Satellite-detected gain in built-up area as a leading economic indicator. (30th October 2019)

• Record Type: Journal Article
• Authors: Ying, Qing; Hansen, Matthew C; Sun, Laixiang; Wang, Lei; Steininger, Marc
• Is Part Of: Environmental research letters. Volume 14:Number 11(2019:Nov.)
• Publication Date: 2019-10-30
• Subjects: leading economic indicator -- built-up area -- anthropogenic bare ground gain -- global and regional scale -- the great recession -- spatio-temporal dynamics -- landsat; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/ab443e
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: 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 4, Huang et al 17, Orphanides 24 ). 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 7875 km 2 yr −1, with a peak gain of 11 875 (± 2014 km 2 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.