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Remote Sens. 2014, 6(7), 6089-6110; doi:10.3390/rs6076089

Land-Use Mapping in a Mixed Urban-Agricultural Arid Landscape Using Object-Based Image Analysis: A Case Study from Maricopa, Arizona

School of Geographical Sciences and Urban Planning, Arizona State University, P.O. Box 875302, Tempe, AZ 85287, USA
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Received: 4 March 2014 / Revised: 28 May 2014 / Accepted: 19 June 2014 / Published: 30 June 2014
(This article belongs to the Special Issue Advances in Geographic Object-Based Image Analysis (GEOBIA))
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Abstract

Land-use mapping is critical for global change research. In Central Arizona, U.S.A., the spatial distribution of land use is important for sustainable land management decisions. The objective of this study was to create a land-use map that serves as a model for the city of Maricopa, an expanding urban region in the Sun Corridor of Arizona. We use object-based image analysis to map six land-use types from ASTER imagery, and then compare this with two per-pixel classifications. Our results show that a single segmentation, combined with intermediary classifications and merging, morphing, and growing image-objects, can lead to an accurate land-use map that is capable of utilizing both spatial and spectral information. We also employ a moving-window diversity assessment to help with analysis and improve post-classification modifications. View Full-Text
Keywords: Object-Based Image Analysis (OBIA); land use; segmentation; urban; agriculture; dryland; arid; ASTER Object-Based Image Analysis (OBIA); land use; segmentation; urban; agriculture; dryland; arid; ASTER
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Galletti, C.S.; Myint, S.W. Land-Use Mapping in a Mixed Urban-Agricultural Arid Landscape Using Object-Based Image Analysis: A Case Study from Maricopa, Arizona. Remote Sens. 2014, 6, 6089-6110.

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