To investigate the effect of arable land protection policies in China, a practical framework that integrates geographic information systems (GIS), soil quality assessment and landscape metrics analysis was employed to track and analyze arable land transformations and landscape changes in response to rampant urbanization within the Ningbo region (China) from 2005 to 2013. The results showed that arable land loss and degradation have continued, despite the development of a comprehensive legal framework for arable land protection. The implementation of arable land protection policies is judged to be effective, but not entirely successful, because it guarantees the overall amount of arable land but does not consider soil quality and spatial distribution. In addition, there are distinct variations in arable land change dynamics between two temporal intervals. From 2005–2009, the transformation of arable land was diversified, with intensified conversion among arable land, built-up land, water and orchards. Moreover, many new arable land parcels were adjacent to built-up land, and are in danger of being occupied again through urban sprawl. By 2009–2013, most of the arable land was occupied by urban expansion, whereas a majority of newly increased arable land was reclaimed from coastal tideland. Although the newly increased arable land was contiguous and far from the urban area, it is of poor quality and has limited use. The permanent loss of high-quality arable land due to intensified urban sprawl may threaten sustainable development and food security on a larger scale.
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Δευτέρα 16 Μαΐου 2016
IJGI, Vol. 5, Pages 69: Assessment on the Impact of Arable Land Protection Policies in a Rapidly Developing Region
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Αλέξανδρος Γ. Σφακιανάκης Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,0030693260717...
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heory of COVID-19 pathogenesis Publication date: November 2020Source: Medical Hypotheses, Volume 144Author(s): Yuichiro J. Suzuki ScienceD...
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Alimentary Pharmacology &Therapeutics, EarlyView. https://ift.tt/2qECBIJ
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