Geocarto International · 2021 · 25 citations · 56 references
Natural ResourcesGeographyGeoinformaticsLandscape MetricsRemote SensingSpatial AnalysisLand Cover Change DetectionLand Cover MappingLand UseLand Use Change DetectionLand-use ChangeRemote Sensing Change DetectionAgricultural AbandonmentClassification Accuracy AssessmentLand Cover AnalysisLand Cover Change MonitoringLand Use Change MappingLand-cover ChangeObject-based Image AnalysisSpatial Change Quantification
Determination of the spatio-temporal distribution of Land use and Land cover (LU/LC) is important to understand the dynamics of urbanization, agricultural abandonment, and industrialization. This study aims to create multi-temporal high-resolution LU/LC maps and analyze thematically extensive LU/LC changes using Geographic Object-Based Image Analysis (GEOBIA) and Landscape Metrics for the selected study region in the Istanbul metropolitan city of Turkey. HR SPOT 6/7 images acquired in 2009, 2013, and 2019 were used as main Earth Observation data to create LU/LC maps. Open-source geospatial data were also integrated into classification to better identify some LU/LC classes to increase total classification accuracy. Overall classification accuracy of 2009, 2013, and 2019 dated LU/LC maps are 87.45%, 88.16%, 90.74% respectively. Principal Component Analysis (PCA) and Pearson correlation were used to selecting the landscape metrics and evaluate the results. PCA resulted in three principal components and the total variance was found as 87.3%.
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A factor analysis of landscape pattern and structure metrics
Kurt H. Riitters, R. V. O’Neill, Carolyn T. Hunsaker et al. · Landscape Ecology · 1995 · 1.3K citations