Geospatial modelling for goral habitat evaluation

This study attempts to evaluate the habitat suitability of Chilla Sanctuary of Rajaji National Park for goral(Nemorhaedus goral) spread over 25859 sq km area. The IRS-1B false colour imagery, Survey of India topographical maps and ground observations were used to generate the spatial information on the extent of forest cover, waterholes, slope, settlements and the road network in and around the Sanctuary. The geospatial modelling was attempted using Arc/Info geographic information system (GIS). While proximity to waterholes, open forests with intermittent grasslands and steep slopes (30 degree or more) were considered as favourable conditions, the proximity to roads/settlements and flat terrain was taken as unfavourable condition. The results of this study showed that about 14 per cent area of the Sanctuary is highly to moderately suitable for goral. An additional 5 per cent area becomes available to goralif gujjars (tribals living inside sanctuary) are settled outside the sanctuary. Besides highlighting the endangered condition of the habitat for goral, this study demonstrates potential of remote sensing and GIS techniques for wildlife habitat suitability evaluation.     

Using GIS in Areawide Pest Management: A Case Study in South Dakota

Infestations of corn rootworms (Coleoptera: Chrysomelidae) create economic and environmental concerns in the Corn Belt region of the United States. To supplement the population control tactics of areawide pest management programs, we believe that a better understanding of the spatial relationships between biotic and abiotic or physical factors at the landscape scale is needed. Our research used several geographical information systems (GIS) and spatial analytical techniques to examine relationships between corn rootworm metapopulation dynamics, soil texture, and elevation. Within GIS, several spatially explicit procedures were used that include an interpolation technique, spatial autocorrelation analysis, and contingency analysis. Corn rootworm metapopulation distributions were found to be aggregated and related to soil texture and elevation. We review techniques and discuss our preferences for using particular spatially explicit procedures. The information derived from the spatial analyses demonstrates how GIS can be used in areawide pest management to provide inputs for spatially explicit models to predict future pest populations and formulate more well‐informed pest management decisions. The techniques described in this paper could easily be extended to study the spatial dynamics between other pest populations in agricultural landscapes.     

GML空间数据库系统研究

长期以来,由于GIS数据模型的差异所导致诸多问题一直得不到很好地解决,迫切需要新的数据模型来构建新的空间数据库;大量GML空间数据的涌现,迫切需要研究其存储管理问题。另一方面,传统数据库技术并不适合GML空间数据的存储管理,本原XML数据库技术为GML空间数据的存储管理奠定了一定的基础。在这种环境下,本文从本原XML数据库的角度,对GML空间数据存储问题进行了研究。首先,分析了GML空间数据的特征和存储管理方式,然后,提出了本原GML空间数据库的体系结构。针对GML空间数据的特点,提出了GML空间数据的存储粒度和存储的逻辑模型;最后,在开放源代码数据库Ozone的基础上,实现了本原GML空间数据库的原型系统。     

基于GIS的贝叶斯统计推理技术在印度野牛生境概率评价中的应用

首先给出ＣＯ２倍增下遥感－光合作物产量的概念模型,之后分析未受ＣＯ２倍增的遥感－光合作物产量估测模型;在考虑ＣＯ２倍增对作物产量的影响后,对影响干物质累积的作物光合速率的模型进行修正,进而修正遥感－光合作物产量估测模型。建立ＣＯ２倍增下作物产量影响模型,求取各参数,并在ＣＯ２倍增下对我国华北地区冬小麦产量影响进行填图,表明模型的估测结果有良好的可比性。     

基于GIS的贝叶斯统计推理技术在印度野牛生境概率评价中的应用

目前,ＧＩＳ技术已被广泛应用在野生动物生境研究中。但是,作为空间数据分析和处理工具,ＧＩＳ缺乏进行启发式推理的能力。因此,与擅长于此的贝叶斯统计推理技术相结合则是解决这一问题的重要途径。以西双版纳纳板河流域生物圈保护区为试验区,综合应用ＧＩＳ技术和多元统计技术建立印度野牛生境的两个逻辑斯蒂多元回归模型：趋势表面模型和环境模型,第一个模型的自变量是位置坐标,第二个模型的自变量是一组环境因子,然后应用贝叶斯统计合并这两个模型产生贝叶斯综合模型。结果表明,贝叶斯综合模型优于环境模型,可应用于野生动物生境概率评价。     

