Science and reporting information needs for monitoring dynamics in land cover over time have prompted research, and made operational, a wide variety of change detection methods utilizing multiple dates of remotely sensed data. Change detection procedures based upon spectral values are common; however, landscape pattern analysis approaches which utilize spatial information inherent within imagery present opportunities for the generation of unique and ecologically important information. While the use of two images may provide the means to identify change, the use of more than two images for long-term monitoring affords the ability to identify a greater range of processes of landscape change, including rates and dynamics. The main objective of this review is to investigate and summarize the methods and applications of land cover spatial pattern analysis using three or more image dates. The potential and the limitations of landscape pattern indices are identified and discussed to inform application recommendations. The second objective of this review is to make recommendations, including appropriate landscape pattern indices, for the application of landscape pattern analysis of a long time series of remotely sensed data to a case study involving the mountain pine beetle in British Columbia, Canada. The review concludes with recommendations for future research.
Characterizing spatial structure of urban tree cover (UTC) and impervious surface cover (ISC) density using remotely sensed data in Osmaniye, Turkey
