Modelling, Characterizing, and Monitoring Boreal Forest Wetland Bird Habitat with RADARSAT-2 and Landsat-8 Data

Evan R Delancey,Fiona Gregory,Brian Brisco,Richard Hedley,Erin M Bayne,Logan J T Mcleod,Kevin Murnaghan,Jahan Kariyeva

doi:10.3390/w13172327

Abstract

Earth observation technologies have strong potential to help map and monitor wildlife habitats. Yellow Rail, a rare wetland obligate bird species, is a species of concern in Canada and provides an interesting case study for monitoring wetland habitat with Earth observation data. Yellow Rail has highly specific habitat requirements characterized by shallowly flooded graminoid vegetation, the availability of which varies seasonally and year-to-year. Polarimetric Synthetic Aperture Radar (SAR) in combination with optical data should, in theory, be a great resource for mapping and monitoring these habitats. This study evaluates the use of RADARSAT-2 data and Landsat-8 data to characterize, map, and monitor Yellow Rail habitat in a wetland area within the mineable oil sands region. Specifically, we investigate: (1) The relative importance of polarimetric SAR and Landsat-8 data for predicting Yellow Rail habitat; (2) characterization of wetland habitat with polarimetric SAR data; (3) yearly trends in available habitat; and (4) predictions of potentially suitable habitat across northeastern Alberta. Results show that polarimetric SAR using the Freeman–Durden decomposition and polarization ratios were the most important predictors when modeling the Yellow Rail habitat. These parameters also effectively characterize this habitat based on high congruence with existing descriptions of suitable habitat. Applying the prediction model across all wetland areas showed accurate predictions of occurrence (validated on field occurrence data), and high probability habitats were constrained to very specific wetland areas. Using the RADARSAT-2 data to monitor yearly changes to Yellow Rail habitat was inconclusive, likely due to the different image acquisition times of the 2014 and 2016 images, which may have captured seasonal, rather than inter-annual, wetland dynamics. Polarimetric SAR has proved to be very useful for capturing the specific hydrology and vegetation structure of the Yellow Rail habitat, which could be a powerful technology for monitoring and conserving wetland species habitat.

Highlights

This study aims to build on the work from [16,28] by investigating the importance of polarimetric Synthetic Aperture Radar (SAR) from RADARSAT-2 for developing more accurate predictive models of the YERA habitat
Most non-backscatter RADARSAT-2 inputs showed distinct differences between present/absent sites (Figure 2 panel b and c), while the Landsat-8 indices tended to overlap more between the two site types (Figure 2 panel d)
As expected, based on the figures above, the three most important variables are RADARSAT-2 inputs which control the majority of the model

Summary

Introduction

EO data can provide continuous predictor variables which require no interpolation or sampling biases [1]. These predictor variables are often the most useful in modern presence/absence species distribution models using techniques like Boosted Regression Trees [2]. Wetland mapping and monitoring with EO sensors, such as optical, Synthetic Aperture Radar (SAR), and Light Detection and Ranging have been well studied [3,4,5,6,7], but the application of these technologies to characterize species habitat within wetlands is the logical step which can help habitat monitoring and conservation efforts

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Conclusion