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We have provided here automated cropland classification algorithm (ACCA) model (Figure 1) for Australia along with sample: (a) MODIS 250-m time-series data used to produce it, (b) cropland masks, and (c) output cropland product (Figure 2), and a readme file. User’s can download the ACCA algorithm (Figure 1, in .gmd format downloadable link below) that is in ERDAS Imagine modeler compatible format (.gmd file) and run using the MODIS 250-m time- series data and re-produce the output (Figure 2).
Pardhasaradhi Teluguntla 1,2 (firstname.lastname@example.org) and Prasad S. Thenkabail 1 (email@example.com)
1 = U.S. Geological Survey, 2 = Bay Area Environmental Research Institute
Details of the process is provided in the readme file. So, please download the readme file first and then follow the detailed procedure.
ACCA algorithm of Australia can be used to re-produce the cropland products of Australia year after year using MODIS 250-m time-series data for the corresponding year. Thereby, ACCA algorithm has the ability to reproduce cropland products of the past years (hind-cast), present year (now-cast), and future years (future-cast) as we report in the paper.
The automated cropland classification algorithm (ACCA) is written in ERDAS Modeler, and hence the algorithm file is available in .gmd format.