Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification

Abstract

Abstract:The La Grande River watershed, located in the James Bay region (54°N, Quebec, Canada), is a major contributor to the production of hydroelectricity in the province. Peatlands cover up to 20% of the terrestrial environment in this region. Their hydrological behavior is not well understood. The present study is part of a multidisciplinary project which is aimed at analyzing the hydrological processes in these minerotrophic peatlands (fens) in order to provide effective monitoring tools to water managers. The objective of this study was to use VHR remote sensing data to understand the seasonal dynamics of the hydrology in fens. A series of 10 multispectral pan-sharpened GeoEye-1 images (with a spatial resolution of 40 cm) were acquired during the snow-free season (May to October) in 2009 and 2010, centered on two study sites in the Laforge sector (54°06'N; 72°30'W). These are two fens instrumented for continuous hydrometeorological monitoring (water level, discharge, precipitation, air temperature). An object-based classification procedure was set up and applied. It consisted of segmenting the imagery into objects using the multiresolution segmentation algorithm (MRIS) to delineate internal structures in the peatlands (aquatic, semi-aquatic, and terrestrial). Then, the objects were labeled using a fuzzy logic based algorithm. The overall classification accuracy of the 10 images was assessed to be 82%. The time series of the peatland mapping demonstrated the existence of important intra-seasonal spatial dynamics in the aquatic and semi-aquatic compartments. It was revealed that the dynamics amplitude depended on the morphological features of the OPEN ACCESS Remote Sens. 2012, 4 1888 fens. The observed spatial dynamics was also closely related to the evolution of the measured water levels.

Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping

“…In this study, a multi-scale segmentation algorithm embedded in Defines Developer was adopted. It is a bottom-up clustering technique and has been proved to be particularly suitable to high spatial resolution image segmentation [13,33].…”

Monitoring Volumetric Surface Soil Moisture Content at the La Grande Basin Boreal Wetland by Radar Multi Polarization Data

“…Other multi-temporal C-band SAR applications in northern wetland [45,46] showed that it can distinguish inundation from areas highly saturated with water, although at a different scale platform (European Space Agency Environmental Satellite or ENVISAT ASAR) Wide Swath, spatial resolution of 150 m). With regard to optical images applications at the same study area [34,47], they provided a satisfactory level of accuracy both for the delineation of peatlands and for the distinction of their internal structures. Whereas Dribault et al [34] were able to relate the observed spatial dynamics to the evolution of the measured water levels (discharge), our approach with a multi-date and multi-polarimetric C-band SAR index allowed for quality estimations of surface soil moisture on the peatlands' internal structures.…”

“…Surface soils in permanently flooded areas almost reach saturation (0.8 m 3 ·m -3 or higher) in spring as the snow melts and sustain a high surface soil moisture content all along the season (as seen previously in Figure 4). As cited before, wetland eco-hydrological hierarchical classification [34] consists of three groups: Water, Peat and Forest; each group also has many classes and subclasses. Nonetheless, we take only the classes necessary to explain the differences in vegetation cover on permanently flooded and seasonally flooded areas (one Water class and all Peat classes, but no Forest classes, shown in Table 7).…”

“…This behavior can be explained by the nature of boreal wetland eco-hydrological landscapes. Dribault et al [34] proposed an eco-hydrological hierarchical classification of boreal wetlands in three groups, water, peat and forest, representing three types of landscape: aquatic, semi-aquatic and terrestrial. Permanently flooded areas can be assigned to the aquatic group, while seasonally flooded areas to the semi-aquatic group, which represents a transitory environment onto terrestrial groups.…”

“…A previous optical high resolution image (GeoEye) classification was used [34] to help delineate landscape units. Peatland seasonally flooded (SF) areas were separated from permanently flooded (PF) areas (SF polygons are in yellow and PF polygons in red, Figure 2).…”