A Remote Sensing-Based Approach to Comprehend Local Warming Trends and Its Influencing Factors
| dc.contributor.advisor | Hassan, Quazi | |
| dc.contributor.advisor | Anil, Gupta | |
| dc.contributor.author | Ejiagha, Ifeanyi | |
| dc.contributor.committeemember | Ashraf, Dewan | |
| dc.contributor.committeemember | Elena, Rangelova | |
| dc.contributor.committeemember | Md Golam, Kibria | |
| dc.contributor.committeemember | Mir, Matin | |
| dc.date | 2022-11 | |
| dc.date.accessioned | 2022-06-13T16:07:41Z | |
| dc.date.available | 2022-06-13T16:07:41Z | |
| dc.date.issued | 2022-06 | |
| dc.description.abstract | One main consequence of anthropogenic activities on the earth’s surface is an increment of local temperature over a long period, i.e., local warming. Local warming modulates the local climate and increases the urban thermal intensity. My overall objective was to develop a remote sensing-based method for comprehending local warming intensity, trends, and potential influencing factors in the Canadian province of Alberta. To achieve this, I investigated the impact of landscape composition and configuration on land surface temperature (LST) in the city of Edmonton at the neighbourhood level. In addition, I quantified local warming trends and their relationship with large-scale atmospheric oscillation in the natural subregions of Alberta and assessed urban warming trends and their potential influencing factors in the cities of Calgary and Edmonton. I employed Landsat 5 Thematic mapper (TM), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), and monthly LST composites of moderate resolution imaging spectroradiometer (MODIS) and four indices of atmospheric oscillation from 2001 to 2020. I derived land use land cover (LULC) and LST maps from Landsat images to assess the impact of LULC composition and configuration on Edmonton’s LST. I also determined monthly and annual local warming trends in the natural subregions of Alberta and urban warming in the cities of Calgary and Edmonton using the MODIS data. My results indicated the highest LST in residential and industrial neighbourhoods of Edmonton caused by the proportion and clustered arrangement of landscape patterns, where residential exhibited higher LST than industrial with the same LULC composition. Also, I found significant warming trends in May for most of the natural subregions of the Rocky Mountains and Boreal Forest, and Pacific North America (PNA) was the only atmospheric oscillation with influence from February to April and October to December. Besides, I found a continuous increase in annual day and nighttime surface urban heat island intensity (SUHI) in Calgary and Edmonton over the last 20 years. I deduced that population, built-up expansion, and sea surface temperature (SST) were the main factors that influenced the urban temperature. The findings of this research would be helpful for policymakers and urban planners to develop adaptation and mitigating strategies to curb the impact of local warming, ensuring a sustainable city and environment. | en_US |
| dc.identifier.citation | Ejiagha, I. (2022). A remote sensing-based approach to comprehend local warming trends and its influencing factors (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. | en_US |
| dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/39821 | |
| dc.identifier.uri | http://hdl.handle.net/1880/114733 | |
| dc.language.iso | eng | en_US |
| dc.publisher.faculty | Schulich School of Engineering | en_US |
| dc.publisher.institution | University of Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | en_US |
| dc.subject | Local warming trend | en_US |
| dc.subject.classification | Remote Sensing | en_US |
| dc.title | A Remote Sensing-Based Approach to Comprehend Local Warming Trends and Its Influencing Factors | en_US |
| dc.type | doctoral thesis | en_US |
| thesis.degree.discipline | Engineering – Geomatics | en_US |
| thesis.degree.grantor | University of Calgary | en_US |
| thesis.degree.name | Doctor of Philosophy (PhD) | en_US |
| ucalgary.item.requestcopy | true | en_US |