Remote sensing of boreal wetlands 1: data use for policy and mangement

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dc.contributor.authorChasmer, Laura
dc.contributor.authorCobbaert, Danielle
dc.contributor.authorMahoney, Craig
dc.contributor.authorMillard, Koreen
dc.contributor.authorPeters, Daniel
dc.contributor.authorDevito, Kevin
dc.contributor.authorBrisco, Brian
dc.contributor.authorHopkinson, Christopher
dc.contributor.authorMerchant, Michael
dc.contributor.authorMontgomery, Joshua
dc.contributor.authorNelson, Kailyn
dc.contributor.authorNiemann, Olaf
dc.date.accessioned2021-09-29T23:13:13Z
dc.date.available2021-09-29T23:13:13Z
dc.date.issued2020
dc.descriptionOpen access article. Creative Commons Attribution 4.0 International License (CC BY 4.0) appliesen_US
dc.description.abstractWetlands have and continue to undergo rapid environmental and anthropogenic modification and change to their extent, condition, and therefore, ecosystem services. In this first part of a two-part review, we provide decision-makers with an overview on the use of remote sensing technologies for the ‘wise use of wetlands’, following Ramsar Convention protocols. The objectives of this review are to provide: (1) a synthesis of the history of remote sensing of wetlands, (2) a feasibility study to quantify the accuracy of remotely sensed data products when compared with field data based on 286 comparisons found in the literature from 209 articles, (3) recommendations for best approaches based on case studies, and (4) a decision tree to assist users and policymakers at numerous governmental levels and industrial agencies to identify optimal remote sensing approaches based on needs, feasibility, and cost. We argue that in order for remote sensing approaches to be adopted by wetland scientists, land-use managers, and policymakers, there is a need for greater understanding of the use of remote sensing for wetland inventory, condition, and underlying processes at scales relevant for management and policy decisions. The literature review focuses on boreal wetlands primarily from a Canadian perspective, but the results are broadly applicable to policymakers and wetland scientists globally, providing knowledge on how to best incorporate remotely sensed data into their monitoring and measurement procedures. This is the first review quantifying the accuracy and feasibility of remotely sensed data and data combinations needed for monitoring and assessment. These include, baseline classification for wetland inventory, monitoring through time, and prediction of ecosystem processes from individual wetlands to a national scale.en_US
dc.description.peer-reviewYesen_US
dc.identifier.citationChasmer, L.,Cobbaert, D., Mahoney, C., Millard, K., Peters, D., Devito, K., Brisco, B., Hopkinson, C., Merchant, M., Mongomery, J., Nelson, K., & Niemann, O. (2020). Remote sensing of boreal wetlands 1: Data use for policy and management. Remote Sensing, 12(8), Article 1320. https://doi.org/10.3390/rs12081320en_US
dc.identifier.urihttps://hdl.handle.net/10133/6053
dc.language.isoen_USen_US
dc.publisherMDPIen_US
dc.publisher.departmentDepartment of Geograpy and Environmenten_US
dc.publisher.facultyArts and Scienceen_US
dc.publisher.institutionUniversity of Lethbridgeen_US
dc.publisher.institutionAlberta Environment and Parksen_US
dc.publisher.institutionCarleton Universityen_US
dc.publisher.institutionEnvironment and Climate Change Canadaen_US
dc.publisher.institutionUniversity of Albertaen_US
dc.publisher.institutionCanada Centre for Mapping and Earth Observationen_US
dc.publisher.institutionDucks Unlimited Canadaen_US
dc.publisher.institutionUniversity of Victoriaen_US
dc.publisher.urlhttps://doi.org/10.3390/rs12081320en_US
dc.subjectWetlanden_US
dc.subjectEcosystem changeen_US
dc.subjectData fusionen_US
dc.subjectRamsar Conventionen_US
dc.subjectBorealen_US
dc.subjectBoreal wetlands
dc.subject.lcshEcology
dc.subject.lcshMulti-sensor data fusion
dc.subject.lcshWetlands
dc.subject.lcshRemote sensing
dc.subject.lcshWetland management
dc.titleRemote sensing of boreal wetlands 1: data use for policy and mangementen_US
dc.typeArticleen_US
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