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dc.creatorXu, Dandan 1987-
dc.date.accessioned2017-10-06T21:15:35Z
dc.date.available2018-10-16T17:31:19Z
dc.date.created2016-03
dc.date.submittedMarch 2016
dc.identifier.urihttp://hdl.handle.net/10388/ETD-2016-03-2473
dc.identifier.urihttp://hdl.handle.net/10388/8190
dc.description.abstractGrassland ecosystems cover a large portion of the Earth surface and have similar economic and ecological values as croplands and forest ecosystems. To sustainably provide ecosystem services through grasslands, grassland management bridges the connection between the provision of grassland services and maintenance of grassland conditions. Therefore, it is important to select suitable methods of management for grassland services based on the particular conditions of grasslands. In order to implement appropriate management methods in grassland ecosystem, it is necessary to monitor grassland response and compare it to previous grassland management through long-term time periods, then separate the impact of various methods of management and climate changes. The purpose of this research is to monitor and measure the grassland response to management methods using optical remote sensing (RS) imagery. More specifically, the purpose is to overcome the challenges facing the application of optical RS for evaluating grassland conditions (dead material estimation and the issue of mixed pixel for green vegetation extraction), to monitor the lag impact of long-term conservation actions, and to quantify and separate the effects of management and climate conditions as well as their interactions. The study area is Grasslands National Park (GNP) including the West Block and East Block which is located in the southern part of Saskatchewan, Canada and falls in the mixed prairie ecoregion of North American Great Plains. The results of this research provides the methodology to estimate the dead material and extract the information (coverage or biomass) of green vegetation from mixed pixels containing bare soil, soil crust and dead materials using multispectral RS images. The results also indicate that combining optical RS with historical data of over 40 years has the advantage in monitoring the lag effects of grassland management and in evaluating the best time intervals for certain strategies of grassland management by calibrating of field-collected biophysical parameters and spectra. This research proves that optical RS images can be used to quantitatively separate the effects of grassland management and climate change as well as the interactions between the two when prior data on the intensity of the grassland management is available.
dc.format.mimetypeapplication/pdf
dc.subjectbiodiversity
dc.subjectsoil organic matter
dc.subjectconservation actions
dc.subjectremote sensing
dc.subjectgrassland management
dc.subjectgrazing management
dc.subjectbiomass
dc.subjectgrassland
dc.subjectdead material
dc.subjectsoil line
dc.subjectlag effects
dc.subjectlitter cover
dc.subjectinteraction between grazing and climate.
dc.titleMeasuring grassland response to management using optical remote sensing
dc.typeThesis
dc.date.updated2017-10-06T21:15:35Z
thesis.degree.departmentGeography and Planning
thesis.degree.disciplineGeography
thesis.degree.grantorUniversity of Saskatchewan
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)
dc.type.materialtext
dc.contributor.committeeMemberGuo, Xulin
dc.contributor.committeeMemberLamb, Eric
dc.contributor.committeeMemberReed, Maureen
dc.contributor.committeeMemberPatrick, Bob
dc.contributor.committeeMemberde Boer, Dirk
local.embargo.terms2018-10-06


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