Use of cartographic images by expert and novice field geologists in planning fieldwork routes

Topographic maps and aerial photographs are particularly useful when geoscientists are faced with fieldwork tasks such as selecting paths for observation, establishing sampling schemes, or defining field regions. These types of images are crucial in bedrock geologic mapping, a cognitively complex field-based problem-solving task. Geologic mapping requires the geologist to correctly identify rock types and three-dimensional bedrock structures from often partial or poor-quality outcrop data while navigating through unfamiliar terrain. This paper compares the walked routes of novice to expert geologists working in the field (n = 66) with the results of a route planning and navigation survey of a similar population of geologists (n = 77). Results show clearly that those geologists with previous mapping experience make quick and decisive determinations about field areas from available imagery and maps, regardless of whether they are or not physically present in the field area. Recognition of geologic features enabled experts to form and verbalize a specific plan for travel through a landscape based on those features. Novices were less likely to develop specific travel route plans and were less likely to identify critical landscape cues from aerial photographs.     

Computer-aided design of bus route maps

The bus route map is a diagram that aims to convey necessary information for map readers to find an appropriate way of moving from an origin to a destination. Design of bus route map is a complicated and time-consuming task that requires careful consideration of readability and aesthetics. This paper proposes a new computational method for designing bus route maps. The method helps us to reduce six types of undesirable elements in bus route maps, i.e., gap, shift, crossing, overlap, misalignment, and acute bend. The method consists of two phases: line layout phase determines the relative order of bus routes on each road segment and map layout phase calculates the actual position of bus routes drawn on a map. This paper applies the method to the design of bus route maps of Chiba City, Japan. The result supports the effectiveness of the method as well as reveals open topics for future research.     

北京飞云瀑景点崩塌地质灾害分析及防治方法研究

近15年来,北京飞云瀑景点附近发生过2次大规模崩塌,崩塌堆积岩块体积累计达450 m3,崩塌岩块已滚落覆盖至景区小路。经勘查,确定了1处危岩体及1处危岩带,该危岩体及危岩带对本景点的正常观赏及过往游人构成极大威胁。本文对该景点的崩塌地质灾害地质特征进行了简要介绍;对地质灾害成因、自然发展趋势等进行了初步探讨;对危岩体(带)的稳定性进行了计算、分析及评价;对可能采用的治理方法进行了比选分析。为了最大程度地保护景观资源,最终选择了以避让为主的治理措施,并对选定的治理方案及计算进行了阐述。     

50年来北海市滨海湿地景观格局变化及其驱动机制

以1955~2004年遥感影像为数据源,结合野外调查,运用景观生态学原理,研究50 a间北海市滨海湿地的景观格局及其动态变化。结果表明,50 a间北海市滨海湿地呈整体退化趋势,潮间砂质海滩、潮间淤泥质海滩、红树林滩、小型岛屿湿地减少;景观格局指数显示1977年、1998年是北海市滨海湿地较明显变化的拐点。1977年人类活动影响增加,滨海湿地稍有退化,湿地景观多样性指数减小,优势度指数增加,均匀度指数减小、景观总面积指数降至最低值。1988年湿地保护力度加大,湿地略为好转,景观多样性指数、优势度指数、均匀度指数则呈相反规律。1998年湿地受到的极端气候灾害、人类干扰程度加大,平均斑块分形维数下降,斑块密度指数、景观斑块数破碎化指数呈最高值。湿地景观格局指数的变化,反映了围垦改造、互花米草的生物入侵、城市污染、极端气候灾害等对景观格局的影响,人类活动是北海市滨海湿地景观格局变化的主要驱动因子。     

Possibilities of land use change analysis in a mountainous rural area: a methodological approach

Decreasing population density is a current trend in the European Union, and causes a lower environmental impact on the landscape. However, besides the desirable effect on the regeneration processes of semi-natural forest ecosystems, the lack of traditional management techniques can also lead to detrimental ecological processes. In this study we investigated the land use pattern changes in a micro-region (in North-Eastern Hungary) between 1952 and 2005, based on vectorised land use data from archive aerial photos. We also evaluated the methodology of comparisons using GIS methods, fuzzy sets and landscape metrics. We found that both GIS methods and statistical analysis of landscape metrics resulted in more or less the same findings. Differences were not as relevant as was expected considering the general tendencies of the past 60 years in Hungary. The change in the annual rate of forest recovery was 0.12%; settlements extended their area by an annual rate of 3.04%, while grasslands and arable lands had a net loss in their area within the studied period (0.60% and 0.89%, respectively). The kappa index showed a smaller similarity (~60%) between these dates but the fuzzy kappa and the aggregation index, taking into account both spatial and thematic errors, gave a more reliable result (~70–80% similarity). Landscape metrics on patch and class level ensured the possibility of a detailed analysis. We arrived at a similar outcome but were able to verify all the calculations through statistical tests. With this approach we were able to reveal significant (p < 0.05) changes; however, effect sizes did not show large magnitudes. Comparing the methods of revealing landscape change, the approach of landscape metrics was the most effective approach, as it was independent of spatial errors and ensuring a multiple way of interpretation.     

