A spatiotemporal structural graph for characterizing land cover changes

ABSTRACT

Characterizing landscape patterns and revealing their underlying processes are critical for studying climate change and environmental problems. Previous methods for mapping land cover changes largely focused on the classification of remote sensing images. Therefore, they could not provide information about the evolutionary process of land cover changes. In this paper, we developed a spatiotemporal structural graph (STSG) technique for a comprehensive analysis of land cover changes. First, a land cover neighborhood graph was generated for each snapshot to quantify the spatial relationship between adjacent land cover objects. Then, an object-based temporal tracking algorithm was designed to monitor the temporal changes between land cover objects over time. Finally, land cover evolutionary trajectories, pixel-level land cover change trajectories, and node-wise connectivity changes over time were characterized. We applied the proposed method to analyze land cover changes in Suffolk County, New York from 1996 to 2010. The results demonstrated that STSG can not only characterize and visualize detailed land cover changes spatially but also maintain the temporal sequence and relations of land cover objects in an integrated space-time environment. The proposed STSG provides a useful framework for analyzing land cover changes and can be adapted to characterize and quantify other spatiotemporal phenomena.

KEYWORDS:

• Graph-based
• land cover objects
• evolutionary trajectories
• spatiotemporal relations
• land cover changes

Acknowledgments

We are grateful to the three anonymous referees for their valuable comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data and code availability statement

The data and codes that support the findings of this study are available with a DOI at http://doi.10.6084/m9.figshare.9765377.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (No. 41871331), the Shanghai Sailing Program (No.19YF1413800), and the China Postdoctoral Science Foundation (No. 2018M641961)

Notes on contributors

Bin Wu

Bin Wu is a postdoc researcher with the Key Laboratory of Geographic Information Science (Ministry of Education) and the School of Geographic Sciences, East China Normal University, Shanghai, China. He obtained his PhD in cartography and geographic information systems in 2018 from the same university. His fields of interests are urban remote sensing, LiDAR, and spatio-temporal analysis.

Bailang Yu

Bailang Yu received the B.S. and Ph.D. degrees in cartography and geographic information systems from East China Normal University, Shanghai, China, in 2002 and 2009, respectively. He is currently a Professor with the Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, where he is also with the School of Geographic Sciences. His research interests include urban remote sensing, nighttime light remote sensing, LiDAR, and object-based methods.

Song Shu

Song Shu is an Assistant Professor in the Department of Geography and Planning at Appalachian State University. His research interests are in remote sensing applications applied to Arctic snow, lake hydrology, water resources, cryospheric processes, and global climate change.Qiusheng Wu is an Assistant Professor in the Department of Geography at University of Tennessee. His research interests focus on Geographic Information Science (GIS), remote sensing, and environmental modeling.

Yi Zhao

Yi Zhao is a PhD candidate in the School of Geographic Sciences at East China Normal University, Shanghai, China. His interested research fields contain LiDAR, urban remote sensing, and development of GIS.

Jianping Wu

Jianping Wu received the M.S. degree from Peking University, Beijing, China, in 1986, and the PhD degree from East China Normal University, Shanghai, China, in 1996. He is currently a Professor with East China Normal University. His research interests include remote sensing and geographic information system.