Benefits and drawbacks of two modelling approaches for a generalist carnivore: can models predict where Wile E. Coyote will turn up next?

Wildlife ecologists frequently make use of limited information on locations of a species of interest in combination with readily available GIS data to build models to predict space use. In addition to a wide range of statistical data models that are more commonly used, machine learning approaches provide another means to develop predictive spatial models. However, comparison of output from these two families of models for the same data set is not often carried out. It is important that wildlife managers understand the pitfalls and limitations when a single set of models is used with limited GIS data to try to predict and understand species distribution. To illustrate this, we carried out two sets of models (generalized linear mixed models (GLMMs) and boosted regression trees (BRTs)) to predict geographic occupancy of the eastern coyote (Canis latrans) on the island of Newfoundland, Canada. This exercise is illustrative of common spatial questions in wildlife research and management. Our results show that models vary depending on the approach (GLMM vs. BRT) and that, overall, BRT had higher predictive ability. Although machine learning has been criticized because it is not explicitly hypothesis-driven, it has been used in other areas of spatial modelling with success. Here, we demonstrate that it may be a useful approach for predicting wildlife space use and to generate hypotheses when data are limited. The results of this comparison can help to improve other models for species distributions and also guide future sampling and modelling initiatives.     

3S技术在野生动物生境研究中的应用

3S技术可快速、准确、实时地获取、处理空间信息,具有广泛的应用性。该文从野生动物生境格局、生境破碎化、生境因子特性、生境分析模型建立、生境评价和生境恢复建设等方面,综合评述野生动物生境研究中3S的应用问题,并提出野生动物生境研究将朝着3S技术集成、GIS与数学模型结合、数据可视化模拟、网络化和智能化的方向发展。     

Prediction of Anopheles minimus habitat in India—a tool for malaria management

This paper reports research to predict the distribution of An. minimus, a malaria vector in forest fringe areas using GIS to support precision surveys for malaria control. Because An. minimus is a forest‐associated species, generalized thematic maps (1:6?000?000) of forest cover, soil type, altitude, rainfall and temperature were used. Digitization, overlaying, integration and analysis of thematic maps were done using Arc/Info 8.1 NT and Arc/View 3.2 (GIS, ESRI) software. GIS delineated favourable areas for An. minimus where the species is likely to be found, and precision surveys can be conducted. Precision field surveys in selected locations of favourable/non‐favourable areas were carried out. The species could be found in all locations designated as a favourable area and was absent in non‐favourable areas. In two districts, one where the species is reported to have disappeared in the early 1950s and the other where it was not reported in earlier surveys, GIS helped in precision surveys, and An. minimus was found. The technique can quickly cover vast and inaccessible areas and is easy to duplicate in other parts of the world to assist cost‐effective control of malaria. It can also delineate areas favourable for any species of flora and fauna to help precision surveys.     

Spatial video and GIS

GIS elemental unit representations of spatial data are often defined in terms of points, lines and areas. However, another type of spatial data that is becoming frequently captured, but as yet is largely ignored in GIS, is that of video. While digital video recording is a commonly encountered medium in modern society and encompasses many forms, from simple personal camcorders through to sophisticated survey and surveillance systems, its geographical representation in a GIS has not been fully examined or realised. In the majority of cases the video footage is usually captured while the device and/or the objects being viewed are in motion. What is of particular interest is when video streams can be, or have been, associated with spatial data such as location and orientation to create geographically referenced videographic data, which, for simplicity, will be defined as spatial video. Fundamentally, the nature of video is to record space, so when spatial properties can be accurately acquired and associated with this footage, an important geographical element can be considered for integration and analysis within a GIS.

Existing spatial video systems, both commercial and research, are predominantly used in survey or LBS roles and are usually bespoke and application specific. These systems do not model spatial video to any recognised standards that is generalised to be both data and platform independent. They do not support GIS integration and/or analysis from a purely spatial content perspective. A video-image/remote-sensing centric approach prevails where usage options range from simple visualisation interfaces to interactive computer vision systems. What has been largely overlooked is a spatial approach where the inherent geographical extent recorded in each video frame can be modelled and used in a geo-spatial analysis context. While this modelling approach has not been fully realised, it does exist in a GIS form based on Open Geospatial Consortium standards, where the spatial context of video is defined in a structure called a ViewCone. However, a ViewCone only defines a 2D model of the geographical extent of each frame and is restricted to a three-or-five sided polygon representation.

