Quantifying the Time Series Pattern of a Binary Variable: Land Change Across 36 Years in Brazil
Topics: Land Use and Land Cover Change
, Remote Sensing
, Spatial Analysis & Modeling
Keywords: time series, land change, spatial-temporal analysis, classification, error assessment
Session Type: Virtual Guided Poster Abstract
Day: Sunday
Session Start / End Time: 2/27/2022 09:40 AM (Eastern Time (US & Canada)) - 2/27/2022 11:00 AM (Eastern Time (US & Canada))
Room: Virtual 1
Authors:
Claire Wang, Clark University
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Abstract
Time series analysis has become an important research topic in Geographic Information Science (GIS) and Remote Sensing. Researchers investigating land change value categorical and binary variables as they provide clearer representations of land cover interactions and more data now become available. Binary variables in time series represent the presence or absence of a class at each time point. There are many possible ways to analyze such a time series for land cover classes. Temporal composition and configuration of the presence versus absence of a class during a time series can reveal important characteristics of land change but the profession lacks sufficient methods to characterize such patterns, which my research addresses. Temporal composition means the number of times a category is present while temporal configuration concerns the sequential arrangement of the presence of the class during a time series. I developed concepts and created a computer program to characterize composition and configuration in ways that have implications for data quality assessment and land change science. The data come from MapBiomas’ collection 6.0, annual land cover data of 36 years. The methods (1) differentiate temporal change patterns across spatial scales, (2) give insights into data quality, and (3) improve understanding of land change drivers. My methods are more sophisticated than common error detections because my methods analyze time series in an integrated manner to highlight noteworthy land changes. The methods can be widely applied to other time series of categorical variables via modification of the criteria according to a project’s goals.
Quantifying the Time Series Pattern of a Binary Variable: Land Change Across 36 Years in Brazil
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Virtual Guided Poster Abstract
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