Monitoring Regional Urban Dynamics Using DMSP/OLS Nighttime Light Data in Zhejiang Province

Pengfei Xu,Qian Cheng,Pingbin Jin

doi:10.1155/2020/9652808

Abstract

Accurate monitoring of urban regions and urban sprawls is critical to the detection and assessment of regional development. The nighttime light images of Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) provide us direct solutions to make spatial descriptions of urban regions. Unfortunately, accurate monitoring of urban regions is apt to be hampered due to the shortages of the DMSP/OLS data. In this study, we utilized a new urban region extraction strategy based on the edge-detection method which is widely applied in automatic digital image processing. The edges of urban areas in Zhejiang province were identified based on the distributions and values of pixels. Compared with other traditional methods, the urban regions extracted in this study present a higher overall accuracy and kappa coefficient (OA = 93.1409%; Kappa = 0.8755). Two periods of the urban dynamic process and urban sprawl pattern in Zhejiang from 1992–2013 were further detected by the proposed method. At city level, the drastic increase in urban areas was found in cities of Hangzhou and Ningbo. This study provides an objective and convenient solution to the accurate identification of urban regions, which is also an important step to better understand the urban dynamics and urban development.

Highlights

Traditional urbanization studies are mostly based on statistic data collected by the government, which is usually lack of timeliness and accuracy and could not provide timely spatial detection of urbanization
Various remote sensing data have been applied at different scales with different research targets such as the Landsat ematic Mapper/Enhanced ematic Mapper plus (TM/ETM+), QuickBird, IKONOS, and SPOT/ High Resolution Visible (HRV)
E DMSP/OLS nighttime light images consist of pixels with locations and illuminance information of ground surface, and it had been widely accepted in urbanizationrelated research studies, especially the detections related with spatial information [19, 20]

Summary

Introduction

Traditional urbanization studies are mostly based on statistic data collected by the government, which is usually lack of timeliness and accuracy and could not provide timely spatial detection of urbanization. Various remote sensing data have been applied at different scales with different research targets such as the Landsat ematic Mapper/Enhanced ematic Mapper plus (TM/ETM+), QuickBird, IKONOS, and SPOT/ High Resolution Visible (HRV) These datasets present high or medium spatial resolutions, they are less popular in long-time detection of regions with large scales due to the relatively high cost, complicated data processing procedure, and high equipment requirements. Compared with those images, the nighttime light image of Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) is more economical and is available over a larger temporal window [3, 4]. Compared with the aforementioned methods, the Sobel operator can automatically recognize and understand image features with the detected edges and is not limited by other data sources [33]

Methods

Findings

Discussion

Conclusion