Mapping Wetlands and Land Cover Change with Landsat Archives: The Added Value of Geomorphologic Data

While classification of remote sensing images has proven useful to quantify wetland losses, wetland mappers have always faced challenges, such as dealing with variable responses of wetlands to meteorological conditions and the obstruction of ground by the canopy in forested wetlands. In this paper, we investigate the added value of using geomorphological data, namely hillslope geometry (through Dikau shapes) and soil drainage classes, as ancillary datasets to map the evolution of wetland cover over the last 35 years. We developed an object-based image analysis method, through a case study in Quebec. Two sets of land cover scenarios (spring and fall) were generated from Landsat archives for 1978, 1985, 1992, 2001, and 2014. Results show that the global accuracy was improved by 19% to 35% when using the geomorphological data, especially soil drainage classes, confirming that their use as ancillary data significantly contributed to the classification process. However, differences were noted between spring and fall scenarios. The wetland cover of the study watershed decreased by 8%–53% between 1978 and 2014 at the expense of an increase in urban areas. Meanwhile, the agricultural land cover decreased (72%–83%) throughout the study period, while forests, water, and bare soil remained stable.