Using transition matrices to assess the spatio‐temporal land cover and ecotone changes in fluvial landscapes from historical planimetric data

Abstract

AbstractChange detection approaches based on historical maps are frequently used in fluvial geomorphology to reconstruct long‐term river trajectories and evaluate the level of functional degradation. On this basis, achievable rehabilitation goals may also be addressed. However, most of these studies explore the changes of land cover over time only through changes in the landscape composition, which is nevertheless not sufficient to assess accurately the river responses to natural and/or man‐made disturbances. In this study, we present that transition matrices and new metrics derived from this approach can be used to evaluate the land cover and ecotone area changes at multispatial scales on a 6 km long reach of the Upper Rhine. This study was based on the historical maps of 1828, 1838 and 1872 and using Open Street Map (OSM) for 2021. Our approach was targeting to assess (i) the composition and configuration of a fluvial landscape over time from pixel to landscape scale, (ii) the accurate location of land cover changes, their nature and their intensities, and (iii) the location, nature and diversity of the ecotone areas and their spatial complexities over time. The results showed that (i) the absence of changes in landscape composition over time cannot be interpreted as stability in the fluvial landscape in all cases, (ii) transition matrices are robust tools to face interpretation biases caused by conventional approaches based on landscape composition, because they allow us to trace the changes of each element of the transformed landscape elements. From this study, we indicate that the Rhine regulation induced a habitat and ecotone homogenization following the river correction works, which was exacerbated by the Rhine by‐passing, mainly due to the degradation of lateral connectivity between the main channel and the floodplain and global loss of the hydrosystem functionality.