Monitoring and predicting land use change in Beijing using remote sensing and GIS

By Qiong Wu, Hongqing Li, Rusong Wang, J. Paulussen, Yong He, Min Wang, Bi-hui Wang, Zhen Wang. 2006

405 citations recorded by the source corpus.

Rapid land use change has taken place in many mega cities of China such as Beijing over the past two decades. In this paper, land use change dynamics were investigated by the combined use of satellite remote sensing, geographic information systems (GIS). The results indicated that there had been a notable and uneven urban growth and a major loss of cropland loss between 1986 and 2001. Most of the urban growth and loss of agriculture land occurred in inner and outer suburbs. Land use change was projected for the next 20 years using Markov chains and regression analyses. The further integration of remote sensing and GIS technologies with Markov model and regression model was found to be useful for describing, analyzing and predicting the process of land use change.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/db4a12ec96e93ee1a511788e3c671875d78313d6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Vipin Kumar
2. Yehua Dennis Wei
3. Jun Luo
4. Xiaowei Jia
5. Xinyue Ye

In Global and Planetary Change

1. Yehua Dennis Wei
2. Xinyue Ye
3. Vipin Kumar
4. Huiran Han
5. Chengfeng Yang
6. Jun Luo
7. Xiaowei Jia
8. Jinping Song

Citations in the corpus

• Modeling spatial variations of urban growth patterns in Chinese cities: The case of Nanjing (2009, positive): “Various models have been developed to analyze and simulate urban growth patterns (e.g., Arai and Akiyama, 2004; Clarke et al., 1997; Landis and Zhang, 1998), including in the context of China (Chen et al., 2002; Cheng and Masser, 2003a; Liu and Zhou, 2005; Xiao et al., 2006; Wu et al., 2006).”
• Predict Land Covers with Transition Modeling and Incremental Learning (2017, background): “Conventional machine learning models have been widely explored in a variety of land cover prediction problems [7, 22].”
• Urbanization, urban land expansion and environmental change in China (2014, background): “…such as the YRD (e.g., Xie et al. 2005; Luo and Wei 2009; Yue et al. 2010), the Pearl River Delta (e.g., Yeh and Li 1998; Weng 2002), and Beijing (e.g., Wu et al. 2006), and more recently, major interior cities such as Wuhan (e.g., Cheng and Masser 2003) and Chengdu (e.g., Schneider et al. 2005 ).”
• Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China (2015, methodology): “The model has been widely used to predict LULC change [33].”