Spatial-Temporal Pattern and Driving Forces of Land Use Changes in Xiamen1
REFERENCES (35)
- et al.
Planning and design for eco-sustainable farmland consolidation
Pedosphere
(2005) - et al.
- et al.
Development of an agricultural land evaluation and site assessment (LESA) decision support tool using remote sensing and geographic information system
Journal of soil and water conservation
(2005) - et al.
Regional land use/cover information processing
Resources Science (in Chinese)
(2002) - et al.
Analysis of LUCC pattern of physical region in NSTEC
Progress in Earth Sciences (in Chinese)
(2002) - et al.
The spatial-temporal pattern and driving forces of land use change in the Jianghan Plain during 1990–2000
Geographical Research (in Chinese)
(2003) - et al.
A study on the spatial-temporal dynamic changes of land-use and driving forces analysis of China in the 1990s
Geographical Research (in Chinese)
(2003) - et al.
The study on land use and land cover change in China through RS
- et al.
Study on spatial-temporal feature of modern land use change in China: Using remote sensing techniques
Quaternary Sciences (in Chinese)
(2000)
A spatial analysis model for measuring the rate of land use change
Journal of Natural Resources (in Chinese)
Progress of study on land use and land cover change
Journal of Apply Foundation and Engineering (in Chinese)
Agricultural intensification and ecosystem properties
Science
Land-use/land-cover change: Challenges for geographers
GeoJournal
Characteristics and regulation mechanism of moisture in dryland of lateritic red soil in Fujian Province
Soils (in Chinese)
Analysis of moisture properties and nutrient status of dryland soil and their influencing factors in Fujian Province
Journal of Jimei University (Natural Science) (in Chinese)
Water problem of lateritic red soil and its management
Soils (in Chinese)
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2021, Sustainable Cities and SocietyCitation Excerpt :Over time, the land use land cover (LULC) map plays a crucial role by providing essential information about landscape transformation and environmental impacts (Mallick & Rudra, 2021b). Therefore, the research on land-use change has become a mainstream subject of urban planning, global environmental change, and sustainable development, which was initiated by the International Geosphere-Biosphere Project (IGBP) and International Human Dimension Program (IHDP) as land use land cover change (LULCC) in 1995 (Quan et al., 2006; Maity et al., 2020a). The major transformation of land has found in the conversion of wasteland to a built-up area, agricultural land to fallow land, and forest cover to agricultural land, etc. (Pramanik, 2017; Mondal et al., 2017; Mondal et al., 2020).
Research on the interactive relationship and the optimal adaptation degree between land use benefit and industrial structure evolution: A practical analysis of Jiangsu province
2021, Journal of Cleaner ProductionCitation Excerpt :Thirdly, the key point of the research is the result and reason of the impact of industrial development on LUB. The optimization of industrial structure improves the degree of land use intensification (Dong et al., 2020; Fischer and Sun, 2001; Quan et al., 2006), and the LUB improves with the industrial development (Lu et al., 2020a, 2020b; Peng et al., 2016). Industrial transfer and industrial agglomeration bring external economies of scale, which can improve LUB to varying degrees (Chen et al., 2018b; Zhou et al., 2019).
Agricultural land fragmentation analysis in a peri-urban context: From the past into the future
2019, Ecological IndicatorsCitation Excerpt :Agricultural land fragmentation (AF) is the result of complex interactions between a diverse set of driving forces, including ecological (Bentley, 1987), economic and population growth (Cheng et al., 2015), landscape protection (Bürgi et al., 2017; Eiter and Potthoff, 2007; Plieninger et al., 2016), urbanization (Quan et al., 2006), transport infrastructures (Irwin et al., 2007; Torrens and Alberti, 2000), climate change (Oliver et al., 2015), and agricultural policies (e.g., European Common Agricultural Policy, and the European Union's rural development policy – 2014–2020).
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Project supported by the Fujian Provincial Natural Science Foundation of China (No. D0210010).