Login | Request Account (DAF staff only)

Items where Subject is "Remote sensing"

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: Creators | Item Type | Date
Jump to: A | B | F | H | J | P | R | T | X | Z
Number of items at this level: 17.

A

Akbarian, 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

Atzeni, M., Muehlebach, J., Fielder, D. and Mayer, D. G. (2020) Detect-alert-deter system for enhanced biosecurity and risk assessment. Project Report. AgriFutures.

B

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.

F

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.

H

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.

J

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.

P

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

R

Roboson, A. and Medway, J. (2009) Remote sensing applications for cotton. Australian Cottongrower, 30 (4). pp. 40-43.

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.

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.

T

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.

X

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

Z

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

This list was generated on Fri Dec 9 21:42:13 2022 UTC.