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- Devendran, Aarthi Aishwarya, 1986-, et al.
(författare)
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Spatial interaction model of energy demand of buildings and satellite thermal imageries using Geographically Weighted Regression analysis
- 2022
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Ingår i: eceee 2022 Summer Study on energy efficiency. - : European Council for an Energy Efficient Economy (ECEEE). - 9789198827002 ; , s. 559-569
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Konferensbidrag (refereegranskat)abstract
- The Energy Performance Certificate (EPC) is an important information tool to improve the energy performance (EP) of buildings. However, establishing the EP of building is tedious, time-consuming, and numerous input parameters are required in its estimation. However, the usefulness of EPC for the implementation of customized solutions by the supply-side actors require that EPCs are available for all buildings, easily accessible, credible, and recent. However, this is not the case at present. This could be addressed by employing remote sensing dataset along with GIS based spatial analysis techniques. In the present study, the spatial regression analysis technique is implemented in identifying the spatial relation between the input variables and the EP of selected 4541 buildings within Växjö municipality, Sweden.The input variables used in the study include the land surface temperature (LST) maps of summer and spring of 2020 derived through the thermal band of Landsat 8 satellite data, built-up and openland neighbourhood maps prepared from the land use/land cover map 2020 of the study region. Building topology including year of construction, type, category, and complexity of buildings are also used to identify the relation between the input variables and the EP of those selected buildings. Results of spatial regression analysis reveal a significant positive relation between the LST and EP of buildings (regression co-efficient are 0.86 and 0.95 in spring and summer respectively).The stronger correlation in summer could be because of the availability of higher intensity of solar radiation which gets absorbed by the built-up regions. Results suggest that the LST maps derived from satellite imageries could provide information on the EP of buildings. This could be beneficial to local decision makers and policy regulators in identifying the buildings with lower EP with better accuracy with less dependence on EPC data which are sometimes not available or not updated. The results could also be beneficial to investment bankers, real estate companies during the purchase and sale of a building. Policy makers and renovation companies could get benefited with the results in preliminary identification of the potential hotspots for district energy renovation where the EP of buildings is poorer. This could help achieve the goal of sustainable urban planning targeting energy reduction, climate adaptation, through implementation of effective energy management strategies in the building sector.
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| 2. |
- Devendran, Aarthi Aishwarya, 1986-, et al.
(författare)
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Spatio-Temporal Land Cover Analysis and the Impact of Land Cover Variability Indices on Land Surface Temperature in Greater Accra, Ghana Using Multi-Temporal Landsat Data
- 2022
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Ingår i: Journal of Geographic Information System. - : Scientific Research Publishing. - 2151-1950 .- 2151-1969. ; 14:3, s. 240-258
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Tidskriftsartikel (refereegranskat)abstract
- Urbanization, as a result of anthropogenic activities, reduces the vegetated and green spaces and thereby increases the impervious surfaces in cities. This in turn increases the surface temperature of cities when compared to the rural regions resulting in the formation of urban heat island. Especially, in under-developed countries, it is very crucial to obtain timely and accurate information on the urban trend and its development due to the higher increasing rate of population growth and lack of infrastructural facilities and regulations to mitigate the adverse consequences of urbanization. The current study analyzes the urban development of Greater Accra, Ghana using Landsat 7 dataset acquired in 2002, 2013, and 2020. Further, the influence of urban growth on the land surface temperature (LST) and land cover variability (LCV) indices including NDVI (Normalized Difference Vegetation Index), NDBI(Normalized Difference Built-Up Index), and NDWI (Normalized Difference Water Index) is identified during the study periods. Results suggest that the area of built-up quadrupled between 2002 and 2020 in the study region.Shannon’s entropy-based analysis suggests that the urban development in the region is heterogeneous or dispersive in nature. Further, the regression analysis highlights a strong positive relation between LST and NDBI (0.755) and a negative relation is found associated between LST and NDVI (0.4417) and LST and NDWI (0.76). Results of the study could be useful to design sustainable urban socio-economic and environmental planning policies in the study region.
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