<abstract> <b><sc>Abstract. </sc></b>The ability to map the spatiotemporal distribution of orchards is essential in order to optimally utilize and manage their available resources. By analyzing multi-temporal characteristic and spectral features of medium-resolution images, the optimum features required to extract orchard data are determined and a classification rule set based on the object-based information analysis method (OBIA) is built. For those years in which images at key time points were missing, the extracted orchard data were used in the extraction process for these years as a thematic layer. The method was tested in Dangshan County, located in central China. Time series maps derived from the eight years of data over a nearly 20-year period from the Landsat Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-HJ-1 satellite Charge Coupled Device agree well with field samples and historical records. Among the derived maps, the accuracy of orchard data derived from the 2010 HJ-1 images was estimated at about 92.9%. Compared with the common index, NDVI, the inclusion of IOPT (index for orchard in plain terrain) in the extraction process can lead to a significant improvement. When using a single-date image, the accuracies were all less than 70.0%, and when using multi-temporal images, an accuracy of 85.7% was achieved.
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