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Survival Analysis in Land Change Science

Integrating with GIScience to Address Temporal Complexities

Bibliographic Data

ID8375931
AuthorsLi An (0000-0002-7933-5174, San Diego State University), David G Brown (0000-0001-6023-5950, Michigan Department of Natural Resources), Daniel G Brown
Year2008
Volume98
Issue2
Pages323-344
Publication date2008-04-15
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAnnals of the Association of American Geographers (JOURNAL)
Journal identifiersISSN: 0004-5608 • E-ISSN: 1467-8306
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/00045600701879045
OpenAlexW2102577064
LanguageEN
Citations received12
References cited42

Although land changes are characterized by dimensionality in both space and time, and a multitude of methods and techniques have been developed to model them, the temporal dimension has seldom been adequately addressed by commonly used methods. In the context of temporal complexities represented in different space– time data models, this study aims to establish a framework for applying survival analysis theory and techniques to geographical land change modeling. Our efforts focus on (1) introducing basic concepts in survival analysis and their connections to space–time data commonly used in land change analysis, (2) using survival metrics to describe temporal patterns that are not easily detected by other methods, and (3) applying survival analysis methods to disclose effects of varying temporal patterns and uncertainties. Our findings suggest that survival analysis, coupled with geographic information systems (GIS) and remote sensing data, can effectively disclose relationships in land changes, and in many instances excel in shedding light on the temporal patterns of land changes. Key Words: geographic information systems, land change modeling, remote sensing, survival analysis, temporal complexity

Archaeology · Cartography · Context (archaeology) · Curse of dimensionality · Dimension (graph theory) · Focus (optics) · Geography · Physics · Artificial Intelligence · Computer Science · demographic modeling and climate adaptation · Land Use and Ecosystem Services · Mathematics · Spatial and Panel Data Analysis

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Unique citing works12
Citations per year0,71
Citation span2009 - 2023 (15)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 10
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