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Geographic Information Science & Technology Body of Knowledge最新文献

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Competence in GIS&T Knowledge Work 具备gis & &t知识工作能力
Pub Date : 2018-07-01 DOI: 10.22224/GISTBOK/2018.3.10
D. DiBiase
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引用次数: 3
Strategic Planning for GIS Design GIS设计的战略规划
Pub Date : 2018-07-01 DOI: 10.22224/GISTBOK/2018.3.8
Z. Nedović-Budić, E. Knapp, J. Ran
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引用次数: 0
Location-allocation Modeling 子建模
Pub Date : 2018-07-01 DOI: 10.22224/GISTBOK/2018.3.4
R. Church, Antonio Medrano
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引用次数: 8
GIS&T and Geodesign gis & Geodesign
Pub Date : 2018-07-01 DOI: 10.22224/GISTBOK/2018.3.3
Darren M. Ruddell, Kelleann Foster
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引用次数: 2
Spatial MapReduce 空间MapReduce
Pub Date : 2018-07-01 DOI: 10.22224/gistbok/2018.3.9
A. Eldawy
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引用次数: 0
The Classic Transportation Problem 经典的交通问题
Pub Date : 2017-10-01 DOI: 10.22224/GISTBOK/2017.4.7
Ying Song
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引用次数: 1
Citizen Science with GIS&T 公民科学与gis & &t
Pub Date : 2017-08-19 DOI: 10.22224/GISTBOK/2017.3.5
P. Rickles, M. Haklay, C. Ellul, A. Skarlatidou
Citizen Science is defined as the participation of non-professional volunteers in scientific projects (Dickson et al, 2010) and has experienced rapid growth over the past decade. The projects that are emerging in this area range from contributory projects, co-created projects, collegiate projects, which are initiated and run by a group of people with shared interest, without any involvement of professional scientists. In many citizen science projects, GIS&T is enabling the collection, analysis, and visualisation of spatial data to affect decision-making. Some examples may include: Recording the location of invasive species or participating in a BioBlitz to record local biodiversity (Figure 1). Measuring air quality or noise over a large area and over time to monitor local conditions and address them Using tools to educate on and increase access to local resources, improving community resilience Such projects have the opportunity to empower or disempower members of the public, depending upon access to and understanding of technology. Citizen Science projects using GIS&T may help communities influence decision makers and support the gathering of large-scale scientific evidence on a range of issues. This may also renew people’s interests in the sciences and foster continued and lifelong learning.
公民科学被定义为非专业志愿者参与科学项目(Dickson et al, 2010),在过去十年中经历了快速增长。在这一领域出现的项目包括贡献项目、共同创建的项目、大学项目,这些项目由一群有共同兴趣的人发起和运行,没有任何专业科学家的参与。在许多公民科学项目中,GIS&T使空间数据的收集、分析和可视化能够影响决策。一些例子可能包括:记录入侵物种的位置或参与生物闪电行动以记录当地的生物多样性(图1)。测量大面积和长期的空气质量或噪音,以监测当地情况并解决这些问题。使用工具进行教育并增加对当地资源的获取,提高社区的复原力。这些项目有机会赋予或剥夺公众成员的权力,这取决于对技术的获取和理解。使用GIS&T的公民科学项目可以帮助社区影响决策者,并支持收集关于一系列问题的大规模科学证据。这也可能重新激发人们对科学的兴趣,促进持续和终身学习。
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引用次数: 2
GIS and Parallel Programming GIS与并行编程
Pub Date : 1900-01-01 DOI: 10.22224/GISTBOK/2019.1.1
Eric Shook
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引用次数: 0
Web GIS Programming Web GIS编程
Pub Date : 1900-01-01 DOI: 10.22224/GISTBOK/2019.1.5
J. Swift, Daniel W. Goldberg
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引用次数: 2
Kriging Interpolation 克里格插值
Pub Date : 1900-01-01 DOI: 10.22224/gistbok/2019.4.4
P. Goovaerts
Kriging is a geostatistical interpolation technique that considers both the distance and the degree of variation between known data points when estimating values in unknown areas. A kriged estimate is a weighted linear combination of the known sample values around the point to be estimated. Applied properly, Kriging allows the user to derive weights that result in optimal and unbiased estimates. It attempts to minimize the error variance and set the mean of the prediction errors to zero so that there are no overor under-estimates. Included with the Kriging routine is the ability to construct a semivariogram of the data which is used to weight nearby sample points when interpolating. It also provides a means for users to understand and model the directional (e.g., north-south, east-west) trends of their data. A unique feature of Kriging is that it provides an estimation of the error at each interpolated point, providing a measure of confidence in the modeled surface.
Kriging是一种地质统计学插值技术,它在估计未知区域的值时考虑了已知数据点之间的距离和变化程度。克里格估计是待估计点周围已知样本值的加权线性组合。如果应用得当,Kriging允许用户得出最优和无偏估计的权重。它试图将误差方差最小化,并将预测误差的均值设置为零,这样就不会出现高估或低估的情况。Kriging例程包括构建数据的半变异函数的能力,该函数在插值时用于对附近的样本点进行加权。它还为用户提供了了解其数据的方向(例如,南北、东西)趋势和建立模型的方法。Kriging的一个独特之处在于它提供了对每个插值点误差的估计,从而提供了对建模表面的置信度度量。
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引用次数: 17
期刊
Geographic Information Science & Technology Body of Knowledge
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