Assessing and Improving Positional Accuracy and its Effects on Areal Estimation at Coleambally Irrigation Area
Access status:
Open Access
Type
Report, TechnicalAbstract
If management decisions are made with geospatial data that have not been assessed for positional accuracy, then debate about both methodologies of measurement and management decisions can occur. This debate, in part, can be avoided by assessing the positional accuracy of geospatial ...
See moreIf management decisions are made with geospatial data that have not been assessed for positional accuracy, then debate about both methodologies of measurement and management decisions can occur. This debate, in part, can be avoided by assessing the positional accuracy of geospatial data, leading to increased confidence (decreased uncertainty) in both the data and the decisions made from the data. In this study, we assessed the positional accuracy of two Geographic Information System (GIS) baseline datasets at the Coleambally Irrigation Area (CIA); high-resolution digital aerial photography acquired in January 2000, and the Digital Topographic Data Base (DTDB) roads data. We also assessed areal error of paddock measurements from an improved accuracy version of the high-resolution digital aerial photography. Positional accuracies were assessed by comparing well-defined features from both baseline datasets (original aerial photography and DTDB roads) to high-level accuracy Differential Global Positioning System (DGPS) data for the same features. This assessment showed that neither baseline dataset met the National Mapping Council of Australia’s standards of map accuracy. Consequently, we processed the original digital photography to create an improved dataset, which was over 2.5 times more accurate than the original photography, and over 4 times more accurate than the DTDB data. The improved dataset also met the map accuracy standard for Australia. We also assessed areal error by comparing paddock boundaries delineated from the improved dataset to those delineated from a DGPS associated with paddock soil surveys. The 90% confidence interval measured from the improved data for any individual paddock is approximately at the ± 5% target error set by Coleambally Irrigation Limited (CIL). The 95% confidence interval is roughly ± 6%. Overall areal error of multiple paddocks is much lower than the individual case with the 95% confidence interval for 2 paddocks being from about ± 4% error reducing to less than ± 2% for 8 or more paddocks. Knowledge of both positional and areal accuracies of the improved high-resolution digital aerial photography provides a means to more effectively manage environmental compliance of rice farmers at CIA and gives the CIL justification for making management decisions from this spatial data.
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See moreIf management decisions are made with geospatial data that have not been assessed for positional accuracy, then debate about both methodologies of measurement and management decisions can occur. This debate, in part, can be avoided by assessing the positional accuracy of geospatial data, leading to increased confidence (decreased uncertainty) in both the data and the decisions made from the data. In this study, we assessed the positional accuracy of two Geographic Information System (GIS) baseline datasets at the Coleambally Irrigation Area (CIA); high-resolution digital aerial photography acquired in January 2000, and the Digital Topographic Data Base (DTDB) roads data. We also assessed areal error of paddock measurements from an improved accuracy version of the high-resolution digital aerial photography. Positional accuracies were assessed by comparing well-defined features from both baseline datasets (original aerial photography and DTDB roads) to high-level accuracy Differential Global Positioning System (DGPS) data for the same features. This assessment showed that neither baseline dataset met the National Mapping Council of Australia’s standards of map accuracy. Consequently, we processed the original digital photography to create an improved dataset, which was over 2.5 times more accurate than the original photography, and over 4 times more accurate than the DTDB data. The improved dataset also met the map accuracy standard for Australia. We also assessed areal error by comparing paddock boundaries delineated from the improved dataset to those delineated from a DGPS associated with paddock soil surveys. The 90% confidence interval measured from the improved data for any individual paddock is approximately at the ± 5% target error set by Coleambally Irrigation Limited (CIL). The 95% confidence interval is roughly ± 6%. Overall areal error of multiple paddocks is much lower than the individual case with the 95% confidence interval for 2 paddocks being from about ± 4% error reducing to less than ± 2% for 8 or more paddocks. Knowledge of both positional and areal accuracies of the improved high-resolution digital aerial photography provides a means to more effectively manage environmental compliance of rice farmers at CIA and gives the CIL justification for making management decisions from this spatial data.
See less
Date
2004-01-01Publisher
CSIRO Land and WaterShare