Consistent, accurate, high resolution, long time-series mapping of built-up land in the North China Plain. Issue 7 (3rd October 2021)

• Record Type: Journal Article
• Authors: Wang, Jinzhu; Hadjikakou, Michalis; Bryan, Brett A.
• Is Part Of: GIScience & remote sensing. Volume 58:Issue 7(2021)
• Page Start: 982
• Page End: 998
• Publication Date: 2021-10-03
• Subjects: Built-up land -- urbanization -- fourier transformation -- mapping -- remote sensing -- time-series; Geodesy -- Periodicals; Cartography -- Periodicals; Aerial photogrammetry -- Periodicals; Remote sensing -- Periodicals; 526.05
• DOI: 10.1080/15481603.2021.1948275
• Languages: English
• ISSNs: 1548-1603

Abstract

ABSTRACT: Accurate, long time-series, high-resolution mapping of built-up land dynamics is essential for understanding urbanization and its environmental impacts. Despite advances in remote sensing and classification algorithms, built-up land mapping which only uses spectral data and derived indices remains prone to uncertainty. We mapped the extent of built-up land in the North China Plain, one of China's most important agricultural regions, from 1990 to 2019 at three-yearly intervals and 30 m spatial resolution. We applied Discrete Fourier Transformation to dense time-stack Landsat data to create Fourier predictors to reduce mapping uncertainty. As a result, we improved the overall accuracy of built-up land mapping by 8% compared to using spectral data and derived indices. In addition, a temporal correction algorithm applied to remove misclassified pixels further improved mapping accuracy to a consistently high level (>94%) over the time periods. A cross-product comparison showed that our maps achieved the highest accuracies across all years. The built-up land area in the North China Plain increased from 37, 941 km 2 in 1990–1992 to 131, 578 km 2 in 2017–2019. Consistent, high-accuracy, long time-series built-up land mapping provides a reliable basis for formulating policy and planning in one of the most rapidly urbanizing regions on this planet.