Submitter and Co-author information

Yijun WanghuangFollow

Standing

Graduate (Masters)

Type of Proposal

Poster Presentation

Faculty

Faculty of Science

Faculty Sponsor

Cameron Proctor

Abstract/Description of Original Work

Lakes are one of the most important freshwater resources on the earth, yet water quality in Dianchi Lake (China) has been declining due to increased human usage and alterations to the natural landscape. Wetlands surrounding the lake help buffer it from human impacts, can purify agricultural and other pollutants, and artificial wetlands have been suggested as a solution to improve lake water quality. It is unclear if the efficacy of lakeside wetlands varies and if the spatial pattern of these wetlands is a contributing factor to near shore water quality. Assessing lakeside wetlands characteristics relies upon high-resolution surveys, which is offered by UAV hyperspectral remote sensing as it offers high spatial resolution, strong band continuity and large amount of spectral information and has been widely used for wetland plant classification and physicochemical parameter retrieval. To quantify the relationship between near shore water quality and wetlands pattern, we conducted a hyperspectral UAV survey that characterized land cover classes and their spatial arrangement in 10 different coastal lake sections. Specifically, supervised classification was performed on the preprocessed hyperspectral images and Fragstats was used to calculate multiple landscape composition, connectivity, and configuration. These spatial pattern metrics will be correlated to the 8 measured water quality metrics including temperature(T), dissolved oxygen (DO), electrical conductance (EC), total nitrogen (TN), total phosphorus(TP),NH3-N,pH and chlorophyll a. Principal components analysis will be used to reduce the water quality data dimensionality. This research provides feasible theoretical and technical support for future wetland ecosystem protection and monitoring.

Share

COinS
 

The relationship between the spatial pattern of lakeside wetlands and water quality utilizing UAV hyperspectral remote sensing

Lakes are one of the most important freshwater resources on the earth, yet water quality in Dianchi Lake (China) has been declining due to increased human usage and alterations to the natural landscape. Wetlands surrounding the lake help buffer it from human impacts, can purify agricultural and other pollutants, and artificial wetlands have been suggested as a solution to improve lake water quality. It is unclear if the efficacy of lakeside wetlands varies and if the spatial pattern of these wetlands is a contributing factor to near shore water quality. Assessing lakeside wetlands characteristics relies upon high-resolution surveys, which is offered by UAV hyperspectral remote sensing as it offers high spatial resolution, strong band continuity and large amount of spectral information and has been widely used for wetland plant classification and physicochemical parameter retrieval. To quantify the relationship between near shore water quality and wetlands pattern, we conducted a hyperspectral UAV survey that characterized land cover classes and their spatial arrangement in 10 different coastal lake sections. Specifically, supervised classification was performed on the preprocessed hyperspectral images and Fragstats was used to calculate multiple landscape composition, connectivity, and configuration. These spatial pattern metrics will be correlated to the 8 measured water quality metrics including temperature(T), dissolved oxygen (DO), electrical conductance (EC), total nitrogen (TN), total phosphorus(TP),NH3-N,pH and chlorophyll a. Principal components analysis will be used to reduce the water quality data dimensionality. This research provides feasible theoretical and technical support for future wetland ecosystem protection and monitoring.