Next Article in Journal / Special Issue
A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA) Utilizing Raster Attribute Tables
Previous Article in Journal
Mangrove Species Identification: Comparing WorldView-2 with Aerial Photographs
Previous Article in Special Issue
Change Detection Algorithm for the Production of Land Cover Change Maps over the European Union Countries
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Remote Sensing
Volume 6
Issue 7
10.3390/rs6076089
remotesensing-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

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

by
Christopher S. Galletti
* and
Soe W. Myint
School of Geographical Sciences and Urban Planning, Arizona State University, P.O. Box 875302, Tempe, AZ 85287, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2014, 6(7), 6089-6110; https://doi.org/10.3390/rs6076089
Submission 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))
Browse Figures
Versions Notes

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.
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

Share and Cite

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. https://doi.org/10.3390/rs6076089

AMA Style

Galletti CS, Myint SW. Land-Use Mapping in a Mixed Urban-Agricultural Arid Landscape Using Object-Based Image Analysis: A Case Study from Maricopa, Arizona. Remote Sensing. 2014; 6(7):6089-6110. https://doi.org/10.3390/rs6076089

Chicago/Turabian Style

Galletti, Christopher S., and Soe W. Myint. 2014. "Land-Use Mapping in a Mixed Urban-Agricultural Arid Landscape Using Object-Based Image Analysis: A Case Study from Maricopa, Arizona" Remote Sensing 6, no. 7: 6089-6110. https://doi.org/10.3390/rs6076089

APA Style

Galletti, C. S., & Myint, S. W. (2014). Land-Use Mapping in a Mixed Urban-Agricultural Arid Landscape Using Object-Based Image Analysis: A Case Study from Maricopa, Arizona. Remote Sensing, 6(7), 6089-6110. https://doi.org/10.3390/rs6076089

Article Metrics

Back to TopTop