The PAT QGIS toolset - AWITC · a new freeware suite of data analysis tools ‐Precision...
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REFERENCES 1 QGIS Development Team. 2016. QGIS Geographic Information System. Version 2.18. Open Source Geospatial Foundation Project. https://qgis.org. 2 Minasny B, McBratney AB, Whelan BM (2005) VESPER version 1.62. Australian Centre for Precision Agriculture. https://sydney.edu.au/agriculture/pal/software/vesper.shtml. 3 Lawes RA, Bramley RGV. 2012. A Simple Method for the Analysis of On‐Farm Strip Trials. Agronomy Journal 104, 371‐377. 4 Bramley RGV, Hamilton RP. 2004. Understanding variability in winegrape production systems. 1. Within vineyard variation in yield over several vintages. Australian Journal of Grape and Wine Research. 10: 32‐45. 5 Bramley RGV, Lawes RA, Cook SE. 2013. Spatially distributed experimentation: tools for the optimization of targeted management. Chapter 12 in: Oliver MA, Bishop TFA, Marchant BM. (Eds). Precision Agriculture for Sustainability and Environmental Protection. Earthscan, Food and Agriculture Series. Routledge, Abingdon, UK. pp. 205‐218. 6 Song X, Bramley R, Evans K. 2019. Exploring a simple strip approach to vineyard experiments for understanding spatial variation in treatment responses. This conference. 7 Panten K, Bramley RGV. 2011. Viticultural experimentation using whole blocks: Evaluation of three floor management options. Australian Journal of Grape and Wine Research 17 136‐146. ACKNOWLEDGEMENTS CSIRO’s development of PAT draws on many years of Precision Agriculture RDE and has been supported by Wine Australia through funding from the Australian Federal Department of Agriculture as part of its Rural R&D for Profit program. The PAT QGIS toolset The core PAT toolset delivers the workflow for the generation of maps from high spatial density ‘on‐the‐go’ sensor data such as from yield monitors or high resolution soil surveys (e.g. EM38; Figure 1). PAT also contains tools for the analysis of vineyard related data as shown in Table 1. Winegrowers can now more easily benefit from many years of Precision Viticulture (PV) research through a new freeware suite of data analysis tools ‐ Precision Agriculture Tools (PAT). PAT, a free ‘plugin’ to QGIS 1 , provides simple easy ‐ to ‐ use tools that implement the spatial data analyses that underpin PV. CSIRO AGRICULTURE & FOOD, WAITE CAMPUS Figure 3: A ‘whole‐of‐block’ trial in a Clare Valley vineyard focused on mid‐row management 7 . Analysis of on‐farm trials PAT also includes tools for the analysis of so‐called ‘spatially distributed experiments’ 5 , whether these are simple strip trials 6 or ‘whole‐of‐block’ trials 7 (Figure 3). PAT’s run strip trial t‐test analysis and whole‐of‐block analysis tools can be used to provide additional insights to these types of trials that are conducted at scale using the grower’s own equipment. PAT enables easy analysis of such trials. Table 1. A selection of some of the PAT analysis tools. Figure 2: Development of management zones in a Padthaway vineyard. Christina Ratcliff, David Gobbett and Rob Bramley Figure 1. PAT workflow for mapping high spatial density on‐the‐go data. Accessing PAT The analysis functions underpinning PAT are available in an open source library for the Python programming language called pyprecag which enables developers to build the PAT capabilities into their own software. However, we expect most users to access PAT via the QGIS front end. PAT plugin for QGIS is currently available for use with QGIS 2 for Windows. Currently PAT does not support QGIS 3.x. Further information, including on how to access PAT and pyprecag can be obtained by emailing [email protected].
Transcript of The PAT QGIS toolset - AWITC · a new freeware suite of data analysis tools ‐Precision...
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REFERENCES1QGIS Development Team. 2016. QGIS Geographic Information System. Version 2.18. Open Source Geospatial Foundation Project. https://qgis.org.2Minasny B, McBratney AB, Whelan BM (2005) VESPER version 1.62. Australian Centre for Precision Agriculture. https://sydney.edu.au/agriculture/pal/software/vesper.shtml.3Lawes RA, Bramley RGV. 2012. A Simple Method for the Analysis of On‐Farm Strip Trials. Agronomy Journal 104, 371‐377.4Bramley RGV, Hamilton RP. 2004. Understanding variability in winegrape production systems. 1. Within vineyard variation in yield over several vintages. Australian Journal of Grape andWine Research. 10: 32‐45.5Bramley RGV, Lawes RA, Cook SE. 2013. Spatially distributed experimentation: tools for the optimization of targeted management. Chapter 12 in: Oliver MA, Bishop TFA, Marchant BM. (Eds). Precision Agriculture for Sustainability and Environmental Protection. Earthscan, Food and Agriculture Series. Routledge, Abingdon, UK. pp. 205‐218.6Song X, Bramley R, Evans K. 2019. Exploring a simple strip approach to vineyard experiments for understanding spatial variation in treatment responses. This conference.7Panten K, Bramley RGV. 2011. Viticultural experimentation using whole blocks: Evaluation of three floor management options. Australian Journal of Grape and Wine Research 17 136‐146.
ACKNOWLEDGEMENTSCSIRO’s development of PAT draws on many years of Precision Agriculture RDE and has been supported by Wine Australia through funding from the Australian Federal Department of Agriculture as part of its Rural R&D for Profit program.
The PAT QGIS toolsetThe core PAT toolset delivers the workflow for the generation of maps from high spatial density ‘on‐the‐go’ sensor data such as from yield monitors or high resolution soil surveys (e.g. EM38; Figure 1). PAT also contains tools for the analysis of vineyard related data as shown in Table 1.
Winegrowers can now more easily benefit from many years of Precision Viticulture (PV) research through a new freeware suite of data analysis tools ‐ Precision Agriculture Tools (PAT). PAT, a free ‘plugin’ to QGIS1, provides simple easy‐to‐use tools that implement the spatial data analyses that underpin PV.
CSIRO AGRICULTURE & FOOD, WAITE CAMPUS
Figure 3: A ‘whole‐of‐block’ trial in a Clare Valley vineyard focused on mid‐row management7.
Analysis of on‐farm trialsPAT also includes tools for the analysis of so‐called ‘spatially distributed experiments’5, whether these are simple strip trials6 or ‘whole‐of‐block’ trials7 (Figure 3).
PAT’s run strip trial t‐test analysis and whole‐of‐block analysis tools can be used to provide additional insights to these types of trials that are conducted at scale using the grower’s own equipment. PAT enables easy analysis of such trials.
Table 1. A selection of some of the PAT analysis tools.Figure 2: Development of management zones in a Padthaway vineyard.
Christina Ratcliff, David Gobbett and Rob Bramley
Figure 1. PAT workflow for mapping high spatial density on‐the‐go data.
Accessing PATThe analysis functions underpinning PAT are available in an open source library for the Python programming language called pyprecag which enables developers to build the PAT capabilities into their own software. However, we expect most users to access PAT via the QGIS front end.
PAT plugin for QGIS is currently available for use with QGIS 2 for Windows. Currently PAT does not support QGIS 3.x. Further information, including on how to access PAT and pyprecag can be obtained by emailing [email protected].
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