Estimating farm dam storage using SPOT imagery

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dc.contributor.advisorWinter, Kevinen_ZA
dc.contributor.authorPetersen, Nicole Jadeen_ZA
dc.date.accessioned2015-01-05T06:45:17Z
dc.date.available2015-01-05T06:45:17Z
dc.date.issued2011en_ZA
dc.descriptionIncludes abstract.en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractThe objective of this study is to establish a methodology in which remote sensing can be used to support the monitoring of water resources. SPOT XS imagery and object-oriented classification was used to identify farm dams and their surface area. Two equations applied to determining the capacity of dams were used to convert surface area to volume. The results showed a similarity between fieldwork and object-oriented classification data for surface area. Overall, there appears to be a strong positive correlation between object-oriented classification and unsupervised classification. The correlation between object-oriented classification and supervised classification ranged from strong positive association to little or no association. This study concludes that remote sensing is a useful tool in identifying water bodies and generating an estimate of volume stored.en_ZA
dc.identifier.apacitationPetersen, N. J. (2011). <i>Estimating farm dam storage using SPOT imagery</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science. Retrieved from http://hdl.handle.net/11427/11341en_ZA
dc.identifier.chicagocitationPetersen, Nicole Jade. <i>"Estimating farm dam storage using SPOT imagery."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science, 2011. http://hdl.handle.net/11427/11341en_ZA
dc.identifier.citationPetersen, N. 2011. Estimating farm dam storage using SPOT imagery. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Petersen, Nicole Jade AB - The objective of this study is to establish a methodology in which remote sensing can be used to support the monitoring of water resources. SPOT XS imagery and object-oriented classification was used to identify farm dams and their surface area. Two equations applied to determining the capacity of dams were used to convert surface area to volume. The results showed a similarity between fieldwork and object-oriented classification data for surface area. Overall, there appears to be a strong positive correlation between object-oriented classification and unsupervised classification. The correlation between object-oriented classification and supervised classification ranged from strong positive association to little or no association. This study concludes that remote sensing is a useful tool in identifying water bodies and generating an estimate of volume stored. DA - 2011 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2011 T1 - Estimating farm dam storage using SPOT imagery TI - Estimating farm dam storage using SPOT imagery UR - http://hdl.handle.net/11427/11341 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/11341
dc.identifier.vancouvercitationPetersen NJ. Estimating farm dam storage using SPOT imagery. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science, 2011 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/11341en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Environmental and Geographical Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherEnvironmental Managementen_ZA
dc.titleEstimating farm dam storage using SPOT imageryen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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