64 in the training area and 0.61 in the testing area. The RCC for the best RBFLN model was 0.62. Modeling of soil groups using Arc-SDM is time consuming because models need to be constructed for each soil group before combining them into a final prediction map. In this study a simple method was tested for combining the maps. In the future, more attention should be paid to combining the posterior probability models and also to selecting data sets used for modeling.     

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.     

Application of Radial Basis Functional Link Networks to Exploration for Proterozoic Mineral Deposits in Central Iran

The metallogeny of Central Iran is characterized mainly by the presence of several iron, apatite, and uranium deposits of Proterozoic age. Radial Basis Function Link Networks (RBFLN) were used as a data-driven method for GIS-based predictive mapping of Proterozoic mineralization in this area. To generate the input data for RBFLN, the evidential maps comprising stratigraphic, structural, geophysical, and geochemical data were used. Fifty-eight deposits and 58 ‘nondeposits’ were used to train the network. The operations for the application of neural networks employed in this study involve both multiclass and binary representation of evidential maps. Running RBFLN on different input data showed that an increase in the number of evidential maps and classes leads to a larger classification sum of squared error (SSE). As a whole, an increase in the number of iterations resulted in the improvement of training SSE. The results of applying RBFLN showed that a successful classification depends on the existence of spatially well distributed deposits and nondeposits throughout the study area. An erratum to this article can be found at     

Participatory risk mapping of garbage‐related issues in a rural mexican municipality

Garbage generation and garbage management are two critical human‐environmental issues in Mexico and across the globe. Yet, an understanding of garbage as a broader set of human environmental issues beyond generation and management is lacking, amid a significant urban bias on garbage research. Using a modified form of participatory risk mapping, a method that rank‐orders risks or issues by incidence and relative importance, this study highlights the diversity and heterogeneity of garbage‐related issues as reported by 433 respondents in the rural Mexican municipio of Coxcatlán, Puebla. Results show that burning, dumping, service provision, public cleanliness, and other issues affect rural households. When the data are stratified by place and demographics, and applied to inferential statistics, the results show a more nuanced, more place‐contingent picture of garbage‐related issues than simply the institutional narratives on generation and composition.     

Australian ‘gayborhoods’ and ‘lesborhoods’: a new method for estimating the number and prevalence of adult gay men and lesbian women living in each Australian postcode

ABSTRACT

Gay men and lesbian women often demonstrate unique settlement patterns, forming what have been referred to as ‘gayborhoods’. This study sought to provide the first postcode-level estimates of population size and prevalence of gay and lesbian people in Australia. Data on same-gender-partnered households from the Australian Census were combined with information from six different surveys conducted from 2011 to 2017. We estimated that in 2016 there were 132,203 gay men (1.5% of adult males; 95% CI: 1.4–1.6) and 79,931 lesbian women (0.9% of adult females; 95% CI: 0.8–1.0) in Australia. While many postcodes were sparsely populated by gay and lesbian people (40.1% had prevalences of <0.1%), 24.6% were moderately populated (prevalences in the 50-95th percentile) and 2.7% were highly populated (95th percentile). By jurisdiction, the Australian Capital Territory had the highest prevalences of gay men (2.1%; 95% CI: 2.0–2.2) and lesbian women (1.5%; 95% CI: 1.4–1.6). Although the majority of highly populated postcodes were found in major cities (83.7%), some were also found in regional and remote area (16.3%). This method can be applied in other countries to enhance populate estimates. The accompanying dataset can be used to guide service delivery, conduct geographically contextualised research and develop policies relevant to gay men and lesbian women in Australia.     

Applied Geography and New Geographies

Scale and resolution have long been key issues in geography. The rapid development of analytical cartography, GIS, and remote sensing (the mapping sciences) in the last decade has forced the issues of scale and resolution to be treated formally and better defined. This paper addresses the problem of scale and resolution in geographical studies, with special reference to the mapping sciences. The fractal concept is introduced, and its use in identifying the scale and resolution problem is discussed. The implications of the scale and resolution problem on studies of global change and modeling are also explored.