4.6 Article

Long-term monitoring of citrus orchard dynamics using time-series Landsat data: a case study in southern China

期刊

INTERNATIONAL JOURNAL OF REMOTE SENSING
卷 39, 期 22, 页码 8271-8292

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/01431161.2018.1483088

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资金

  1. National Natural Science Foundation of China [41601453]
  2. Jiangxi Province Natural Science Foundation [20161BAB213078]
  3. Collaborative Innovation Center for Major Ecological Security Issues of Jiangxi Province and Monitoring Implementation [JXS-EW-00]

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Citrus orchard planting is a typical land-use change process that can impact terrestrial ecosystem services both locally and globally. Longterm monitoring of citrus orchard dynamics is critical for understanding its change patterns as well as the potential driving factors. Satellite remote-sensing imagery has been a primary data source for this purpose. However, most previous studies with multi-year intervals only captured some, but not all detailed information on citrus orchard expansion. In this study, we developed a framework for mapping annual citrus orchard extent and track its long-term dynamics in Xunwu County, China, using the historical Landsat repository from 1990 to 2016. The results suggested that the average overall accuracy of original annual mapping was 87.73%, and its performance was significantly improved after the temporal filtering approach (91.46%). Several features (e.g. elevation, slope, normalized difference vegetation index) played more important roles in citrus orchard identification. With the achieved annual mapping layers, we found a rapid citrus orchard expansion trend during the study interval (i.e. from 22.18 to 697.21 km(2)). Moreover, this expansion process was unevenly distributed in time. Spatially, emerging citrus orchards were primarily transformed from forests and croplands and mainly distributed in areas with elevations from 200 to 500 m and slopes range from 5 degrees to 20 degrees. This study demonstrated the potential of mapping citrus orchard dynamics at a higher temporal frequency with remote-sensing time-series, which can contribute to providing reference for sustainable land-use policy.

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