Scale in GIS: An overview

Goodchild, Michael F.

doi:10.1016/j.geomorph.2010.10.004

Cited by 165 publications

(110 citation statements)

References 33 publications

(28 reference statements)

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“…The issues associated with thematic, spatial, and temporal scales have been widely discussed in the ecological (e.g., Levin, 1992;Schneider, 2001;Hobbs, 2003) and geospatial literatures (e.g., Stone, 1972;Atkinson and Tate, 2000;Goodchild, 2011), including a recent review by on scale in marine habitat mapping. Here, I focus on how scale impacts mapping outcomes, and the implications of scale for decision-making.…”

Section: Scalementioning

confidence: 99%

“…Data quality Van Oort and Bregt, 2005Devillers and Goodchild, 2010Li et al, 2012Robertson et al, 2010Lechner et al, 2012Rocchini et al, 2011Gallo and Goodchild, 2012Moudrý and Šímová, 2012Cros et al, 2014Lecours et al, 2017a Scale Woodcock, 1987Quattrochi and Goodchild, 1997Marceau and Hay, 1999Duncan et al, 2002Goodchild, 2011Zhang et al, 2014Wiens, 1989Borcard et al, 2004Rahbek, 2005Seo et al, 2009Austin and Van Niel, 2011Moudrý and Šímová, 2012Bradter et al, 2013Wilson et al, 2007Anderson et al, 2008Brown et al, 2011Harris and Baker, 2012bRengstorf et al, 2012 …”

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confidence: 99%

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On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

Lecours

2017

Front. Mar. Sci.

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Conservation planning and management typically require accurate and spatially explicit data at scales that are relevant for conservation objectives. In marine conservation, these data are often combined with spatial analytical techniques to produce marine habitat maps. While marine habitat mapping is increasingly used to inform conservation efforts, this field is still relatively young and its methods are rapidly evolving. Because conservation efforts do not always specify standards or guidelines for the production of habitat maps, results can vary dramatically. As representations of real environmental characteristics, habitat maps are highly sensitive to how they are produced. In this review paper, I present four concepts that are known to cause variation in spatial representation and prediction of habitats: the methodology used, the quality and scale of the data, and the choice of variables in regards to fitness for use. I then discuss the potential antinomy associated with the use of habitat maps in conservation: while habitat maps have become an invaluable tool to inform and assist decision-making, maps of the same area built using different methods and data may provide dissimilar representations, thus providing different information and possibly leading to different decisions. Exploring the theories and methods that have proved effective in terrestrial conservation and the spatial sciences, and how they can be integrated in marine habitat mapping practices, could help improve maps used to support marine conservation efforts and result in more reliable products to inform conservation decisions. Having a strong, consistent, transparent, repeatable, and science-based protocol for data collection and mapping is essential for effectively supporting decision-makers in developing conservation and management plans. The development of user-friendly tools to assist in the application of such protocol is crucial to a widespread improvement in practices. I discuss the potential to use interactive and collaborative Geographic Information Systems (GIS) to encourage the conservation and management community, from data collectors and mapmakers to decision-makers, to move toward a digital resilience and to develop such science-based protocol. Until standards and protocols are developed, habitat maps should always be interpreted with care, and the methods and metadata associated with their production should always be explicitly stated.

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Section: Scalementioning

confidence: 99%

mentioning

confidence: 99%

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

Lecours

2017

Front. Mar. Sci.

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“…The very act of identifying a particular pattern means that scale, extent, and resolution are involved (Goodchild, 2011). The choice of scale affects the type of pattern observed critically since patterns that appear at one level of resolution may be lost at lower or higher levels (Gibson et al, 2000).…”

Section: Feature Collection Worldmentioning

confidence: 99%

“…This means that different features, each one with its own geospatial rendering and with specific binary topological relationships (such as contained or part of or other spatial relationships), can be represented. We adopted multiple representations of a holding area based on the notion that (i) spatial abstraction is achieved by reducing the number of objects by means of their aggregation or elimination (Mustiere and Smaalen, 2007); and (ii) spatial analysis can be used to support the downscaling 1 of spatial data (Goodchild, 2011).…”

Section: Feature Collection Worldmentioning

confidence: 99%

A conceptual holding model for veterinary applications

Ferrè

Kuhn

Rumor³

et al. 2014

Geospat Health

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Abstract. Spatial references are required when geographical information systems (GIS) are used for the collection, storage and management of data. In the veterinary domain, the spatial component of a holding (of animals) is usually defined by coordinates, and no other relevant information needs to be interpreted or used for manipulation of the data in the GIS environment provided. Users trying to integrate or reuse spatial data organised in such a way, frequently face the problem of data incompatibility and inconsistency. The root of the problem lies in differences with respect to syntax as well as variations in the semantic, spatial and temporal representations of the geographic features. To overcome these problems and to facilitate the inter-operability of different GIS, spatial data must be defined according to a "schema" that includes the definition, acquisition, analysis, access, presentation and transfer of such data between different users and systems. We propose an application "schema" of holdings for GIS applications in the veterinary domain according to the European directive framework (directive 2007/2/EC -INSPIRE). The conceptual model put forward has been developed at two specific levels to produce the essential and the abstract model, respectively. The former establishes the conceptual linkage of the system design to the real world, while the latter describes how the system or software works. The result is an application "schema" that formalises and unifies the information-theoretic foundations of how to spatially represent a holding in order to ensure straightforward information-sharing within the veterinary community.

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“…Generally, numerical models are aimed at: i) predicting the kinematics of the slope movements (Huang et al, 2009;Ning et al, 2011;Longoni et al, 2014); and ii) forecasting the triggering factors that may lead to failure (Della Seta et al, 2013;Camera et al, 2014). If available data are not sufficient to achieve these goals, numerical modeling is unprofitable (Goodchild, 2011).…”

Section: Introductionmentioning

confidence: 99%

The role of the spatial scale and data accuracy on deep-seated gravitational slope deformation modeling: The Ronco landslide, Italy

et al. 2016

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In recent decades numerical models have been developed and extensively used for landslide hazard and risk assessment. The reliability of the outcomes of these numerical simulations must be evaluated carefully as it mainly depends on the soundness of the physical model of the landslide that in turn often requires the integration of several surface and subsurface surveys in order to achieve a satisfactory spatial resolution. Merging diverse sources of data may be particularly complex for large landslides, because of intrinsic heterogeneity and possible great data uncertainty. In this paper, we assess the spatial scale and data accuracy required for effective numerical landslide modeling. We focus on two particular aspects: the model extent and the accuracy of input datasets. The Ronco landslide, a deep-seated gravitational slope deformation (DSGSD) located in the North of Italy, was used as a test-bed. Geological, geomorphological and geophysical data were combined and, as a result, eight models with different spatial scales and data accuracies were obtained. The models were used to run a back analysis of an event in 2002, during which part of the slope moved after intense rainfalls. The results point to the key role of a proper geomorphological zonation to properly set the model extent. The accuracy level of the input datasets should also be tuned. We suggest applying the approach presented here to other DSGSDs with different geological and geomorphological settings to test the reliability of our findings.

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Scale in GIS: An overview

Cited by 165 publications

References 33 publications

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

A conceptual holding model for veterinary applications

The role of the spatial scale and data accuracy on deep-seated gravitational slope deformation modeling: The Ronco landslide, Italy

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