The Application of Remote Sensing and GIS for Improving Modeling the Response of Wetland Vegetation Communities to Water Level Fluctuations at Long Point, Ontario
| dc.contributor.author | Huang, Jingwen | |
| dc.date.accessioned | 2016-09-27T22:23:43Z | |
| dc.date.available | 2016-09-27T22:23:43Z | |
| dc.date.issued | 2016-09-27 | |
| dc.date.submitted | 2016-09-26 | |
| dc.description.abstract | Coastal wetlands are complex and dynamic environments which are of high environmental, social, and economic importance. With the acceleration of climate change and global warming, it is necessary to monitor and protect dynamic coastal wetlands. Wetland ecosystem simulation modeling is one approach to help produce better wetland protection and management strategies. The application of remote sensing and Geographic Information System (GIS) in wetland ecosystem simulation models can help with better spatial modeling of wetland ecosystems. In addition, coastal topographic models can achieve digital representations of terrain surfaces and aquatic environments. This study applies remote sensing and GIS technologies for improving wetland vegetation simulation modeling. First, the study integrates multiple topographic data sources (i.e. Light Detection and Ranging data (LiDAR) and bathymetry data) to generate a coastal topographic model. Shoreline data are involved in the generation process. Second, a pre-existing wetland simulation model is updated to a new version to model the response of wetland vegetation communities to water level fluctuations at Long Point, Ontario. Third, different coastal topographic models have been employed to explore how a coastal topographic model affects the wetland simulation results. Model sensitivity analysis is conducted to explore the variation of model simulation results to different vegetation transition baselines parameter. Findings from this study suggest that a high accuracy coastal topographic model could yield a higher accuracy simulation result in a wetland ecosystem simulation model. Second, the application of remote sensing and the integration of multiple topographic data (e.g. LiDAR data and bathymetry data) could provide high accuracy and high density elevation information in coastal area, especially in land-water transitional areas. Finally, a narrower vegetation transition baseline increases the possibility for a wetland community shift to a wetter wetland community. | en |
| dc.identifier.uri | http://hdl.handle.net/10012/10940 | |
| dc.language.iso | en | en |
| dc.pending | false | |
| dc.publisher | University of Waterloo | en |
| dc.title | The Application of Remote Sensing and GIS for Improving Modeling the Response of Wetland Vegetation Communities to Water Level Fluctuations at Long Point, Ontario | en |
| dc.type | Master Thesis | en |
| uws-etd.degree | Master of Science | en |
| uws-etd.degree.department | Geography and Environmental Management | en |
| uws-etd.degree.discipline | Geography | en |
| uws-etd.degree.grantor | University of Waterloo | en |
| uws.comment.hidden | Hi, Sorry, I deleted my previsou submission by accident and re-start a new one. So sorry about the inconvinence. Regards, Jingwen | en |
| uws.contributor.advisor | Su-yin, Tan | |
| uws.contributor.affiliation1 | Faculty of Environment | en |
| uws.peerReviewStatus | Unreviewed | en |
| uws.published.city | Waterloo | en |
| uws.published.country | Canada | en |
| uws.published.province | Ontario | en |
| uws.scholarLevel | Graduate | en |
| uws.typeOfResource | Text | en |