A GIS‐based Approach in Support of an Assessment of Food Safety Risks

A Geographical Information System (GIS)‐based approach was developed for the identification of vulnerabilities and the measurement of risks associated with contamination of food systems with biological agents. In this research work, a tight integration of ArcGIS with the Arena simulation tool has been implemented. Arena was used to simulate and track contamination in a food distribution network and transmit the time dependent information to GIS. ArcGIS was employed to provide the primary user interface, process network data, and visualize the results. In addition, the GIS, through its powerful capabilities to process spatial data, could allow decision‐ makers to quickly determine the potential impact of a contamination event, at any stage, as a function of both time and geography. Two contamination scenarios along the farm‐to‐fork chain were examined to show the geographic zone and the proportion of the population affected by the contamination. A constraint Voronoi data structure was developed to define influence zones (these were color coded according to a dynamic risk index), to identify those areas that are at greatest immediate risk as time progresses, and to estimate the population affected by these contamination events. This approach thus appears to have general application to many GIS‐based risk assessment problems.     

GIS in Participatory Research: Assessing the Impact of Landmines on Communities in North-west Cambodia

The view of GIS, adopted by many, as an undemocratic and divisive technology is perhaps most poignant in settings where financial and skills‐based resources are limited, notably in lower‐income countries. Where those countries are also recovering from a period of military conflict there would at first sight seem to be little opportunity for employing GIS as part of a socially‐sensitive approach to ‘development’. This paper explores the potential for using GIS in participatory approaches to gathering and analysing geographical information on human‐environment interactions in post‐conflict settings. We discuss empirical work from northwest Cambodia where GIS and participatory methods have been integrated to assess risk to local communities from landmines and to develop priorities for landmine clearance. In juxtaposing ‘official’, spatially‐referenced data with indigenous geographical knowledge in this study we seek to privilege meaningful geographical understandings over conventional notions of spatial ‘accuracy’. In so doing we carry out a Participatory Mine Impact Assessment (PMIA) to explore spatial activities among local populations in mine‐contaminated communities and to help identify improved strategies for returning refugees in re‐establishing livelihoods.     

Geographic Information Systems for Risk Evaluation: Perspectives on Applications to Environmental Health

Geographic information system (GIS) applications for risk evaluation concerning environmental and ecological health are appearing with greater frequency. In this paper, we devise a conceptual framework for risk evaluation that encompasses and synthesizes several component frameworks (including risk scoping, risk communication, risk assessment (risk analysis), risk management, and risk monitoring) concerning environmental health, and hence human and ecological impacts. The purpose of devising the framework was to understand better where, when, and how GIS might be used for risk evaluation, and to identify gaps in knowledge requiring further research. An examination of 40 publications shows that most of the research done on the use of GIS for risk evaluation concerned applications in risk assessment rather than risk scoping, management, and risk monitoring. A four-level risk assessment framework is proposed, and criteria for evaluating the work are used to clarify what has been accomplished overall and where research opportunities exist. Future directions for the application of GIS in risk evaluation are suggested.     

Decomposing Malaria Mosquito Aquatic Habitat Data into Spatial Autocorrelation Eigenvectors in a SAS/GIS® Module

We present a geostatistical approach that accounts for spatial autocorrelation in malaria mosquito aquatic habitats in two East African urban environments. QuickBird 0.61 m data, encompassing visible bands and the near infra‐red (NIR) bands, were selected to synthesize images of Anopheles gambiae s.l. aquatic habitats in Kisumu and Malindi, Kenya. Field sampled data of An. gambiae s.l. aquatic habitats were used to determine which ecological covariates were associated with An. gambiae s.l. larval habitat development. A SAS/GIS^® spatial database was used to calculate univariate statistics, correlations and perform Poisson regression analyses on the An. gambiae s.l. aquatic habitat datasets. Semivariograms and global autocorrelation statistics were generated in ArcGIS^®. The spatially dependent models indicate the distribution of An. gambiae s.l. aquatic habitats exhibits weak positive autocorrelation in both study sites, with aquatic habitats of similar log‐larval counts tending to cluster in space. Individual anopheline habitats were further evaluated in terms of their covariations with spatial autocorrelation by regressing them on candidate spatial filter eigenvectors. This involved the decomposition of Moran's I statistic into orthogonal and uncorrelated map pattern components using a negative binomial regression. The procedure generated synthetic map patterns of latent spatial correlation representing the geographic configuration of An. gambiae s.l. aquatic habitat locations in each study site. The Gaussian approximation spatial filter models accounted for approximately 13% to 32% redundant locational information in the ecological datasets. Spatial statistics generated in a SAS/GIS^® module can capture spatial dependency effects on the mean response term of a Poisson regression analysis of field and remotely sampled An. gambiae s.l. aquatic habitat data.     

