SAR and lidar temporal data fusion approaches to boreal wetland ecosystem monitoring

Simple item page
dc.contributor.authorMontgomery, Joshua
dc.contributor.authorBrisco, Brian
dc.contributor.authorChasmer, Laura
dc.contributor.authorDevito, Kevin
dc.contributor.authorCobbaert, Danielle
dc.contributor.authorHopkinson, Christopher
dc.date.accessioned2021-10-20T20:28:02Z
dc.date.available2021-10-20T20:28:02Z
dc.date.issued2019
dc.descriptionOpen access article. Creative Commons Attribution 4.0 International License (CC BY 4.0) appliesen_US
dc.description.abstractThe objective of this study was to develop a decision-based methodology, focused on data fusion for wetland classification based on surface water hydroperiod and associated riparian (transitional area between aquatic and upland zones) vegetation community attributes. Multi-temporal, multi-mode data were examined from airborne Lidar (Teledyne Optech, Inc., Toronto, ON, Canada, Titan), synthetic aperture radar (Radarsat-2, single and quad polarization), and optical (SPOT) sensors with near-coincident acquisition dates. Results were compared with 31 field measurement points for six wetlands at riparian transition zones and surface water extents in the Utikuma Regional Study Area (URSA). The methodology was repeated in the Peace-Athabasca Delta (PAD) to determine the transferability of the methods to other boreal environments. Water mask frequency analysis showed accuracies of 93% to 97%, and kappa values of 0.8–0.9 when compared to optical data. Concordance results comparing the semi-permanent/permanent hydroperiod between 2015 and 2016 were found to be 98% similar, suggesting little change in wetland surface water extent between these two years. The results illustrate that the decision-based methodology and data fusion could be applied to a wide range of boreal wetland types and, so far, is not geographically limited. This provides a platform for land use permitting, reclamation monitoring, and wetland regulation in a region of rapid development and uncertainty due to climate change. The methodology offers an innovative time series-based boreal wetland classification approach using data fusion of multiple remote sensing data sources.en_US
dc.description.peer-reviewYesen_US
dc.identifier.citationMontgomery, J., Brisco, B., Chasmer, L., Devito, K., Cobbaert, D.,& Hopkinson, C. (2019). SAR and lidar temporal data fusion approaches to boreal wetland ecosystem monitoring. Remote Sensing, 11(2), Article 161. https://doi.org/10.3390/rs11020161en_US
dc.identifier.urihttps://hdl.handle.net/10133/6070
dc.language.isoen_USen_US
dc.publisherMDPIen_US
dc.publisher.departmentDepartment of Geograpy and Environmenten_US
dc.publisher.facultyArts and Scienceen_US
dc.publisher.institutionAlberta Environment and Parksen_US
dc.publisher.institutionUniversity of Lethbridgeen_US
dc.publisher.institutionNatural Resources Canadaen_US
dc.publisher.institutionUniversity of Albertaen_US
dc.publisher.urlhttps://doi.org/10.3390/rs11020161en_US
dc.subjectSARen_US
dc.subjectLidaren_US
dc.subjectBoreal wetlandsen_US
dc.subjectData fusionen_US
dc.subjectDecision-based methodologyen_US
dc.subjectTime seriesen_US
dc.subjectEcosystem monitoring
dc.subject.lcshSynthetic aperture radar
dc.subject.lcshOptical radar
dc.subject.lcshWetlands
dc.subject.lcshMultisensor data fusion
dc.titleSAR and lidar temporal data fusion approaches to boreal wetland ecosystem monitoringen_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Chasmer-SAR-and-lidar.pdf
Size:
9.84 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.75 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Chasmer, Laura
Hopkinson, Christopher