Items where Subject is "Remote sensing"
Number of items at this level: 18. ArticleAkbarian, S., Xu, C.-Y., Wang, W., Ginns, S. P. and Lim, S. (2022) Sugarcane yields prediction at the row level using a novel cross-validation approach to multi-year multispectral images. Computers and Electronics in Agriculture, 190 , 107024. Anderson, N. T., Walsh, K. B., Koirala, A., Wang, Z., Amaral, M. H., Dickinson, G. R., Sinha, P. and Robson, A. J. (2021) Estimation of Fruit Load in Australian Mango Orchards Using Machine Vision. Agronomy, 11 (9). p. 1711. ISSN 2073-4395 Beutel, T. S., Shepherd, R., Karfs, R. A., Abbott, B. N., Eyre, T., Hall, T. J. and Barbi, E. (2021) Is ground cover a useful indicator of grazing land condition? The Rangeland Journal, 43 (1). pp. 55-64. Fitzgerald, G.J., Rodriguez, D., Christensen, L.K., Belford, R., Sadras, V.O. and Clarke, T.R. (2006) Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments. Precision Agriculture, 7 (4). pp. 233-248. Fitzgerald, G.J., Rodriguez, D. and O'Leary, G. (2010) Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI). Field Crops Research, 116 (3). pp. 318-324. Jensen, T., Apan, A., Young, F. and Zeller, L. (2007) Detecting the attributes of a wheat crop using digital imagery acquired from a low-altitude platform. Computers and Electronics in Agriculture, 59 (1-2). pp. 66-77. Potgieter, A.B., Apan, A., Dunn, P. and Hammer, G. (2007) Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery. Australian Journal of Agricultural Research, 58 (4). pp. 316-325. Pringle, M. J., O'Reagain, P. J., Stone, G. S., Carter, J. O., Orton, T. G. and Bushell, J. J. (2021) Using remote sensing to forecast forage quality for cattle in the dry savannas of northeast Australia. Ecological Indicators, 133 . p. 108426. ISSN 1470-160X Roboson, A. and Medway, J. (2009) Remote sensing applications for cotton. Australian Cottongrower, 30 (4). pp. 40-43. Rodriguez, D., Fitzgerald, G.J., Belford, R. and Christensen, L.K. (2006) Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-physiological concepts. Australian Journal of Agricultural Research, 57 (7). pp. 781-789. Tilling, A.K., O'Leary, G.J., Ferwerda, J.G., Jones, S.D., Fitzgerald, G.J., Rodriguez, D. and Belford, R. (2007) Remote sensing of nitrogen and water stress in wheat. Field Crops Research, 104 (1-3). pp. 77-85. Xie, Z., Phinn, S. R., Game, E. T., Pannell, D. J., Hobbs, R. J., Briggs, P. R., Beutel, T. S., Holloway, C. and McDonald-Madden, E. (2020) Corrigendum to “Using Landsat observations (1988–2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation” [Remote Sens. Environ. 232 (2019), 111317]. Remote Sensing of Environment, 241 . p. 111737. ISSN 0034-4257 Zhao, Y., Zheng, B., Chapman, S. C., Laws, K., George-Jaeggli, B., Hammer, G. L., Jordan, D. R. and Potgieter, A. B. (2021) Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery. Plant Phenomics, 2021 . p. 9874650. ISSN null Zhi, X., Massey-Reed, S. R., Wu, A., Potgieter, A., Borrell, A., Hunt, C. H., Jordan, D., Zhao, Y., Chapman, S., Hammer, G. and George-Jaeggli, B. (2022) Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum. Plant phenomics (Washington, D.C.), 2022 . p. 9768502. ISSN 2643-6515 MonographAtzeni, M., Muehlebach, J., Fielder, D. and Mayer, D. G. (2020) Detect-alert-deter system for enhanced biosecurity and risk assessment. Project Report. AgriFutures. Robson, A., Abbott, C., Bramley, R. and Lamb, D. (2013) Remote Sensing - based precision agriculture tool for the sugar industry. Project Report. Sugar Research Australia. Conference or Workshop ItemHan, L., Cao, J., Ibell, P. and Diczbalis, Y. (2022) DigiHort: Digital Twins for Innovation of Future Orchard Systems. In: TropAg 2022 International Agriculture Conference, 31 October - 2 November 2022, Brisbane, Australia. Holloway, C. T., O'Reagain, P. J. and Tomkins, N. (2008) Patch selection by cattle can be quantified using satellite imagery and GPS in extensive, semi-arid savannas. In: Multifunctional grasslands in a changing world, Volume 1: XXI International Grassland Congress and VIII International Rangeland Congress., 29th June - 5th July 2008, Hohhot, China. |