Porovnat metody

	Urban Heat Island Analysis	Urban Sprawl Measurement
Obor	Urban Studies	Urban Studies
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	1982	2014
Tvůrce	Tim R. Oke (energetic basis of the UHI)	Reid Ewing & Shima Hamidi (building on Galster et al.)
Typ	Measurement of the temperature excess of urban areas relative to their rural surroundings	Composite index combining multiple dimensions of urban form into a sprawl/compactness score
Původní zdroj	Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24.	Ewing, R., & Hamidi, S. (2015). Compactness versus sprawl: A review of recent evidence from the United States. Journal of Planning Literature, 30(4), 413–432.
Další názvy	UHI Analysis, Urban Heat Island Intensity, Surface Urban Heat Island (SUHI) Analysis, Land Surface Temperature Differential	Sprawl Index, Compactness Index of Sprawl, Ewing Sprawl Index, Composite Sprawl Measure
Příbuzné	4	4
Shrnutí	Urban heat island (UHI) analysis quantifies how much warmer cities are than the rural land around them, a difference driven by impervious surfaces, reduced vegetation, waste heat, and street-canyon geometry that traps radiation. The intensity of the effect is defined simply as the urban-minus-rural temperature differential, a framework given its physical, energy-balance foundation by Tim Oke in 1982. Modern analysis increasingly maps the surface UHI from thermal satellite imagery, converting radiance to brightness temperature and then to land surface temperature so the heat island can be observed continuously across an entire metropolitan area rather than at a few weather stations.	Urban sprawl measurement quantifies how compact or sprawling a metropolitan region is by combining several distinct dimensions of urban form into a single composite index. The dominant approach, developed by Reid Ewing, Shima Hamidi and colleagues, captures four factors — development density, land-use mix, activity centering, and street-network connectivity — and folds standardized indicators of each into one score, calibrated so the average region equals 100 and higher values mean greater compactness. Because sprawl is multidimensional, no single variable such as density adequately describes it, which is why the composite-index strategy has become the standard for comparing regions and linking form to outcomes.