First order approximation of broadband directional Albedo with High Resolution Quickbird Imagery: A case study for arid urban areas

Publication Type

Journal Article

Publication Date

2-2016

Abstract

Albedo is a key forcing parameter controlling the planetary radiative energy budget and its partitioning between the surface and the atmosphere. Characterizing and developing high resolution albedo for an urban environment in arid regions is important because of the high urbanization rate in these regions and because of the high land-cover heterogeneity within urban settings. Using a Monte Carlo simulation of a multi-variable regression, we (a) correlate directional solar reflectance (albedo) ground measurements from Phoenix, AZ, with four narrowband reflectance data from QuickBird, and (b) developed a new set of coefficients for converting QuickBird narrowband reflectances to albedo. The albedo models were then applied to a second image over Las Vegas, NV, to assess their feasibility and accuracy. Two wavebands, visible-near infrared (VNIR) and total shortwave albedo, were evaluated for two reflectance models: surface and top-of-atmosphere. Results show that it is possible to accurately estimate directional albedo from high resolution imagery, specifically QuickBird, with the most accurate result from an atmospherically corrected VNIR model. The methodology presented in this paper could thus be applied in other urban areas to obtain a first order estimation of albedo. The new set of coefficients can be applied as first order albedo estimate by researchers, urban planners, developers and city managers interested in the influence of high-resolution albedo on a myriad of urban ecosystem processes.

Keywords

Albedo, urban, Quickbird, modeling, arid regions, high resolution

Discipline

Urban Studies and Planning

Research Areas

Political Science

Publication

GIScience and Remote Sensing

Volume

53

Issue

3

First Page

303

Last Page

319

ISSN

1548-1603

Identifier

10.1080/15481603.2016.1153944

Publisher

Taylor & Francis: STM, Behavioural Science and Public Health Titles

Additional URL

https://doi.org/10.1080/15481603.2016.1153944

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