300206. Agricultural spatial analysis and modelling
| Title | 300206. Agricultural spatial analysis and modelling |
|---|---|
| Parent | 3002. Agriculture, land and farm management |
Latest research outputs
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A cost-effective approach to estimate plant available water capacity
Gajurel, Suman, Lai, Yunru, Lobsey, Craig and Pembleton, Keith G.. 2024. "A cost-effective approach to estimate plant available water capacity." Geoderma. 442. https://doi.org/10.1016/j.geoderma.2024.116794Article
Modelling future spatial distribution of peanut crops in Australia under climate change scenarios
Haerani, Haerani, Apan, Armando, Nguyen-Huy, Thong and Basnet, Badri. 2023. "Modelling future spatial distribution of peanut crops in Australia under climate change scenarios." Geo-spatial Information Science. https://doi.org/10.1080/10095020.2022.2155255Article
TIMESAT software for estimating crop seasonality parameter
Haerani, Haerani and Apan, Armando. 2023. "TIMESAT software for estimating crop seasonality parameter." 1st Unhas International Conference on Agricultural Technology (UICAT 2021). Makassar, Indonesia 27 - 28 Oct 2021 United States. AIP Publishing. https://doi.org/10.1063/5.0118791Paper
A global-temporal analysis on Phytophthora sojae resistance-gene efficacy
McCoy, Austin G., Belanger, Richard R., Bradley, Carl A., Cerritos-Garcia, Daniel G., Garnica, Vinicius C., Giesler, Loren J., Grijalba, Pablo E., Guillin, Eduardo, Henriquez, Maria A., Kim, Yong Min, Malvick, Dean K., Matthiesen, Rashelle L., Mideros, Santiago X., Noel, Zachary A., Robertson, Alison E., Roth, Mitchell G., Schmidt, Clarice L., Smith, Damon L., Sparks, Adam H., ..., Chilvers, Martin I.. 2023. "A global-temporal analysis on Phytophthora sojae resistance-gene efficacy." Nature Communications. 14 (1). https://doi.org/10.1038/s41467-023-41321-7Article
Assessing the biophysical factors affecting irrigation performance in rice cultivation using remote sensing derived information
Sawadogo, Alidou, Dossou-Yovo, E., Kouadio, Louis, Zwart, Sander J., Traore, Farid and Gundogdu, Kemal S.. 2023. "Assessing the biophysical factors affecting irrigation performance in rice cultivation using remote sensing derived information." Agricultural Water Management. 278, pp. 1-12. https://doi.org/10.1016/j.agwat.2022.108124Article
Field evaluation of automated site-specific irrigation for cotton and perennial ryegrass using soil-water sensors and Model Predictive Control
McCarthy, Alison, Foley, Joseph, Raedts, Pieter and Hills, James. 2023. "Field evaluation of automated site-specific irrigation for cotton and perennial ryegrass using soil-water sensors and Model Predictive Control." Agricultural Water Management. 277, pp. 1-17. https://doi.org/10.1016/j.agwat.2022.108098Article
Estimation of papaya volume and surface area using a dual ellipsoid representation and image analysis
Scarmana, Gabriel. 2022. "Estimation of papaya volume and surface area using a dual ellipsoid representation and image analysis." Staiger, Rudolf (ed.) 27th International Federation of Surveyors International Congress (FIG 2022): Volunteering for the Future – Geospatial Excellence for a Better Living. Warsaw, Poland Warsaw, Poland.Paper
Detection of calcium, magnesium, and chlorophyll variations of wheat genotypes on sodic soils using hyperspectral red edge parameters
Choudhury, Malini Roy, Christopher, Jack, Das, Sumanta, Apan, Armando, Menzies, Neal W., Chapman, Scott, Mellor, Vincent and Dang, Yash P.. 2022. "Detection of calcium, magnesium, and chlorophyll variations of wheat genotypes on sodic soils using hyperspectral red edge parameters." Environmental Technology and Innovation. 27, pp. 1-14. https://doi.org/10.1016/j.eti.2022.102469Article
Evaluation of drought tolerance of wheat genotypes in rain-fed sodic soil environments using high-resolution UAV remote sensing techniques
Das, Sumanta, Christopher, Jack, Choudhury, Malini Roy, Apan, Armando, Chapman, Scott, Menzies, Neal W. and Dang, Yash P.. 2022. "Evaluation of drought tolerance of wheat genotypes in rain-fed sodic soil environments using high-resolution UAV remote sensing techniques." Biosystems Engineering. 217, pp. 68-82. https://doi.org/10.1016/j.biosystemseng.2022.03.004Article
