Indiana University-Purdue University Indianapolis (IUPUI) / Better comprehension of the Urban Heat Island study requires information on the natural
as well as built characteristics of the environment at high spatial resolution. Sky View
Factor (SVF) has been distinguished as a significant parameter for Local Climate Zone
(LCZ) classification based on environmental characteristics that influence the urban
climate at finer spatial scales. The purpose of this thesis was to evaluate currently
available data sources and methods for deriving continuous SVF estimates. The specific
objectives were to summarize the characteristics of currently available digital surface
models (DSMs) of the study region and to compare the results of using these models to
estimate SVF with three different raster-based algorithms: Horizon Search Algorithm in
R-programming (Doninck, 2018), Relief Visualization Toolbox (RVT) (Žiga et al.,
2016), and the Urban Multi-scale Environmental Predictor (UMEP) plugin in QGIS
(Lindberg, et al., 2018).
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/28041 |
| Date | 02 1900 |
| Creators | Adhikari, Bikalpa |
| Contributors | Wilson, Jeffrey S., Dwyer, Owen J., Banerjee, Aniruddha, Thapa, Bhuwan |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Rights | Attribution-NonCommercial-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Page generated in 0.0019 seconds