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Impact of the Scale on Several Metrics Used in Geographical Object-Based Image Analysis: Does GEOBIA Mitigate the Modifiable Areal Unit Problem (MAUP)?

UMR ESPACE 7300, CNRS, Department of Geography, 74 rue Louis Pasteur, 84029 Avignon CEDEX, France
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ISPRS Int. J. Geo-Inf. 2019, 8(3), 156; https://doi.org/10.3390/ijgi8030156
Received: 30 September 2018 / Revised: 1 January 2019 / Accepted: 24 February 2019 / Published: 22 March 2019
(This article belongs to the Special Issue GEOBIA in a Changing World)
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Abstract

Using two GEOBIA (Geographical Object Based Image Analysis) algorithms on a set of segmented images compared to grid partitioning at different scales, we show that statistical metrics related to both objects and sets of pixels are (more or less) subject to the Modifiable Areal Unit Problem. Subsequently, even in a same spatial partition, there may be a bias in statistics describing the objects due to some size effect of the pixel samples. For instance, pixels homogeneity based on Grey Level Cooccurrence Matrices (GLCM), Landscape Shape Index, entropy, object compacity, perimeter/area ratio are studied according to scale. The approach consists in studying the behavior of a given statistical metrics through scales and to compare the results on several image segmentations, according to different partitioning processes, from GEOBIA (Baatz & Schäpe algorithm and Self Organizing Maps) or using reference grids. We finally discuss about the relationship between GEOBIA metrics and scale. By analysing object shape and pixels composition from different metrics points of views, we show that GEOBIA does not always mitigate the Modifiable Areal Unit Problem. View Full-Text
Keywords: GEOBIA; Modifiable Areal Unit Problem; MAUP; scale effect; aggregation fallacy; object; homogeneity; shape GEOBIA; Modifiable Areal Unit Problem; MAUP; scale effect; aggregation fallacy; object; homogeneity; shape
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Josselin, D.; Louvet, R. Impact of the Scale on Several Metrics Used in Geographical Object-Based Image Analysis: Does GEOBIA Mitigate the Modifiable Areal Unit Problem (MAUP)? ISPRS Int. J. Geo-Inf. 2019, 8, 156.

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