Conclusion

The study tested the behaviour and credibility of various landscape metrics for discriminating various landscape patterns and properties across various spatial resolutions. It reveals that the spatial resolution of the remote sensing data plays an important role in the landscape analysis. Exploration of landscape structure to understand the different landscape patterns for the analysis of composition reveal the dependency on spatial resolution of the data. The results reveal that landscape metrics based on patch (NP, PLADJ, AGGREGATION, IJI, CLUMPINESS) are sensitive to spatial resolution whereas metrics that are based on shape and neighbourhood (Cohesion, Connect, NLSI) are not sensitive and behave similarly across all resolutions. Comparison of the landscape metrics of various resolutions provides explicit knowledge of their sensitivity. Variations in landscape metrics with different spatial resolutions decide the effectiveness of the approach through spatial metrics used to analyze the landscape dynamics. Landscape metrics are apt indicators of land use development and environmental status and there is a need to incorporate these indices in spatial environment monitoring and information systems to achieve sustainable management of the natural resources.