Estimation of pasture growth rate in the south west of Western Australia from AVHRR NDVI and climate data

Hill, Michael J.; Donald, G. E.; Hyder, M. W.; Smith, Richard C.

doi:10.1016/j.rse.2004.08.006

Cited by 88 publications

(55 citation statements)

References 23 publications

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“…This has been applied to pastures and rangelands (Kumar et al, 2001;Schellberg et al, 2008). For example, in temperate Australia 50% to 70% of the variance in growth rate of annual pastures could be predicted from satellite imagery (Hill et al, 2004;Donald et al, 2010) and accumulated pasture growth usefully estimated from sequential measurements. Such satellite-based spectral information appears most useful to estimate plant community distribution and pasture cover in extensive rangelands (Booth and Tueller, 2003;Karfs et al, 2009).…”

Section: Evaluation Of Pasture Attributesmentioning

confidence: 99%

The importance of grasslands for animal production and other functions: a review on management and methodological progress in the tropics

Boval

Dixon

2012

Animal

179

106

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The global importance of grasslands is indicated by their extent; they comprise some 26% of total land area and 80% of agriculturally productive land. The majority of grasslands are located in tropical developing countries where they are particularly important to the livelihoods of some one billion poor peoples. Grasslands clearly provide the feed base for grazing livestock and thus numerous high-quality foods, but such livestock also provide products such as fertilizer, transport, traction, fibre and leather. In addition, grasslands provide important services and roles including as water catchments, biodiversity reserves, for cultural and recreational needs, and potentially a carbon sink to alleviate greenhouse gas emissions. Inevitably, such functions may conflict with management for production of livestock products. Much of the increasing global demand for meat and milk, particularly from developing countries, will have to be supplied from grassland ecosystems, and this will provide difficult challenges. Increased production of meat and milk generally requires increased intake of metabolizable energy, and thus increased voluntary intake and/or digestibility of diets selected by grazing animals. These will require more widespread and effective application of improved management. Strategies to improve productivity include fertilizer application, grazing management, greater use of crop by-products, legumes and supplements and manipulation of stocking rate and herbage allowance. However, it is often difficult to predict the efficiency and cost-effectiveness of such strategies, particularly in tropical developing country production systems. Evaluation and on-going adjustment of grazing systems require appropriate and reliable assessment criteria, but these are often lacking. A number of emerging technologies may contribute to timely low-cost acquisition of quantitative information to better understand the soil–pasture–animal interactions and animal management in grassland systems. Development of remote imaging of vegetation, global positioning technology, improved diet markers, near IR spectroscopy and modelling provide improved tools for knowledge-based decisions on the productivity constraints of grazing animals. Individual electronic identification of animals offers opportunities for precision management on an individual animal basis for improved productivity. Improved outcomes in the form of livestock products, services and/or other outcomes from grasslands should be possible, but clearly a diversity of solutions are needed for the vast range of environments and social circumstances of global grasslands.

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Section: Evaluation Of Pasture Attributesmentioning

confidence: 99%

The importance of grasslands for animal production and other functions: a review on management and methodological progress in the tropics

Boval

Dixon

2012

Animal

179

106

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“…The NDVI index has been used to successfully identify green vegetation canopy characteristics such as the leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (faPAR) and green biomass (Tucker 1979;Hill et al 2004). LAI has a significant impact on the capacity of a vegetation canopy to intercept solar radiation faPAR (Friedl et al 1994).…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, the use of NDVI, coupled with meteorological data to estimate pasture biomass and potential pasture growth rate (Edirisinghe et al 2000;Hill et al 2004), has been found useful for assisting in livestock management decisions. These estimates of pasture growth rate were validated for pastures in the south-west of Western Australia, and they are now available for weekly intervals at a shire scale (http://www.pasturesfromspace.csiro.au/, verified 8 July 2012) and at a farm and paddock scale by subscription to the commercial service, Pasture Watch (http://www.fairport.com.au/ pasturewatch/, verified 20 June 2012).…”

Section: Introductionmentioning

confidence: 99%

Satellite derived evidence of whole farmlet and paddock responses to management and climate

Donald

Scott

Vickery³

2013

Anim. Prod. Sci.

