Mapping worlds? Excavating cartographic encounters in Plantation Ireland through GIS

This paper uses the analytical potential of Geographical Information Systems (GIS) to explore processes of map production and circulation in early-seventeenth century Ireland. The paper focuses on a group of historic maps, attributed to Josias Bodley, which were commissioned in 1609 by the English Crown to assist in the Plantation of Ulster. Through GIS and digitizing map-features, and in particular by quantifying map-distortion, it is possible to examine how these maps were made, and by whom. Statistical analyses of spatial data derived from the GIS are shown to provide a methodological basis for ‘excavating’ historical geographies of Plantation map-making. These techniques, when combined with contemporary written sources, reveal further insight on the ‘cartographic encounters’ taking place between surveyors and map-makers working in Ireland in the early 1600s, opening up the ‘mapping worlds’ which linked Ireland and Britain through the networks and embodied practices of Bodley and his map-makers.

Role assessment of GIS analysis and its reliability while ranking urban sustainability using scenarios specific to regional climate, community and culture

Urban Sustainability expresses the level of conservation of a city while living a town or consuming its urban resources, but the measurement of urban sustainability depends on what are considered important indicators of conservation besides the permitted levels of consumption in accordance with adopted criteria. This criterion should have common factors that are shared for all the members tested or cities to be evaluated as in this particular case for Abu Dhabi, but also have specific factors that are related to the geographic place, community and culture, that is the measures of urban sustainability specific to a middle east climate, community and culture where GIS Vector and Raster analysis have a role or add a value in urban sustainability measurements or grading are considered herein. Scenarios were tested using various GIS data types to replicate urban history (ten years period), current status and expected future of Abu Dhabi City setting factors to climate, community needs and culture. The useful Vector or Raster GIS data sets that are related to every scenario where selected and analysed in the sense of how and how much it can benefit the urban sustainability ranking in quantity and quality tests, this besides assessing the suitable data nature, type and format, the important topology rules to be considered, the useful attributes to be added, the relationships which should be maintained between data types of a geo- database, and specify its usage in a specific scenario test, then setting weights to each and every data type representing some elements of a phenomenon related to urban suitability factor. The results of assessing the role of GIS analysis provided data collection specifications such as the measures of accuracy reliable to a certain type of GIS functional analysis used in an urban sustainability ranking scenario tests. This paper reflects the prior results of the research that is conducted to test the multidiscipline evaluation of urban sustainability using different indicator metrics, that implement vector GIS Analysis and Raster GIS analysis as basic tools to assist the evaluation and increase of its reliability besides assessing and decomposing it, after which a hypothetical implementation of the chosen evaluation model represented by various scenarios was implemented on the planned urban sustainability factors for a certain period of time to appraise the expected future grade of urban sustainability and come out with advises associated with scenarios for assuring gap filling and relative high urban future sustainability. The results this paper is reflecting are concentrating on the elements of vector and raster GIS analysis that assists the proper urban sustainability grading within the chosen model, the reliability of spatial data collected; analysis selected and resulted spatial information. Starting from selecting some important indicators to comprise the model which include regional culture, climate and community needs an example of what was used is Energy Demand & Consumption (Cooling systems). Thus, this factor is related to the climate and it‟s regional specific as the temperature varies around 30-45 degrees centigrade in city areas, GIS 3D Polygons of building data used to analyse the volume of buildings, attributes „building heights‟, estimate the number of floors from the equation, following energy demand was calculated and consumption for the unit volume, and compared it in scenario with possible sustainable energy supply or using different environmental friendly cooling systems this is followed by calculating the cooling system effects on an area unit selected to be 1 sq. km, combined with the level of greenery area, and open space, as represented by parks polygons, trees polygons, empty areas, pedestrian polygons and road surface area polygons. (initial measures showed that cooling system consumption can be reduced by around 15 -20 % with a well-planned building distributions, proper spaces and with using environmental friendly products and building material, temperature levels were also combined in the scenario extracted from satellite images as interpreted from thermal bands 3 times during the period of assessment. Other examples of the assessment of GIS analysis to urban sustainability took place included Waste Productivity, some effects of greenhouse gases measured by the intensity of road polygons and closeness to dwelling areas, industry areas as defined from land use land cover thematic maps produced from classified satellite images then vectors were created to take part in defining their role within the scenarios. City Noise and light intensity assessment was also investigated, as the region experiences rapid development and noise is magnified due to construction activities, closeness of the airports, and highways. The assessment investigated the measures taken by urban planners to reduce degradation or properly manage it. Finally as a conclusion tables were presented to reflect the scenario results in combination with GIS data types, analysis types, and the level of GIS data reliability to measure the sustainability level of a city related to cultural and regional demands.