基于GIS技术的县域城市规划数据管理模式应用的研究——以广东省增城市为例

随着近年来GIS技术在城乡规划方面的应用日趋普及,GIS技术在空间数据采集、数据管理与分析等关键环节上的优势也逐渐显露。同时,县域城市城乡规划数据种类繁杂,数据量大,亟需先进的技术手段对其进行有效组织与管理。采用GIS技术对城乡规划数据进行动态管理和更新将给城乡规划带来极大的便利。本文以广东省增城市规划管理信息系统为案例,系统阐述GIS技术在城乡规划数据管理中的应用。     

Cumulative spatial impact layers: A novel multivariate spatio‐temporal analytical summarization tool

Scientific inquiry often requires analysis of multiple spatio‐temporal datasets, ranging in type and size, using complex multi‐step processes demanding an understanding of GIS theory and software. Cumulative spatial impact layers (CSIL) is a GIS‐based tool that summarizes spatio‐temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi‐format, multi‐source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built‐in flexibility of the CSIL tool allows users to answer a range of spatially driven questions. Example applications are provided in this article to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision‐making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSIL provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.     

雅安芦山4.20震后县级单元生态系统风险评价

区域生态风险评价是对各种生态风险及环境问题进行评价和管理的重要手段。针对雅安地震灾区特殊的自然地理及生态环境特征,选取芦山县为研究对象,采用遥感、GIS及SPSS统计分析的方法,通过风险源、风险受体、暴露和易损性分析,建立生态风险综合评价模型,划分生态风险区类型,进而提出生态风险管理对策。结果表明:1)微度和低度生态风险区集中分布在高海拔的森林及草地生态系统,该区生物多样性丰富,抗干扰能力较强,地质灾害及人类活动影响较小;2)中度和高度生态风险区具有沿农田及建设用地生态系统集聚分布的特征,该区地质灾害频繁,地壳活动性较强,生态系统抵抗灾害的能力较差。研究结果可为地震灾区防御、规避风险及安全选址提供科学依据。     

The limits of GIS: Towards a GIS of place

In this article we reflect back on our decade‐long collaboration on the geographies of the Holocaust to argue for a GIS of place. Our previous work on ghettoization in Budapest and on the spatio‐temporal patterns of Jewish persecution in Italy had a marked spatial dimension, both in the research questions we set out to answer and the methods we used, which were largely quantitative. During the course of our research, we progressively came to realize that a spatial perspective favors the voice of the perpetrator and that to fully comprehend and understand the geography of the Holocaust, we needed to engage with the voice of the victim, extend the set of methods and tools used, and broaden our epistemology. While proposing a fully‐fledged model of a qualitative GIS of the places and spaces of the Holocaust is beyond the scope of this article, we: (a) argue for the integration of social network analysis, corpus linguistics, and spatio‐temporal methods and for a mixed‐methods analytical approach and (b) note how the topological and relational foundations we identify as fundamental to a GIS of place parallel the long‐standing call for an “integrated history” of the Holocaust.     

Some thoughts on the integration of spatial analysis and Geographic Information Systems

It is past time for us to examine the relationship that exists between what we commonly call spatial analysis on the one hand, and geographic information systems or GIS on the other. GIS technology is widely used but seems to incorporate only a portion of the tools found in spatial analysis. Spatial analysis can be accused of overly simplistic approaches that severely limit its practical utility. This paper suggests that discarding myopic views and meeting upon a common ground of increased knowledge of modern computing concepts and techniques, including object-orientation, can prove extremely fruitful to both sides.     

Ranking European regions as providers of structural riparian corridors for conservation and management purposes

Riparian zones are of utmost importance in providing a wide range of ecological and societal services. Among these, their role in maintaining landscape connectivity through ecological corridors for animals and plants is of major interest from a conservation and management perspective. This paper describes a methodology to identify European regions as providers of structural riparian corridors, and to rank them with reference to conservation priority. Physical riparian connectors among core habitat patches are identified through a recent segmentation technique, the Morphological Spatial Pattern Analysis. A multi-scale approach is followed by considering different edge distances to identify core and peripheral habitats for a range of hypothetical species. The ranking is performed using a simple set of indices that take into account the degree of environmental pressure and the presence of land protection schemes. An example for environmental reporting is carried out using European administrative regions and major rivers to summarize indices value. The approach is based on freely available software and simple metrics which can be easily reproduced in a GIS environment.     

