Mr. Xiaoping Song Profile

Xiaoping Song

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Publications (3)

Proceedings Article | 3 June 2024 Paper

Mapping the suitable areas for future urbanization in Jiangxi, China

Ming Zhang, Weicheng Wu, Yaoyao Zhu, Sicheng Li, Aohui Li, Xiaoping Song, Lihua Gong, Zhenhao Xu

Proceedings Volume 13170, 131700Z (2024) https://doi.org/10.1117/12.3032271

KEYWORDS: Modeling, Machine learning, Algorithm development, Random forests, Reliability, Geographic information systems, Decision trees, Data modeling, Artificial neural networks, Statistical modeling

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Proceedings Article | 3 June 2024 Paper

A new radar vegetation index for research in the dry areas

Wenjing Li, Weicheng Wu, Zhenhao Xu, Sicheng Li, Aohui Li, Xiaoping Song, Lihua Gong, Yaoyao Zhu

Proceedings Volume 13170, 131700H (2024) https://doi.org/10.1117/12.3032225

KEYWORDS: Vegetation, Radar, Land cover, Synthetic aperture radar, Scattering, Remote sensing, Crop monitoring, Calibration, Biomass, Biological research

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Proceedings Article | 3 June 2024 Paper

Remote sensing-based multi-scenario land use change simulation in Hefei, China

Yecheng He, Weicheng Wu, Xinyuan Xie, Aohui Li, Xiaoping Song, Sicheng Li, Zhenhao Xu, Yaoyao Zhu, Lihua Gong

Proceedings Volume 13170, 131700I (2024) https://doi.org/10.1117/12.3032202

KEYWORDS: Data modeling, Sustainability, Matrices, Remote sensing, Image classification, Vegetation, Systems modeling, Landsat, Atmospheric modeling, Roads

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Land use change detection by remote sensing (RS) and simulation-based prediction may provide support to rational spatial planning of territory, which is of great significance to ensure sustainable land management. For this purpose, this paper employed multitemporal Landsat images dated 2010, 2015 and 2020 and county-level socioeconomic data for achieving such an integrated study taking Hefei city as an example. After atmospheric correction using the COST (Cosine Theta) model, the maximum likelihood approach and post-classification differencing were applied respectively to classify the images and to reveal the land use changes. The Logistic-Multi-Criteria Evaluation-Celluar Automata-Markov (LMCM) hybrid model was harnessed to simulate the land use pattern of 2025 under four different scenarios namely business as usual (BAU), ecological protection (EP), economic development (ED) and sustainable development (SD). The results show that (1) during the period 2010-2020, the built-up areas increased by 804.69 km² and the croplands decreased by 568.14 km²; (2) There seems to be a big difference between the predicted croplands and built-up areas in the four scenarios in 2025. Under the EP scenario, the built-up areas may likely gain an increase of 244.27 km², indicating that the environment shall be protected but the urbanization will be also limited. Under the ED scenario, the built-up areas may be extended by 829.54 km² and the croplands and forests are likely to decline significantly in 2025, meaning that overemphasizing urban development would not only threaten food security, but also bring harm to the local ecosystem. Under the SD scenario, the increase of built-up areas and the reduction of croplands would both come between the other scenarios, and the land use structure seems more stable and rational. Clearly, the SD scenario is the potential pathway for sustainable land use management in the long run. These results may provide the local governments with reference for their decision-making to conduct sustainable land use and urban planning.

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