Aplicação de Sistema de Informações Geográficas na análise espacial de doenças do milho no Brasil.

This study presents an application of the geographical information system technology on plant disease involving a multidisciplinary teamwork of geoprocessing and physiopathology specialists. The spatial analysis tools in a GIS were used to evaluate the spatial distribution of two diseases of maize in Brazil: polysora rusl caused by Puccinia polysora and tropical rust caused by Physopella zeae. A database of cIimate variables (mean temperature. relative humidity. and leaf wetness duration) of cIimatological normal from 1961-1990 was obtained and then related it to a mathematical model of disease development (polysora rust) and to the cIimate intervals (tropical rust) in order to obtain the maps. The choice of the model or the favorable climate interval is the important chalIenge of the method because the difficulty of adequacy to the spatial and temporal scales for the specific application. The major incidence of both disease occurred in almost alI the North region from January to June. although this region has traditionalIy a low production of maize. Considering the biggest producers regions. for both the diseases, favorable areas are located in part of Mato Grosso, Tocanlins. Minas Gerais; Mato Grosso do Sul. and coastal areas of São Paulo, Paraná, and Santa Catarina. varying among the dilferent months from January to June. The method allowed making an adequate distinction of the states and the months considered.

北京地区植被景观的空间分布特征

本文利用地理信息系统(GIS)技术、景观生态学理论和方法、分形理论以及统计分析方法对北京地区植被景观的空间分布特征进行了分析，并对景观格局和景观多样性的分析方法进行了探讨，结果表明： (1)对几乎所有的斑块类型，其斑块大小的分布都不是对称的，而是右偏的。4种概率分布（Г—分布、对数正态分布、Weibull分布和（负）指数分布）都只能刻划部分斑块类型，并且服从对数正态分布的斑块类型最多，服从（负）指数分布的斑块类型最少。 (2)随着斑块面积的增加，边界效应越来越小，而斑块形状越来越不紧凑。 (3)分形分析识别出本地区植被景观中的两个尺度域：一个是斑块面积小于(大约)2.7km2，另一个是斑块面积大于(大约)2.7km2。两个域中的斑块复杂程度有很大差异，后一个域中的斑块明显比前一个域中的斑块复杂，并且随着斑块面积的增加，斑块形状越来越复杂。 (4)用斑块数作为多度指标时，该景观的斑块类型一多度分布服从（截断）对数正态分布和（截断）负二项分布，不服从对数级数分布和几何分布。用斑块面积作为多度指标时，该景观的斑块类型一多度分布服从对数正态分布、Weibull分布和Г—争布，不服从正态分布。从而该景观的斑块类型一多度分布不是对称的，也是右偏的。在4个优势度／多样性模型中，“生态位优先占领”模型和Zipf-Mandelbrot模型可以较好地刻划该景观的斑块类型一多度关系。 (5)样本大小对多样性测度有直接的影响。如果这种影响比较小，就说明测度指标比较稳定。三个丰富度指数中，Ri比R2和R3更稳定;五个多样性性指数中，D和Di最稳定，OD最不稳定，因此，OD是用于景观多样性监测的理想指标;五个均匀度指数中，Jgi最稳定。根据设计的3种计算临界样方数量（即多样性测度指标达到稳定时的样方数量）方法的计算结果，上述几个最稳定的测度指标在通常情况下只需要几个样方(即总抽样面积为数百km2)就达到稳定状态。 (6)斑块类型数目随面积的增加而增加。根据四个评价指标的评价结果，认为双曲线对该景观的斑块类型一面积关系的拟合效果最好。 (7)样本较大（对于一阶刀切估计，大于30个样方;对于二阶刀切估计，大于60个样方）时，刀切法能够给出斑块类型数目(NPT)较好的估计;样本较小（小于30个样方）时，Mingoti和Meeden提出的经验贝叶斯方法能够对NPT给出比刀切法和自助法更好的估计。斑块类型一面积曲线外推虽然也能给出NPT较好的估计，但这种方法需要慎重使用，不能外推得很远。 (8)列联表分析表明，该植被景观中的斑块类型与土壤类型、岩石类型、海拔高度和坡向各因子之间均存在显著的相关性。植被景观多样性与岩石类型多样性和地形多样性之间也均呈显著的正相关关系，即植被景观多样性随岩石类型多样性和地形多样性的增加而增加。但植被景观多样性与土壤类型多样性之间不存在显著的线性相关或秩相关关系，这可能是由于二者的分类体系不吻合。植被景观多样性与总的道路密度和第二类道路密度之间均呈显著的负相关关系，而与第一类和第三类道路密度之间的关系都不显著。这反映出景观样本单元(10kmxlOkm)的尺度对应于第二类道路的影响尺度。而道路密度在一定程度上反映了人类活动的强度，因此，在10kmxlOkm这个尺度上，人类活动愈剧烈，景观多样性就愈小。