Thus, this article examines the potential of modelling spatial video through the use of elemental data types within GIS; gives some examples of using this approach; describes some problems in using spatial video within GIS; and then demonstrates how these problems are being solved. This is done in three stages: Firstly, a detailed overview of spatial video in its current GIS role is provided – this is achieved through a complete introduction to the distinct elements of spatial video followed by a review of its use in both commercial and academic application areas. Secondly, a brief theoretical overview of an alternative GIS-constrained ViewCone data structure is given that defines a more flexible spatial video model for both 2D and 3D GIS analysis and visualisation. Thirdly, a selective sample of results is presented based on an implementation of this approach being applied to a constrained spatial video data source in a specific study area.     

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.     

A dimension-independent extrusion algorithm using generalised maps

One solution to the integration of additional characteristics, for example, time and scale, into GIS data sets is to model them as extra geometric dimensions perpendicular to the spatial ones, creating a higher-dimensional model. While this approach has been previously described and advocated, it is scarcely used in practice because of a lack of high-level construction algorithms and accompanying implementations. We present in this paper a dimension-independent extrusion algorithm permitting us to construct from any (n–1)-dimensional linear cell complex represented as a generalised map, an n-dimensional one by assigning to each (n–1)-cell one or more intervals where it exists along the nth dimension. We have implemented the algorithm in C++11 using CGAL, made the source code publicly available and tested it in experiments using real-world 2D GIS data sets which were extruded to construct up to 5D models.     

Spatial Analysis Techniques as Successful Mineral-Potential Mapping Tools for Orogenic Gold Deposits in the Northern Fennoscandian Shield,Finland

Geoscientific Information Systems (GIS) provide tools to quantitatively analyze and integrate spatially referenced information from geological, geophysical, and geochemical surveys for decision-making processes. Excellent coverage of well-documented, precise and good quality data enables testing of variable exploration models in an efficient and cost effective way with GIS tools. Digital geoscientific data from the Geological Survey of Finland (GTK) are being used widely as spatial evidence in exploration targeting, that is ranking areas based on their exploration importance. In the last few years, spatial analysis techniques including weights-of-evidence, logistic regression, and fuzzy logic, have been increasingly used in GTK’s mineral exploration and geological mapping projects. Special emphasis has been put into the exploration for gold because of the excellent data coverage within the prospective volcanic belts and because of the increased activity in gold exploration in Finland during recent years. In this paper, we describe some successful case histories of using the weights-of-evidence method for the Au-potential mapping. These projects have shown that, by using spatial modeling techniques, exploration targets can be generated by quantitatively analyzing extensive amounts of data from various sources and to rank these target areas based on their exploration potential.     

空间分析技术与地理信息系统的结合*

空间分析和地理信息系统是两种有效的空间信息分析和处理技术,二者的结合一方面可以大大拓展GIS的空间分析功能,另一方面也可使得迅速发展的空间分析得到GIS的有力支持,文中对此进行了探讨,并分析了二者结合的途径。     

Multicriteria Geologic Data Analysis for Mineral Favorability Mapping: Application to a Metal Sulphide Mineralized Area,Ribeira Valley Metallogenic Province,Brazil

GIS techniques have been used in the evaluation of favorability for base-metal mineralization in an area comprising the Cerro Azul and Apiaí quadrangles (SG.22-X-B-IV and V, scale 1:100.000), Ribeira Valley, São Paulo and Paraná States, Brazil. Methods have been employed for selection and weighting of prospective variables when applying GIS techniques to a digital database consisting of geological, geochemical and airborne geophysics, and mineral occurrence information. The exploration variable selection and analysis were based on two mineralization models: (1) Panelas type, vein-type carbonate hosted, and (2) Perau type, sedimentary-exhalative. The overlay was performed by weighted linear combination (WLC) and order weighted average (OWA) methods. Both methods proved suitable for the study area, yielding similar results. The ordered weighted averaging analysis provided the best results, with favorability maps showing a large number of classes occupying relatively minor areas. In comparison, the weighted linear combination analysis produced more coherent results but without details for minor areas. The prospective parameters obtained are considered suitable for both Perau and Panelas types. Both methods are inexpensive, and are suitable for selection of prospective areas during geological surveys in areas similar to the studied one.     

Integration of linear programming and GIS for land-use modelling

Abstract

Geographical Information Systems (GIS) are becoming basic tools for a wide variety of earth science and land-use applications. This article presents linear programming (LP) as a promising tool for spatial modelling within a GIS. Although LP is not properly a spatial technique, it may be used to optimize spatial distributions or to guide the integration of variables. An example of the use of LP in land-use planning is described, with minimizing rural unemployment as the main goal. Technical, financial and ecological constraints are established to show the influence of several limitations on achieving the optimal solution. LP makes it possible to achieve optimal land-use, where the objective is maximized and the constraints respected. LP can also be used to simulate different planning scenarios, by modifying both the objective function coefficients and the constraints. The integration of LP and GIS is presented in two phases: (i) acquisition of attribute data for the LP model, and (ii) modelling and mapping the results.     