Unsupervised regionalization of the United States into landscape pattern types

We present a pattern-based regionalization of the conterminous US – a partitioning of the country into a number of mutually exclusive and exhaustive regions that maximizes the intra-region stationarity of land cover patterns and inter-region disparity between those patterns. The result is a discretization of the land surface into a number of landscape pattern types (LPTs) – spatial units each containing a unique quasi-stationary pattern of land cover classes. To achieve this goal, we use a recently developed method which utilizes machine vision techniques. First, the entire National Land Cover Dataset (NLCD) is partitioned into a grid of square-size blocks of cells, called motifels. The size of a motifel defines the spatial scale of a local landscape. The land cover classes of cells within a motifel form a local landscape pattern which is mathematically represented by a histogram of co-occurrence features. Using the Jensen–Shannon divergence as a dissimilarity function between patterns we group the motifels into several LPTs. The grouping procedure consists of two phases. First, the grid of motifels is partitioned spatially using a region-growing segmentation algorithm. Then, the resulting segments of this grid, each represented by its medoid, are clustered using a hierarchical algorithm with Ward’s linkage. The broad-extent maps of progressively more generalized LPTs resulting from this procedure are shown and discussed. Our delineated LPTs agree well with the perceptual patterns seen in the NLCD map.     

Exploring the spatial distribution patterns of South African Cape hakes using generalised additive models

We developed delta generalised additive models (GAMs) to predict the spatial distribution of different size classes of South African hakes, Merluccius capensis and M. paradoxus, using demersal trawl survey data and geographical (latitude and longitude) and environmental features (depth, temperature, bottom dissolved oxygen and sediment type). Our approach consists of fitting, for each hake size class, two independent models, a binomial GAM and a quasi-Poisson GAM, whose predictions are then combined using the delta method. Delta GAMs were validated using an iterative cross-validation procedure, and their predictions were then employed to produce distribution maps for the southern Benguela. Delta GAM predictions confirmed existing knowledge about the spatial distribution patterns of South African hakes, and brought new insights into the factors influencing the presence/absence and abundance of these species. Our GAM approach can be used to produce distribution maps for spatially explicit ecosystem models of the southern Benguela in a rigorous and objective way. Ecosystem models are critical features of the ecosystem approach to fisheries, and distribution maps constructed using our GAM approach will enable a reliable allocation of species biomasses in spatially explicit ecosystem models, which will increase trust in the spatial overlaps and, therefore, the trophic interactions predicted by these models.     

Spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015

China has experienced unprecedented urbanization in the past decades, resulting in dramatic changes in the physical, limnological, and hydrological characteristics of lakes in urban landscapes. However, the spatiotemporal dynamics in distribution and abundance of urban lakes in China remain poorly understood. Here, we characterized the spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015 using remote-sensing data and landscape metrics. The results showed that the urban lake landscape patterns have experienced drastic changes over the past 25 years. The total surface area of the urban lakes has decreased by 17,620.02?ha, a decrease of 24.22%, with a significant increase in the landscape fragmentation and a reduction in shape complexity. We defined three lake-shrinkage types and found that vanishment was the most common lake-shrinkage pattern, followed by edge-shrinkage and tunneling in terms of lake area. Moreover, we also found that urban sprawl was the dominant driver of the lake shrinkage, accounting for 67.89% of the total area loss, and the transition from lakes to cropland was also an important factor (19.86%). This study has potential for providing critical baseline information for government decision-making in lake resources management and urban landscape design.     

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.     

Measured and perceived visual complexity: a comparative study among three online map providers

We present a study on human perception of map complexity, with the objective of better understanding design decisions that may lead to undesirable levels of complexity in web maps. We compare three complexity metrics to human ratings of complexity obtained through a user survey. Specifically, we use two algorithmic approaches published by others, which measure feature congestion (FC) and subband entropy (SE), as well as our own approach of counting object types rather than individual objects. We compare these metrics with each other as well as with human complexity ratings for three maps of the same area from map providers Google Maps, Bing Maps, and OpenStreetMap. Each map design is assessed at three different scales (levels of detail). We find that (1) the FC and SE metrics appear to be adequate predictors of what humans consider complex; (2) object-type counts are slightly less successful at predicting human-rated complexity, implying that clutter is more important in perceived complexity than diversity of symbology; and (3) generalization choices do impact human complexity ratings. These findings contribute to our understanding of what makes a map complex, with implications for designing maps that are easy to use.