SOAS Research Online

A Free Database of the Latest Research by SOAS Academics and PhD Students

[skip to content]

Ying, Qing, Hansen, Matthew C., Sun, Laixiang, Wang, Lei and Steininger, Marc (2019) 'Satellite-detected gain in built-up area as a leading economic indicator.' Environmental Research Letters, 14 (114015). pp. 1-11.

Text - Published Version
Available under License Creative Commons Attribution 4.0 (CC-BY 4.0).

Download (1MB) | Preview


Leading indicators of future economic activity include measures such as new housing starts, managers purchasing index, money supply, and bond yields. Such macroeconomic and financial indicators hold predictive power in signaling recessionary periods. However, many indicators are constrained by the fact that data are often published with some delay and are subject to constant revision (Bandholz and Funke 2003,Huanget al 2018,Orphanides 2003). In this research, we propose a leading indicator derived from satellite imagery, the expansion of anthropogenic bare ground. Satellite-detected gain in built-up area, a major land cover and land use (LCLU) outcome of anthropogenic bare ground gain (ABGG), provides an inexpensive, consistent, and near-real-time indicator of global and regional macroeconomic change. Our panel data analysis across four major regions of the world from 2001 to 2012 shows that the logarithm of total ABGG, mostly owing to its major LCLU outcome, the expansion of built-up land in either year t, t−1 or t−2, significantly correlated with the year t logarithm of gross domestic product (GDP, de-trended by Hodrick–Prescott filter). Global ABGG between 2001 and 2012 averaged 7875km2 yr−1, with a peak gain of 11 875 (±2014km2 at the 95%confidence interval) in 2006, prior to the 2007–2008 global financial crisis. The curve of global ABGG or its major LCLU outcome of built-up area in year t−1 accords well with that of the de-trended logarithm of the global GDP in year t. Given the 40 year archive of free satellite data, a growing satellite constellation, advances in machine learning, and scalable methods, this study suggests that analyses of ABGG as a whole or its LCLU outcomes can provide valuable information in near-real time for socioeconomic research, development planning, and economic forecasting.

Item Type: Journal Article
Keywords: leading economic indicator, built-up area, anthropogenic bare ground gain, global and regional scale, the great recession, spatio-temporal dynamics, landsat
SOAS Departments & Centres: Departments and Subunits > School of Finance & Management
ISSN: 17489326
Copyright Statement: Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI
DOI (Digital Object Identifier):
Date Deposited: 07 Dec 2020 10:35
Related URLs: https://iopscie ... 748-9326/ab443e (Publisher URL)
Funders: Other

Altmetric Data


Download activity - last 12 monthsShow export options
Downloads since deposit
6 month trend
6 month trend
Accesses by country - last 12 monthsShow export options
Accesses by referrer - last 12 monthsShow export options

Repository staff only

Edit Item Edit Item