Conflict on the Range: Evaluating Driving Factors of Attitudes Toward Prey Species in Qilianshan

Human-wildlife conflict (HWC) is a global conservation issue of increasing concern, and understanding the factors driving conflict is crucial for preventing or mitigating it. In many parts of China, large human populations and increasing development has led to an escalation in HWC with both carnivore and prey species. In this paper we assess herder attitudes toward blue sheep (Pseudaois nayaur, Hodgson, 1833), white lipped deer (Carvus albirostris, Przewalski, 1883), red deer (Cervus elaphus, Linnaeus, 1758), and marmot (Marmota himalayana Hodgson, 1841) through interview-based surveys conducted in 46 households across 8 villages in Qilianshan National Nature Reserve, Gansu, China. We also examine the perceived impact of three ecological-restoration policies (anti-grazing, sustainable grazing, and grass-planting policies) on livelihoods, and how this affects attitudes toward wildlife. Herders reported neutral attitudes toward wildlife species in general, but reported negative attitudes towards blue sheep. Mixed-effects modeling revealed that herder attitudes toward the target species varied significantly across villages, but other socioeconomic variables had limited explanatory power for attitudes. Furthermore, we found that while policy implementation was negatively perceived by herders, anti-grazing policy implementation and total policy implementation were positively correlated with positive attitudes toward wildlife, highlighting a potential gap between perceived threats and actual threats. Finally, we show that the leading cause of reported livestock death is preventable disease, alleviation of which may help improve attitudes toward wildlife.     

Quantifying soil variability in GIS applications: II Spatial distribution of soil properties

Abstract

Application of Geographical Information Systems (GIS) to environmental problems requires a spatial delineation of soil properties and some a priori knowledge of their variability. In the U.S.A. estimated soil properties are available from soil surveys published by the National Cooperative Soil Survey. However, information on the extent and nature of their variability is generally lacking. To remedy the situation, variability of selected soil properties measured at farm and watershed scales was compared with published values using geostatistical methods. Results showed that the variability of bulk density and hydraulic conductivity can be estimated by comparing regularized variograms of measured and published values. An overlay method was proposed that combines measured and published delineations of soil properties into an overlay with the properties of both. The technique makes it possible to incorporate variability into a GIS analysis using data available from published soil surveys.     

中国土地利用/土地覆盖的多尺度空间分布特征分析

研究了我国土地利用影响因素及其空间规模相关性,采用数理统计与ＧＩＳ手段从多个规模尺度上探讨了我国土地利用的空间分布特征。其结果对全国以及各级政府进行土地利用规划、制定相应的土地开发与利用政策等具有一定的参考意义。     

土地利用变化研究中的GIS空间分析方法及其应用

土地利用变化研究尤其是空间变化研究 ,离不开 GIS的空间分析方法。该方法的数据基础主要是矢量格式的土地利用图件和遥感解译制图成果 ;模型基础包括 GIS的时空数据模型、属性数据模型和提取土地利用变化特征的原理模型 ;而数据处理过程则涉及GIS系统的数据转换功能、编辑功能、空间分析功能、数据库操作功能、空间统计分析功能以及图形显示功能等。本文结合北京市土地利用变化的实例分析 ,从上述三方面详细阐述了 GIS的空间分析方法及其在土地利用变化研究中的应用。     

多分辨率小波分析在线状要素简化中的应用

空间数据的多尺度表达问题已成为GIS研究的重点,也是地图自动综合的瓶颈。智能化的多尺度表达是亟须解决的问题。利用小波分析中的多分辨率分析原理,建立微分角度的线状要素简化模型,结合空间要素多尺度表达的特征,研究空间线状要素的简化方法,并对简化后的图形拓扑一致性做简单分析,实现线状要素的简化。     

Development of a GIS model to enhance macrophyte re-establishment projects

Diverse native aquatic macrophytes serve a number of physical and biological functions in the aquatic environment and provide essential habitat for several fish species. In systems that lack submersed macrophytes, native macrophyte re-establishment can be used to revitalize the aquatic community. Planning re-establishment projects requires knowledge of the system along with the growth requirements of macrophytes. Prior studies have identified factors that are important for macrophyte colonization, persistence, and dispersal. However, deductive approaches to identify macrophyte habitat that is suitable for management application have not been developed. A potential solution to this problem is the incorporation of waterscape-wide variables into a Geographic Information System (GIS) and the use of spatial modeling techniques to identify suitable macrophyte habitat. This provides a scientifically based approach to macrophyte re-establishment planning to make efforts more efficient and to recognize potential coverage. The flexibility, scalability, and topological advantages of using a GIS to identify and visualize habitat allow integration with other spatial ecological variables to improve the management of aquatic resources from plants to fish, including invasive species mitigation. Using Little Bear Creek Reservoir, Alabama, as an example system, we illustrate a GIS modeling process that can be applied to any system where the identification of macrophyte habitat is relevant to aquatic resource management goals.     

