Research output per year
Research output per year
Personal profile
Personal profile
Currently Involved in research at Charles Sturt University.
Education/Academic qualification
Agricultural Science, Bachelor (Hons), The University of Sydney
2015 → 2018
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Dive into the research topics where Allister Clarke is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Analysis and forecasting of Australian rice yield using phenology-based aggregation of satellite and weather data
Brinkhoff, J., Clarke, A., Dunn, B. W. & Groat, M., 15 Jun 2024, In: Agricultural and Forest Meteorology. 353, 19 p., 110055.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Citations (Scopus)4 Downloads (Pure) -
Combined location online weather data: easy-to-use targeted weather analysis for agriculture
Yates, D., Blanchard, C., Clarke, A., Rehman, S. U., Islam, M. Z., Ford, R. & Walsh, R., Sept 2024, In: Climatic Change. 177, 9, 19 p., 138.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Downloads (Pure) -
Integrating climate and satellite data for multi-temporal pre-harvest prediction of head rice yield in Australia
Clarke, A., Yates, D., Blanchard, C., Islam, M. Z., Ford, R., Rehman, S. U. & Walsh, R. P., May 2024, In: Remote Sensing. 16, 10, p. 1-20 20 p., 1815.Research output: Contribution to journal › Article › peer-review
Open AccessFile2 Downloads (Pure) -
The effect of dataset construction and data pre-processing on the eXtreme Gradient Boosting algorithm applied to head rice yield prediction in Australia
Clarke, A., Yates, D., Blanchard, C., Islam, M. Z., Ford, R., Rehman, S. & Walsh, R., Apr 2024, In: Computers and Electronics in Agriculture. 219, p. 1-15 15 p., 108716.Research output: Contribution to journal › Article › peer-review
Open AccessFile8 Citations (Scopus)71 Downloads (Pure) -
Combining climate, soil and satellite-derived variables with interpretive machine learning to predict head rice yield
Clarke, A., Blanchard, C., Islam, Z., Yates, D. & Rehman, S., Aug 2022.Research output: Other contribution to conference › Presentation only
Press/Media
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Harnessing data and artificial intelligence to benefit rice industry
21/03/22
1 Media contribution
Press/Media: Press / Media