Remote sensing of boreal wetlands 2: methods for evaluating boreal wetland ecosystem state and drivers of change
Date
2020
Authors
Chasmer, Laura
Mahoney, Craig
Millard, Koreen
Nelson, Kailyn
Peters, Daniel
Merchant, Michael
Hopkinson, Christopher
Brisco, Brian
Niemann, Olaf
Montgomery, Joshua
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
The following review is the second part of a two part series on the use of remotely sensed data for quantifying wetland extent and inferring or measuring condition for monitoring drivers of change on wetland environments. In the first part, we introduce policy makers and non-users of remotely sensed data with an effective feasibility guide on how data can be used. In the current review, we explore the more technical aspects of remotely sensed data processing and analysis using case studies within the literature. Here we describe: (a) current technologies used for wetland assessment and monitoring; (b) the latest algorithmic developments for wetland assessment; (c) new technologies; and (d) a framework for wetland sampling in support of remotely sensed data collection. Results illustrate that high or fine spatial resolution pixels (≤10 m) are critical for identifying wetland boundaries and extent, and wetland class, form and type, but are not required for all wetland sizes. Average accuracies can be up to 11% better (on average) than medium resolution (11–30 m) data pixels when compared with field validation. Wetland size is also a critical factor such that large wetlands may be almost as accurately classified using medium-resolution data (average = 76% accuracy, stdev = 21%). Decision-tree and machine learning algorithms provide the most accurate wetland classification methods currently available, however, these also require sampling of all permutations of variability. Hydroperiod accuracy, which is dependent on instantaneous water extent for single time period datasets does not vary greatly with pixel resolution when compared with field data (average = 87%, 86%) for high and medium resolution pixels, respectively. The results of this review provide users with a guideline for optimal use of remotely sensed data and suggested field methods for boreal and global wetland studies.
Description
Open access article. Creative Commons Attribution 4.0 International License (CC BY 4.0) applies
Keywords
Object oriented classification , Decision-tree , Lidar , Hyperspectral , Monitoring , Ecosystem change , Boreal wetlands , Ramsar Convention
Citation
Chasmer, L., Mahoney, C., Millard, K., Nelson, K., Peters, D., Merchant, M., Hopkinson, C., Brisco, B., Niemann, O., Montgomery, J., Devito, K., & Cobbaert, D. (2020). Remote sensing of boreal wetlands 2: Methods for evaluating boreal wetland ecosystem state and drivers of change. Remote Sensing, 12(8), Article 1321. https://doi.org/10.3390/rs12081321