Predicting socioeconomic conditions from satellite sensor data in rural developing countries: A case study using female literacy in Assam,India

Social data from census and household surveys provide key information for monitoring the status of populations, but the data utility can be limited by temporal gaps between surveys. Recent studies have pointed to the potential for remotely sensed satellite sensor data to be used as proxies for social data. Such an approach could provide valuable information for the monitoring of populations between enumeration periods. Field observations in Assam, north-east India suggested that socioeconomic conditions could be related to patterns in the type and abundance of local land cover dynamics prompting the development of a more formal approach. This research tested if environmental data derived from remotely sensed satellite sensor data could be used to predict a socioeconomic outcome using a generalised autoregressive error (GAR_err) model. The proportion of female literacy from the 2001 Indian National Census was used as an indicator of socioeconomic conditions. A significant positive correlation was found with woodland and a significant negative correlation with winter cropland (i.e., additional cropping beyond the normal cropping season). The dependence of female literacy on distance to nearest road was very small. The GAR_err model reduced residual spatial autocorrelation and revealed that the logistic regression model over-estimated the significance of the explanatory covariates. The results are promising, while also revealing the complexities of population–environment interactions in rural, developing world contexts. Further research should explore the prediction of socioeconomic conditions using fine spatial resolution satellite sensor data and methods that can account for such complexities.     

A cephalopod fishery GIS for the Northeast Atlantic: development and application

Cephalopod stocks are of increasing economic importance. Cephalopod fisheries show marked inter-annual fluctuations unrelated to fishery landings and effort. Their population dynamics, particularly recruitment, are thought to be strongly susceptible to changes in environmental conditions. This arises in part from the short life cycle, resulting in poor buffering of the population against changing conditions. These characteristics make traditional approaches to stock assessment and fishery management inappropriate. GIS offers a tool to improve understanding of spatio-temporal trends in abundance and facilitate rational management. A cephalopod fishery geographical information system for Northeast Atlantic waters (CFGIS-NEA) was developed. The system covers the area from 28.0° W to 11.0° E, and 34.5° N to 65.5° N. It was designed for investigating cephalopod resource dynamics in relation to environmental variation. It is based on Unix Arc/Info, and PC ArcView, combined with the statistical software package S-PLUS and supported by a database in Microsoft Access. Environmental data (e.g. sea surface temperature and salinity, sea bottom temperature and salinity, and bathymetric data), cephalopod fishery, survey and biological data, from a variety of sources, were integrated in the GIS as coverages, grids, shapefiles, and tables. Special functions were developed for data integration, data conversion, query, visualisation, analysis and management. User-friendly interfaces were developed allowing relatively inexperienced users to operate the system. The spatial and temporal distribution patterns of cephalopod abundance by species, the spatial and temporal relationships between cephalopod abundance and environmental factors, and the spatial and temporal patterns of cephalopod fishing activity were analysed using a combination of visual (qualitative) and quantitative methods. Predictive empirical models, such as GAMs (generalized additive models), were developed for modelling cephalopod abundance using environmental variables.     

格网技术对GIS发展的影响

格网技术作为新一代的Web技术,必将深刻影响GIS的发展。格网计算为数据密集型空间分析提供了资源支持。数据格网为海量空间数据分布式存储、管理、传输、分析提供了一体化的解决方法。格网技术为VRGIS实时场景渲染和海量场景数据存储以及GIS互操作问题的解决提供了一种新思路。格网中的智能体组件动态组装应用软件将对GIS应用开发方式产生重大影响。通过建立空间信息格网可以实现中国GIS产业的跨越式发展。     

论地理信息系统及其在地理学中的地位

地理信息系统技术的兴起代表了地理学发展的一个重要方向。地理信息系统是一门处理地理(空间)数据的综合信息技术,它属于技术地理学的范畴,它为资源与环境的管理和规划以及地理学的研究提供了一个革命性工具。另一方面,地理信息系统的建立和应用又依赖于地理学理论和实用模型的发展。进一步勾通地理信息系统与空间分析之间的关系是目前促进地理信息系统发展的重要课题。