Name
Abstract | ||
|---|---|---|
As an indicative parameter that represents the ability of the Earth's surface to reflect solar radiation, albedo determines the allocation of solar energy between the Earth's surface and the atmosphere, which plays an important role in both global and local climate change. Urbanization is a complicated progress that greatly affects urban albedo via land cover change, human heat, aerosol, and other human activities. Although many studies have been conducted to identify the effects of these various factors on albedo separately, there are few studies that have quantitatively determined the combined effects of urbanization on albedo. In this study, based on a partial derivative method, vegetation index data and nighttime light data were used to quantitatively calculate the natural climate change and human activities' contributions to albedo variations in the Jing-Jin-Ji region, during its highest population growth period from 2001 to 2011. The results show that (1) 2005 is the year when urbanization starts accelerating in the Jing-Jin-Ji region; (2) albedo trends are equal to 0.0065 year(-1) before urbanization and 0.0012 year(-1) after urbanization, which is a reduction of 4/5; and (3) the contribution rate of urbanization increases from 15% to 48.4%, which leads to a decrease in albedo of approximately 0.05. Understanding the contribution of urbanization to variations in urban albedo is significant for future studies on urban climate change via energy balance and can provide scientific data for energy conservation policymaking. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/rs10071096 | REMOTE SENSING |
Keywords | Field | DocType |
surface albedo,urbanization,vegetation variation,climate change,DMSP | Physical geography,Urbanization,China,Remote sensing,Albedo,Geology | Journal |
Volume | Issue | ISSN |
10 | 7 | 2072-4292 |
Citations | PageRank | References |
1 | 0.36 | 8 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rongyun Tang | 1 | 1 | 0.36 |
| Xiang Zhao | 2 | 41 | 9.19 |
| Tao Zhou | 3 | 7 | 2.10 |
| Bo Jiang | 4 | 10 | 1.11 |
| Donghai Wu | 5 | 5 | 3.31 |
| Bijian Tang | 6 | 20 | 4.11 |