Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/11502
Title: Integrating MODIS satellite imagery and proximal vegetation sensors to enable precision livestock management
Contributor(s): Donald, Graham (author); Ahmad, Waqar (author); Hulm, Elizabeth (author); Trotter, Mark  (author); Lamb, David  (author)
Publication Date: 2012
DOI: 10.1109/Agro-Geoinformatics.2012.6311630
Handle Link: https://hdl.handle.net/1959.11/11502
Abstract: In temperate and mediterranean regions of Australia, utilisation of pastures by grazing animals can often be as low as thirty percent. Feed budgeting is a critical strategy for improving feed utilisation and there are now pasture evaluation and monitoring programs available to farmers across Australia to enable them to estimate Pasture Growth Rate (PGR) and feed availability or Feed On Offer (FOO). Unfortunately, many farmers do not have the confidence or the time available to make regular accurate field estimates across large and remote paddocks. It is also extremely difficult to measure the spatial variation of FOO and PGR. Both satellite image-based systems, such as that derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and on-ground, active sensors and spectroradiometers have limitations. The MODIS sensor, although offering a daily acquisition interval, has a spatial resolution of 6.25ha which does create an issue in describing higher resolution spatial variation in fields and is susceptible to the unwanted artefacts associated with non-forageable vegetation such as trees. On-ground (proximal) sensors such as the Crop Circle™ instrument, can be integrated with with global positioning systems (GPS) and dataloggers and operated 'on-the-go', but field-coverage require a vast number of samples that in turn require tedious analysis and particularly if done at frequent intervals. The aim of this paper is to test whether the MODIS and Crop Circle™ data can be intergrated to provide the benefit of both high spatial and temporal resolution. Such information would be useful when determining feed on offer and pasture growth rate information at weekly or strategic times from MODIS acquisitions including other biophysical and physical relevant attributes. This electronic document is a "live" template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.
Publication Type: Conference Publication
Conference Details: Agro-Geoinformatics 2012: 1st International Conference on Agro-Geoinformatics, Shanghai, China, 2nd - 4th August, 2012
Source of Publication: Proceedings of the First International Conference on Agro-Geoinformatics (Agro-Geoinformatics 2012), p. 157-161
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Place of Publication: Los Alamitos, United States of America
Fields of Research (FoR) 2008: 050206 Environmental Monitoring
Fields of Research (FoR) 2020: 410599 Pollution and contamination not elsewhere classified
Socio-Economic Objective (SEO) 2008: 829899 Environmentally Sustainable Plant Production not elsewhere classified
Socio-Economic Objective (SEO) 2020: 260199 Environmentally sustainable plant production not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

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