Seafloor mapping data, Victoria

The collection includes three major data types

- Seafloor structure information: Collation of seafloor structure information (bathymetry and softness hardness) collected using multibeam sonar systems as part of the Victorian Marine Habitat Mapping Project and bathymetric light detection and ranging data (LiDAR) collected as part of the future coats program. The geographic is Victorian State waters (~1400km2 multibeam sonar & ~4000 km2 for LiDAR as of 2012

- Video information: ~800 linear kilometres of precisely georeferenced towed video data from depths of 10-100m in Victorian coastal waters. 300 baited stereo video drops in Hopkins and Discovery Bay site locations. All video has been classified to the lowest taxonomic resolution possible with the video systems employed and converted to spatial data layers in the GIS environment.

- Habitat maps: Predicted habitat models integrating seafloor structure and video information developed using classification algorithms and remote sensing technologies.

Detecting spatiotemporal clusters of accidental poisoning mortality among Texas counties, U.S., 1980 – 2001

Background Accidental poisoning is one of the leading causes of injury in the United States, second only to motor vehicle accidents. According to the Centers for Disease Control and Prevention, the rates of accidental poisoning mortality have been increasing in the past fourteen years nationally. In Texas, mortality rates from accidental poisoning have mirrored national trends, increasing linearly from 1981 to 2001. The purpose of this study was to determine if there are spatiotemporal clusters of accidental poisoning mortality among Texas counties, and if so, whether there are variations in clustering and risk according to gender and race/ethnicity. The Spatial Scan Statistic in combination with GIS software was used to identify potential clusters between 1980 and 2001 among Texas counties, and Poisson regression was used to evaluate risk differences. Results Several significant (p < 0.05) accidental poisoning mortality clusters were identified in different regions of Texas. The geographic and temporal persistence of clusters was found to vary by racial group, gender, and race/gender combinations, and most of the clusters persisted into the present decade. Poisson regression revealed significant differences in risk according to race and gender. The Black population was found to be at greatest risk of accidental poisoning mortality relative to other race/ethnic groups (Relative Risk (RR) = 1.25, 95% Confidence Interval (CI) = 1.24 – 1.27), and the male population was found to be at elevated risk (RR = 2.47, 95% CI = 2.45 – 2.50) when the female population was used as a reference. Conclusion The findings of the present study provide evidence for the existence of accidental poisoning mortality clusters in Texas, demonstrate the persistence of these clusters into the present decade, and show the spatiotemporal variations in risk and clustering of accidental poisoning deaths by gender and race/ethnicity. By quantifying disparities in accidental poisoning mortality by place, time and person, this study demonstrates the utility of the spatial scan statistic combined with GIS and regression methods in identifying priority areas for public health planning and resource allocation.

Public Commons for Geospatial Data: A Conceptual Model

A wide variety of spatial data collection efforts are ongoing throughout local, state and federal agencies, private firms and non-profit organizations. Each effort is established for a different purpose but organizations and individuals often collect and maintain the same or similar information. The United States federal government has undertaken many initiatives such as the National Spatial Data Infrastructure, the National Map and Geospatial One-Stop to reduce duplicative spatial data collection and promote the coordinated use, sharing, and dissemination of spatial data nationwide. A key premise in most of these initiatives is that no national government will be able to gather and maintain more than a small percentage of the geographic data that users want and desire. Thus, national initiatives depend typically on the cooperation of those already gathering spatial data and those using GIs to meet specific needs to help construct and maintain these spatial data infrastructures and geo-libraries for their nations (Onsrud 2001). Some of the impediments to widespread spatial data sharing are well known from directly asking GIs data producers why they are not currently involved in creating datasets that are of common or compatible formats, documenting their datasets in a standardized metadata format or making their datasets more readily available to others through Data Clearinghouses or geo-libraries. The research described in this thesis addresses the impediments to wide-scale spatial data sharing faced by GIs data producers and explores a new conceptual data-sharing approach, the Public Commons for Geospatial Data, that supports user-friendly metadata creation, open access licenses, archival services and documentation of parent lineage of the contributors and value- adders of digital spatial data sets.

Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.