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Abstract. Satellite imagery was used to assess differences between three treatments in a grazing enterprise systems study of three 53-ha farmlets on the Northern Tablelands of New South Wales, Australia. The study involved a comparison between a typical control farmlet (B) with one with higher levels of sown pasture and soil fertility (A) and one employing intensive rotational grazing (C). Landsat thematic mapper data were used to derive normalised difference vegetation index (NDVI) and spectral class images for eight dates from before the commencement of the farmlet trial (June 2000) to annual spring measurements in September-October of each year from 2000 to 2006 across all paddocks of each farmlet. The Landsat imagery taken before the commencement of the farmlet treatments (June 2000) showed only small differences between the three farmlets, confirming that the allocation of land to the farmlets had been without bias. The assessments using Landsat NDVI in spring over 7 years showed differences in green herbage resulting from the variation in rainfall received over different years as well as differences between the farmlets. The Landsat NDVI images showed increasing and significant differences in pasture greenness over time, especially between Farmlet A and Farmlets B and C. In addition, there were significant differences in pasture spectral classes between Farmlet A and Farmlets B and C, with a significant correlation with higher levels of sown perennial and annual grasses and legumes on Farmlet A. Using different statistical tools, several relationships were found between NDVI and spectral class data and explanatory variables of farmlet, paddock, sowing phase, modelled soil moisture and recent grazing activity. The moderate resolution Landsat data across the entire area of each farmlet proved to be especially useful for assessing pastures within every paddock used in this farmlet study. In addition, moderate resolution imaging spectro radiometer NDVI satellite data were collated for weekly intervals from September 2003 to December 2006 in order to assess seasonal pasture growth patterns on each of the farmlets. These patterns were significantly correlated with a growth index calculated from temperature and available soil moisture, and showed that the growth on the three farmlets was closer to a highly productive reference paddock than a low input, unsown pasture in another reference paddock. The satellite data facilitated the detection of significant differences in pasture botanical composition, soil fertility, grazing management, climate and season. The ready availability of quality remote sensed imagery, combined with the significance of the relationships established, confirms that the technology is a valuable objective tool for both farming systems research and for managing entire farms.

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“…The GAPP model GAPP values for 1994 to 2006 were calculated from weekly estimates of pasture growth rate (PGR) derived using satellite images, climate data, and a light-use efficiency (LUE) model [18], as described in detail by [7]. This method is distinguished by LUE values which are constrained by climate indices.…”

Section: B Image and Climate Datamentioning

confidence: 99%

“…Such datasets provide monitoring of vegetation characteristics such as gross primary production (GPP) [2][6] across large geographical extents. There has been other work on the remote sensing of pastures [7], but this has tended to focus on crops [8], or on rangeland remote sensing [9].…”

Section: Introductionmentioning

confidence: 99%

Three regionalised analyses of a time-series of annual pasture production for southwest Western Australia

Handcock

Donald

Gherardi

2007

2007 IEEE International Geoscience and Remote Sensing Symposium

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Abstract-A thirteen year time-series (1994 to 2006) of gross annual pasture production (GAPP; representing both pasture and crop) was created for the Mediterranean-climate area in the southwest of Western Australia (SWWA) using a light-use efficiency model, incorporating NOAA-AVHRR and NASA-MODIS images in combination with climate data. Trends across the GAPP time-series were quantified by aggregating pixels to spatial regions (called a partition, unit, or spatial support) so that the effects of local spatial noise were minimized. We compared the GAPP analysis using the three spatial partitioning schemes (precipitation zones, Interim Biogeographic Regionalisation for Australia (IBRA) eco-regions, and Statistical Local Areas), and showed that the aggregation unit's size & shape impacted on the analysis. Our results demonstrate trends in GAPP that may be indicative of broader trends in climate change for the SWWA.

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Estimation of pasture growth rate in the south west of Western Australia from AVHRR NDVI and climate data

Cited by 88 publications

References 23 publications

The importance of grasslands for animal production and other functions: a review on management and methodological progress in the tropics

The importance of grasslands for animal production and other functions: a review on management and methodological progress in the tropics

Satellite derived evidence of whole farmlet and paddock responses to management and climate

Three regionalised analyses of a time-series of annual pasture production for southwest Western Australia

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