Cong OU, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China
Greenhouse-led farmland (GF) is one of the fastest-growing technocentric agricultural production sectors worldwide, offering a micro-scale environment to counteract unfavorable natural conditions for crops. It plays an essential role in food production, resource conservation and the rural economy, but has also caused environmental and socio-economic problems due to policy promotion and market demand. However, the spatiotemporal characteristics and driving mechanisms of GF over a long-term period were poorly understood. In this study, long-term annual remote sensing-based and statistical data were used to investigate the spatiotemporal dynamics of GF and its drivers in Shandong (SD) province, China from 1989 to 2018. The results showed that: GF in SD over the past 30 years was toward continuous clustering and has a positive synergistic relationship with the change of its total area on both regional and city scales. GF with a cumulative duration of more than 15 years and a demolition frequency of less than 0.2 were mainly distributed in northwestern Weifang, southwestern Linyi and western of Liaocheng. The expansion trajectory of GF roughly formed a circular expansion pattern around the central mountainous area and showed significant differences under different spatial gradients around the rural settlements. Budget expenditure for rural development, local retail sales and average earnings of local farmers were the most important local driving factors of the GF expansion in SD. In terms of the external driven mechanism, we also found that vegetable production in Guangxi, Hainan, Hunan as well as Hubei province and vegetable demand in Beijing were a one-way Granger causality of the development of GF in SD. These findings can enhance the comprehensive understanding of this typical component of “human-nature” interaction and support the sustainable development of regional agriculture.
Mots clés : Greenhouse-led farmland|Spatiotemporal dynamics|Driven mechanism|Long-term period|Shandong province
A104594CO