Northern Australia Climate Program: supporting adaptation in rangeland grazing systems through more targeted climate forecasts, improved drought information and an innovative extension program
Cobon, David, Jarvis, Chelsea, Reardon-Smith, Kate, Guillory, Laura, Pudmenzky, Christa, Nguyen-Huy, Thong, Mushtaq, Shahbaz and Stone, Roger. 2021. "Northern Australia Climate Program: supporting adaptation in rangeland grazing systems through more targeted climate forecasts, improved drought information and an innovative extension program." The Rangeland Journal. 43 (3), pp. 87-100. https://doi.org/10.1071/RJ20074Article
Queensland’s multi-year Wet and Dry periods: implications for grazing enterprises and pasture resources
McKeon, G., Stone, R., Ahrens, D., Cobon, D., Irvine, S. and Syktus, J.. 2021. "Queensland’s multi-year Wet and Dry periods: implications for grazing enterprises and pasture resources." The Rangeland Journal. 43 (3), pp. 121-142. https://doi.org/10.1071/RJ20089Article
Automated variety trial plot growth and flowering detection for maize and soybean using machine vision
McCarthy, Alison and Raine, Steven. 2022. "Automated variety trial plot growth and flowering detection for maize and soybean using machine vision." Computers and Electronics in Agriculture. 194, pp. 1-21. https://doi.org/10.1016/j.compag.2022.106727Article
Spatiotemporal Hybrid Random Forest Model for Tea Yield Prediction Using Satellite-Derived Variables
Jui, S. Janifer Jabin, Ahmed, A. A. Masrur, Bose, Aditi, Raj, Nawin, Sharma, Ekta, Soar, Jeffrey and Chowdhury, Md Wasique Islam. 2022. "Spatiotemporal Hybrid Random Forest Model for Tea Yield Prediction Using Satellite-Derived Variables." Remote Sensing. 14 (3), pp. 1-18. https://doi.org/10.3390/rs14030805Article
Automated hyperspectral vegetation index derivation using a hyperparameter optimisation framework for high-throughput plant phenotyping
Koh, Joshua C. O., Banerjee, Bikram P., Spangenberg, German and Kant, Surya. 2022. "Automated hyperspectral vegetation index derivation using a hyperparameter optimisation framework for high-throughput plant phenotyping." New Phytologist. 233 (6), pp. 2659-2670. https://doi.org/10.1111/nph.17947Article
Roots’ Drought Adaptive Traits in Crop Improvement
Shoaib, Mirza, Banerjee, Bikram P., Hayden, Matthew and Kant, Surya. 2022. "Roots’ Drought Adaptive Traits in Crop Improvement." Plants. 11 (17). https://doi.org/10.3390/plants11172256Article
Estimating early season growth and biomass of field pea for selection of divergent ideotypes using proximal sensing
Tefera, Abeya Temesgen, Banerjee, Bikram Pratap, Pandey, Babu Ram, James, Laura, Puri, Ramesh Raj, Cooray, Onella, Marsh, Jasmine, Richards, Mark, Kant, Surya, Fitzgerald, Glenn J. and Cooray, Onella. 2022. "Estimating early season growth and biomass of field pea for selection of divergent ideotypes using proximal sensing." Field Crops Research. 277. https://doi.org/10.1016/j.fcr.2021.108407Article
Infield sensing of cotton insects using automated image analysis of crop symptoms: CSP2203
Heimoana, Simone, Blankley, S. and McCarthy, Alison. 2022. Infield sensing of cotton insects using automated image analysis of crop symptoms: CSP2203. Australia. Cotton Research and Development Corporation.Technical report
Automated infield canopy temperature assessment of early stage cotton using thermal camera and plant segmentation
McCarthy, Alison, Nunn, Christopher, Jamali, Hizbullah and Long, Derek. 2022. Automated infield canopy temperature assessment of early stage cotton using thermal camera and plant segmentation . Australia. Cotton Research and Development Corporation.Technical report
Cotton health assessment and yield prediction
McCarthy, Alison and Baillie, Craig. 2022. Cotton health assessment and yield prediction. United States. John Deere.Technical report
Future Farm: Improving farmer confidence in targeted N management through automated sensing and decision support