Network Density Estimation: A GIS Approach for Analysing Point Patterns in a Network Space

Human activities and more generally the phenomena related to human behaviour take place in a network‐constrained subset of the geographical space. These phenomena can be expressed as locations having their positions configured by a road network, as address points with street numbers. Although these events are considered as points on a network, point pattern analysis and the techniques implemented in a GIS environment generally consider events as taking place in a uniform space, with distance expressed as Euclidean and over a homogeneous and isotropic space. Network‐spatial analysis has developed as a research agenda where the attention is drawn towards point pattern analytical techniques applied to a space constrained by a road network. Little attention has been put on first order properties of a point pattern (i.e. density) in a network space, while mainly second order analysis such as nearest neighbour and K‐functions have been implemented for network configurations of the geographical space. In this article, a method for examining clusters of human‐related events on a network, called Network Density Estimation (NDE), is implemented using spatial statistical tools and GIS packages. The method is presented and compared to conventional first order spatial analytical techniques such as Kernel Density Estimation (KDE). Network Density Estimation is tested using the locations of a sample of central, urban activities associated with bank and insurance company branches in the central areas of two midsize European cities, Trieste (Italy) and Swindon (UK).     

基于GIS的采煤沉陷区地质环境数据库建设研究

文章梳理了采煤沉陷区地质环境调查基础数据类型和空间数据类型,依据我国矿山地质环境调查评价的行业标准和规范,建立了集成数据管理、服务、交换体系的综合数据库,实现了基于GIS的综合业务数据集成、管理与服务。结果表明:GIS技术可以实现采煤沉陷区环境地质调查数据库建设,为采煤沉陷区的土地治理和生态恢复提供决策支持。     

A Comparison of an Ecological Model and GIS Spatial Analysis to Describe Niche Partitioning Amongst Carrion Beetles in Nebraska

Carrion beetles depend on vertebrate carcasses to rear their young. Carcasses are a limited resource with patchy distribution, and there is an intense competition among many species for these carcasses. This situation is expected to lead to niche partitioning, such that different beetle species use different resources and thus escape direct competition. Our project used a geographic information system (GIS) and pitfall sampling to characterize carrion beetle preferences for soil texture and land use in Kearney County, Nebraska. The GIS was used to select sites where sampling was conducted using pitfall traps baited with rat carcasses. Attracted beetles were counted, identified to species, and released. The resulting data were used to construct occurrence maps of eleven species of carrion beetles by overlaying soil texture and land use. We then compared the results of EcoSim (an ecological simulation model of niche overlap) with GIS–generated maps of probability of carrion beetle occurrence. Our results are consistent with landscape–level niche partitioning by seven of the eleven examined species. Our application of GIS to the spatial analysis of carrion beetle distributions demonstrates how this technology can be used to test ecological and evolutionary hypotheses, predict habitat associations, and examine the effects of land use on a community of insects. This work could easily be extended to study the habitat preferences of the federally endangered American burying beetle, Nicrophorus americanus .     

Advanced image processing methods as a tool to map and quantify different types of biological soil crust

Biological soil crusts (BSCs) modify numerous soil surface properties and affect many key ecosystem processes. As BSCs are considered one of the most important components of semiarid ecosystems, accurate characterisation of their spatial distribution is increasingly in demand. This paper describes a novel methodology for identifying the areas dominated by different types of BSCs and quantifying their relative cover at subpixel scale in a semiarid ecosystem of SE Spain. The approach consists of two consecutive steps: (i) First, Support Vector Machine (SVM) classification to identify the main ground units, dominated by homogenous surface cover (bare soil, cyanobacteria BSC, lichen BSC, green and dry vegetation), which are of strong ecological relevance. (ii) Spectral mixture analysis (SMA) of the ground units to quantify the proportion of each type of surface cover within each pixel, to correctly characterize the complex spatial heterogeneity inherent to semiarid ecosystems. SVM classification showed very good results with a Kappa coefficient of 0.93%, discriminating among areas dominated by bare soil, cyanobacteria BSC, lichen BSC, green and dry vegetation. Subpixel relative abundance images achieved relatively high accuracy for both types of BSCs (about 80%), whereas general overestimation of vegetation was observed. Our results open the possibility of introducing the effect of presence and of relative cover of BSCs in spatially distributed hydrological and ecological models, and assessment and monitoring aimed at reducing degradation in these areas.