Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling.

By Qihao Weng. Journal of Environmental Management, 2002

891 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/889a77e73e09c3af852f913c9bc16e8ab3f09927

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. Giles M. Foody
2. Mengistie Kindu
3. Yehua Dennis Wei
4. Dengsheng Lu
5. Ting Bai
6. Thomas Knoke
7. Deren Li
8. Jun Luo

In Global and Planetary Change

1. Yehua Dennis Wei
2. Hualou Long
3. Xinyue Ye
4. Giles M. Foody
5. Dengsheng Lu
6. Ting Bai
7. Thomas Knoke
8. Deren Li

Citations in the corpus

• Socio-economic development and land-use change: Analysis of rural housing land transition in the Transect of the Yangtse River, China (2007, background): “E-mail address: longhl@igsnrr.ac.cn (H. Long). urban sprawl (Weng, 2002; Tan et al., 2005), the transformation of arable land into rural housing land has found much less attention.”
• Change detection techniques (2004, methodology): “2000, Petit and Lambin 2001, Chen 2002, Weng 2002), especially when the change detection involved long period intervals associated with different data sources, formats and accuracies or multi-scale land-cover change analysis (Petit and Lambin 2001).”
• Modeling spatial variations of urban growth patterns in Chinese cities: The case of Nanjing (2009, positive): “By using spatial modeling, GIS and remote sensing technologies, a lot of works have been done to understand the patterns, mechanisms and effects of urban growth in China (e.g. Li, 1998; Schneider et al., 2005; Sui and Zeng, 2001; Weng, 2002; Wu and Yeh, 1997; Xie et al., 2005; Yeh and Li, 1998, 1999”
• Assessing the accuracy of land cover change with imperfect ground reference data (2010, background): “Here, a key feature is that a common objective is to map the land cover to a target accuracy of ~85% (Weng, 2002; Yang and Lo, 2002; Rogan et al., 2003; Treitz and Rogan, 2004; Yang and Liu, 2005; Mundia and Aniya, 2005).”
• Harshness in image classification accuracy assessment (2008, background): “…sometimes stated without apparent need for justification or provision of supporting evidence from the literature, and it is essentially seen by many as a universal standard for thematic mapping in remote sensing (e.g. Fisher and Langford 1996, Weng 2002, Rogan et al. 2003, Bektas and Goksel 2004).”
• Land Use/Land Cover Change Analysis Using Object-Based Classification Approach in Munessa-Shashemene Landscape of the Ethiopian Highlands (2013, background): “However, the magnitude of LULC change differs with the time period being examined [9], geographical location [10], slope gradient, and elevation range [11,12].”
• Urbanization, urban land expansion and environmental change in China (2014, background): “The use of GIS and remote sensing to detect heat-island effects as an indicator of growth in the built environments of China is more easily observed (Weng 2002).”
• Deep learning for change detection in remote sensing: a review (2022, methodology): “It provides a means to study land use/ cover change (Weng 2002), biodiversity (Newbold et al. 2015), the urbanization process (Han et al. 2017a), disaster detection (Saito et al. 2004), and other environmental changes.”