Bramley, Rob, Whelan, Brett, Colaco, André, McCarthy, Alison, Richetti, Jonathan, Lawes, Roger, Fajardo, Mario, Bender, Asher, Pothula, Anand, Baillie, Craig, Perry, Eileen, Fitzgerald, Glenn, Clancy, Alex, Leo, Stephen and Grace, Peter. 2022. Future Farm: Improving farmer confidence in targeted N management through automated sensing and decision support. Australia. Grains Research and Development Corporation.Technical report
Screening two biodegradable polymers in enhanced efficiency fertiliser formulations reveals the need to prioritise performance goals
Redding, M.R., Witt, T., Lobsey, C.R., Mayer, D.G., Hunter, B., Pratt, S., Robinson, N., Schmidt, S., Laycock, B. and Phillips, I.. 2022. "Screening two biodegradable polymers in enhanced efficiency fertiliser formulations reveals the need to prioritise performance goals." Journal of Environmental Management. 304. https://doi.org/10.1016/j.jenvman.2021.114264Article
Improving estimation of in-season crop water use and health of wheat genotypes on sodic soils using spatial interpolation techniques and multi-component metrics
Choudhury, Malini Roy, Mellor, Vincent, Das, Sumanta, Christopher, Jack, Apan, Armando, Menzies, Neal W., Chapman, Scott and Dang, Yash P.. 2021. "Improving estimation of in-season crop water use and health of wheat genotypes on sodic soils using spatial interpolation techniques and multi-component metrics." Agricultural Water Management. 255. https://doi.org/10.1016/j.agwat.2021.107007Article
Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learning
Das, Sumanta, Christopher, Jack, Apan, Armando, Choudhury, Malini Roy, Chapman, Scott, Menzies, Neal W. and Dang, Yash P.. 2021. "Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learning." Agricultural and Forest Meteorology. 307. https://doi.org/10.1016/j.agrformet.2021.108477Article
UAV-thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil
Das, Sumanta, Christopher, Jack, Apan, Armando, Choudhury, Malini Roy, Chapman, Scott, Menzies, Neal W. and Dang, Yash P.. 2021. "UAV-thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil." ISPRS Journal of Photogrammetry and Remote Sensing. 173, pp. 221-237. https://doi.org/10.1016/j.isprsjprs.2021.01.014Article
Statistical comparison of additive regression tree methods on ecological grassland data
Plant, Emily, King, Rachel and Kath, Jarrod. 2021. "Statistical comparison of additive regression tree methods on ecological grassland data." Ecological Informatics. 61, pp. 1-23. https://doi.org/10.1016/j.ecoinf.2020.101198Article
An empirical model for prediction of wheat yield, using time-integrated Landsat NDVI
Lai, Y. R., Pringle, M. J., Kopittke, P. M., Menzies, N. W., Orton, T. G. and Dang, Y. P.. 2018. "An empirical model for prediction of wheat yield, using time-integrated Landsat NDVI." International Journal of Applied Earth Observation and Geoinformation. 72, pp. 99-108. https://doi.org/10.1016/j.jag.2018.07.013Article
Multispectral remote sensing as a tool to support organic crop certification: assessment of the discrimination level between organic and conventional maize
Denis, Antoine, Desclee, Baudouin, Migdall, Silke, Hansen, Herbert, Bach, Heike, Ott, Pierre, Kouadio, Amani Louis and Tychon, Bernard. 2020. "Multispectral remote sensing as a tool to support organic crop certification: assessment of the discrimination level between organic and conventional maize." Remote Sensing. 13 (1). https://doi.org/10.3390/rs13010117Article
Mapping rice area and yield in northeastern asia by incorporating a crop model with dense vegetation index profiles from a geostationary satellite
Yeom, Jong-Min, Jeong, Seungtaek, Deo, Ravinesh C. and Ko, Jonghan. 2021. "Mapping rice area and yield in northeastern asia by incorporating a crop model with dense vegetation index profiles from a geostationary satellite." GIScience and Remote Sensing. https://doi.org/10.1080/15481603.2020.1853352Article
Machine Learning Regression Analysis for Estimation of Crop Emergence Using Multispectral UAV Imagery
Banerjee, Bikram P., Sharma, Vikas, Spangenberg, German and Kant, Surya. 2021. "Machine Learning Regression Analysis for Estimation of Crop Emergence Using Multispectral UAV Imagery." Remote Sensing. 13 (15). https://doi.org/10.3390/rs13152918Article
New sensing technologies for citrus gall wasp and Fuller’s rose weevil: CT19009
