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Open AccessArticle

A Map Spectrum-Based Spatiotemporal Clustering Method for GDP Variation Pattern Analysis Using Nighttime Light Images of the Wuhan Urban Agglomeration

by 1,2, 1,2 and 1,*
1
School of Remote Sensing and Information Engineering, Wuhan University, Luoyu Road 129, Wuhan 430079, China
2
Collaborative Innovation Center of Geospatial Information Technology, Wuhan University, Luoyu Road 129, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Academic Editors: Jamal Jokar Arsanjani and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2017, 6(6), 160; https://doi.org/10.3390/ijgi6060160
Received: 24 March 2017 / Revised: 12 May 2017 / Accepted: 27 May 2017 / Published: 31 May 2017
Estimates of gross domestic product (GDP) play a significant role in evaluating the economic performance of a country or region. Understanding the spatiotemporal process of GDP growth is important for estimating or monitoring the economic state of a region. Various GDP studies have been reported, and several studies have focused on spatiotemporal GDP variations. This study presents a map spectrum-based clustering approach to analyze the spatiotemporal variation patterns of GDP growth. First, a sequence of nighttime light images (from the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS)) is used to support the spatial distribution of statistical GDP data. Subsequently, the time spectrum of each spatial unit is generated using a time series of dasymetric GDP maps, and then the spatial units with similar time spectra are clustered into one class. Each category has a similar spatiotemporal GDP variation pattern. Finally, the proposed approach is applied to analyze the spatiotemporal patterns of GDP growth in the Wuhan urban agglomeration. The experimental results illustrated regional discrepancies of GDP growth existed in the study area. View Full-Text
Keywords: map spectrum; spatiotemporal clustering; nighttime light image; GDP growth patterns; Wuhan urban agglomeration map spectrum; spatiotemporal clustering; nighttime light image; GDP growth patterns; Wuhan urban agglomeration
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Zhang, P.; Liu, S.; Du, J. A Map Spectrum-Based Spatiotemporal Clustering Method for GDP Variation Pattern Analysis Using Nighttime Light Images of the Wuhan Urban Agglomeration. ISPRS Int. J. Geo-Inf. 2017, 6, 160.

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