Presentation + Paper
18 September 2018 The urbanization impact in China: a prospective model (1992-2025)
Author Affiliations +
Abstract
The gradual spread of urbanization, the phenomenon known under the term urban sprawl, has become one of the paradigms that have characterized the urban development since the second half of the twentieth century and early twenty-first century. The arrival of electrification to nearly every corner of the planet is certainly the first and more meaningful indicator of artificialization of land. In this sense, the paper proposes a new methodology designed to identify the highly impacted landscapes in China based on the analysis of the satellite image of nighttime lights.

The night-lights have been used widespread in scientific contributions, from building human development indices, identifying megalopolis [2] [3] or analyzing the phenomenon of urbanization and sprawl [4], but generally they have not been used to forecast the urbanization in the near future. This paper proposes to study the urbanization impact in China between 1992 and 2013, and models a hypothesis of future scenarios of urbanization (2013-2025). For this purpose, the paper uses DMSP-OLS Nighttime Lights (1992 – 2013). After obtaining a homogeneous series for the whole period 1992- 2013, we proceed to model the spatial dynamics of past urbanization process using the "urbanistic potential" of each of the 13.7 millions of analyzed cells. This model allows to design a probable growth of the urbanization phenomenon between 2013 and 2025 as well to predict a progressive displacement of the urbanization from east coast to mainland and west, in congruence with the current demographic models [5].
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Blanca Arellano and Josep Roca "The urbanization impact in China: a prospective model (1992-2025)", Proc. SPIE 10767, Remote Sensing and Modeling of Ecosystems for Sustainability XV, 107670A (18 September 2018); https://doi.org/10.1117/12.2321267
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Calibration

Satellites

Sensors

Data modeling

Remote sensing

Earth observing sensors

Satellite imaging

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