Long, Derek, McCarthy, Alison and Mo, Jianhua. 2021. New sensing technologies for citrus gall wasp and Fuller’s rose weevil: CT19009. Australia. Hort Innovation Austarlia.Technical report
A Bayesian approach toward the use of qualitative information to inform on-farm decision making: The example of soil compaction
Roberton S.D., Lobsey, C.R. and Bennett, J.McL.. 2021. "A Bayesian approach toward the use of qualitative information to inform on-farm decision making: The example of soil compaction ." Geoderma. 382. https://doi.org/10.1016/j.geoderma.2020.114705Article
Characterizing net primary productivity of forests and non-forest areas in the Philippines using satellite imagery
Apan, Armando and Maraseni, Tek. 2012. "Characterizing net primary productivity of forests and non-forest areas in the Philippines using satellite imagery." 1st National Symposium and Workshop on Environmental Science (IESM 2012): Environmental Science in a Changing Environment. Manila, Philippines 07 - 08 May 2012 Manila, Philippines.Presentation
The climate-induced alteration of future geographic distribution of aflatoxin in peanut crops and its adaptation options
Haerani, Haerani, Apan, Armando and Basnet, Badri. 2020. "The climate-induced alteration of future geographic distribution of aflatoxin in peanut crops and its adaptation options." Mitigation and Adaptation Strategies for Global Change. 25 (6), pp. 1149-1175. https://doi.org/10.1007/s11027-020-09927-0Article
Remote sensing of peanut cropping areas and modelling of their future geographic distribution and disease risks
Haerani, Haerani. 2019. Remote sensing of peanut cropping areas and modelling of their future geographic distribution and disease risks. PhD Thesis Doctor of Philosophy. University of Southern Queensland.PhD Thesis
System Identification of Linearized Rice Growth Dynamic for Precision Irrigation
Cabrera, John Audie, Radanielson, Ando Mariot and Pedrasa, Jhoanna Rhodette. 2019. "System Identification of Linearized Rice Growth Dynamic for Precision Irrigation." International Tropical Agriculture Conference 2019 (TropAg 2019). Brisbane, Australia 11 - 13 Nov 2019 Basel, Switzerland. https://doi.org/10.3390/proceedings2019036031Poster
Machine vision and automation technologies for the Australian cotton industry
McCarthy, Alison. 2019. "Machine vision and automation technologies for the Australian cotton industry." 78th International Cotton Advisory Committee Plenary Meeting (ICAC 2019). Brisbane, Australia 02 - 07 Dec 2019Presentation
Spatiotemporal assessment of irrigation performance of the Kou Valley irrigation scheme in Burkina Faso using satellite remote sensing-derived indicators
Sawadogo, Alidou, Kouadio, Louis, Traore, Farid, Zwart, Sander J., Hessels, Tim and Gundogdu, Kemal S.. 2020. "Spatiotemporal assessment of irrigation performance of the Kou Valley irrigation scheme in Burkina Faso using satellite remote sensing-derived indicators." ISPRS International Journal of Geo-Information. 9 (8), pp. 1-23. https://doi.org/10.3390/ijgi9080484Article
Climatology and Variability of the Evaporative Stress Index and its suitability as a tool to monitor Australian drought
Nguyen, Hanh, Otkin, Jason A., Wheeler, Matthew C., Hope, Pandora, Trewin, Blair and Pudmenzky, Christa. 2020. "Climatology and Variability of the Evaporative Stress Index and its suitability as a tool to monitor Australian drought." Journal of Hydrometeorology. 21 (10), pp. 2309-2324. https://doi.org/10.1175/JHM-D-20-0042.1Article
In-season yield prediction using VARIwise
McCarthy, Alison, O'Keeffe, Kieran and McKay, Andrew. 2019. "In-season yield prediction using VARIwise." Australian Association of Cotton Scientists 2019 Australian Cotton Research Conference (AACS 2019). Armidale, Australia 28 - 30 Oct 2019Keynote
Monitoring rice growth status in the Mekong Delta, Vietnam using multitemporal Sentinel-1 data
Phung, Hoang-Phi, Lam-Dao, Nguyen, Nguyen-Huy, Thong, Le-Toan, Thuy and Apan, Armando A.. 2020. "Monitoring rice growth status in the Mekong Delta, Vietnam using multitemporal Sentinel-1 data." Journal of Applied Remote Sensing. 14 (1), pp. 014518-1-014518-23. https://doi.org/10.1117/1.JRS.14.014518Article