Investigation of The Relationships Between Image Spatial Resolution And Landscape Metrics

Abstract

<title>Abstract</title> <p>Land Use and Land Cover (LULC) maps derived from satellite images are a significant source of geo-information to better understand the current status of landscapes, to analyze the landscape changes, and to develop sustainable decisions for landscape and urban planning. Since the spectral and spatial resolution of satellite images directly impact the LULC classes to be identified and the accuracy of the classification, these will also affect the values of calculated landscape metrics. This research aims to propose the most appropriate functions and features to obtain highly accurate thematically extensive LULC classification results from multi-resolution satellite images and to investigate how the change in spatial resolution of satellite images would affect the landscape metrics values and landscape pattern analysis Sentinel-2, SPOT-7, Pleaides, and Worldview-4 images with respective 10 m, 1.5 m, 0.5 m, and 0.3 m spatial resolution were classified using Geographic Object-Based Image Analysis techniques to create multi-scale LULC maps with the overall classification accuracy values of 66.05%, 85.00%, 91.79%, and 95.71%, respectively. Patch Density, Total Area, Largest Patch Index, Shape Index, Euclidian Nearest Neighbor distance, Aggregation Index, and Shannon's Diversity Index metrics were found to be most appropriate metrics to analyze the impact of spatial resolution on landscape metrics calculations considering the ability of these metrics to capture the spatial details, spatial arrangement, spatial distribution and complexity of shapes of landscape and classes.Landscape metrics results obtained from different LULC maps were compared to analyze the effects of image spatial resolution on different landscape metrics.</p>