Mapping the annual dynamics of cultivated land in typical area of the Middle-lower Yangtze plain using long time-series of Landsat images based on Google Earth Engine

Jin, Y., Liu, X., Yao, J. , Zhang, X. and Zhang, H. (2020) Mapping the annual dynamics of cultivated land in typical area of the Middle-lower Yangtze plain using long time-series of Landsat images based on Google Earth Engine. International Journal of Remote Sensing, 41(4), pp. 1625-1644. (doi: 10.1080/01431161.2019.1673917)

Abstract

Cultivated land in Middle-lower Yangtze Plain has been greatly reduced over the last few decades due to rapid urban expansion and massive urban construction. Accurate and timely monitoring of cultivated land changes has significant for regional food security and the impact of national land policy on cultivated land dynamics. However, generating high-resolution spatial-temporal records of cultivated land dynamics in complex areas remains difficult due to the limitations of computing resources and the diversity of land cover over a complex region. In our study, the annual dynamics of cultivated land in Middle-lower Yangtze Plain were first produced at 30 m resolution with a one-year interval in 1990–2010.Changes of vegetation and cultivated land are examined with the breakpoints inter-annual Normalized Difference Vegetation Index (NDVI) trajectories and synthetic NDVI derived by the enhanced spatial and temporal adaptive reflectance fusion model (ESTRAFM), respectively. Last, cultivated land dynamics is extracted with a one-year interval by detecting phenological characteristic. The results indicate that the rate of reduction in cultivated land area has accelerated over the past two decades, and has intensified since 1997.The dynamics of cultivated land mainly occurred in the mountains, hills, lakes and around towns, and the change frequency of these area was mainly one or two times. In particular, the changes in cultivated land in Nanjing have been most intense, perhaps attributed to urban greening and infrastructure construction.

• Item Type: Articles
• Additional Information: This research was supported by the National Key R&D Program of China (Grant No. 2017YFA0604401, 2017YFA0604402 and 2017YFA0604404), the National Natural Science Foundation of China (Grant No. 41601420). The authors are grateful to Xinchang Zhang, Ziyu Lin, who had assisted or advised them during various stages of this work
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Yao, Dr Jing
• Authors: Jin, Y., Liu, X., Yao, J., Zhang, X., and Zhang, H.
• Subjects: G Geography. Anthropology. Recreation > G Geography (General); G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
• College/School: College of Social Sciences > School of Social and Political Sciences > Urban Studies
• Journal Name: International Journal of Remote Sensing
• Publisher: Taylor & Francis
• ISSN: 0143-1161
• ISSN (Online): 1366-5901
• Published Online: 04 October 2019
• Copyright Holders: Copyright © 2019 Taylor and Francis
• First Published: First published in International Journal of Remote Sensing 41(4): 1625-1644
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher