Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study
A web mapping XYZ Tile Layer Service, such as Google Earth (GE), provides an amazing resource for the visualization of spatial data against aerial and satellite imagery with global coverage, typically at a resolution finer than 5 m. However, the increasing requirement on spatial accuracy in farm inf...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/13/10/2563 |
| _version_ | 1827722093419036672 |
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| author | Hari Krishna Dhonju Kerry Brian Walsh Thakur Bhattarai |
| author_facet | Hari Krishna Dhonju Kerry Brian Walsh Thakur Bhattarai |
| author_sort | Hari Krishna Dhonju |
| collection | DOAJ |
| description | A web mapping XYZ Tile Layer Service, such as Google Earth (GE), provides an amazing resource for the visualization of spatial data against aerial and satellite imagery with global coverage, typically at a resolution finer than 5 m. However, the increasing requirement on spatial accuracy in farm information requires a greater appreciation of the issues involved in the use of such services. Position errors can be created in the georeferencing and orthorectification of images, transformation between reference frames (datums) in map projection, e.g., using a spheroid as compared to an ellipsoid earth model, and tectonic shifts. A review is provided of these issues, and a case study is provided of the horizontal positional accuracy of web map imagery for Australian mango orchards. Positional accuracies varied from 1.804 to 6.131 m across four farms using GE 2021 imagery, between 1.556 and 3.365 m in one farm for the most recent imagery available from each of four web map providers, and from 0.806 m (in 2016) to 10.634 m (in 2003) in one farm for the period of 2003 and 2021 using the historical GE imagery resource. A procedure involving the estimation of four transformation parameters was demonstrated for the alignment of GNSS data with GE imagery. However, as the scale factor was unity and the rotational value was near zero, the use of a simple horizontal mean shift vector was recommended. Further recommendations are provided on (i) the use of web mapping services, with a comparison of the use of UAV survey imagery, and (ii) the need for metadata, particularly the date of collection, on collected position data, in the context of use in farm management information systems. |
| first_indexed | 2024-03-10T21:30:49Z |
| format | Article |
| id | doaj.art-e38eaf6064fe4852b8d0898bf4f7dbe6 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T21:30:49Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-e38eaf6064fe4852b8d0898bf4f7dbe62023-11-19T15:21:58ZengMDPI AGAgronomy2073-43952023-10-011310256310.3390/agronomy13102563Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case StudyHari Krishna Dhonju0Kerry Brian Walsh1Thakur Bhattarai2Institute of Future Farming Systems, Central Queensland University, Rockhampton, QLD 4701, AustraliaInstitute of Future Farming Systems, Central Queensland University, Rockhampton, QLD 4701, AustraliaInstitute of Future Farming Systems, Central Queensland University, Rockhampton, QLD 4701, AustraliaA web mapping XYZ Tile Layer Service, such as Google Earth (GE), provides an amazing resource for the visualization of spatial data against aerial and satellite imagery with global coverage, typically at a resolution finer than 5 m. However, the increasing requirement on spatial accuracy in farm information requires a greater appreciation of the issues involved in the use of such services. Position errors can be created in the georeferencing and orthorectification of images, transformation between reference frames (datums) in map projection, e.g., using a spheroid as compared to an ellipsoid earth model, and tectonic shifts. A review is provided of these issues, and a case study is provided of the horizontal positional accuracy of web map imagery for Australian mango orchards. Positional accuracies varied from 1.804 to 6.131 m across four farms using GE 2021 imagery, between 1.556 and 3.365 m in one farm for the most recent imagery available from each of four web map providers, and from 0.806 m (in 2016) to 10.634 m (in 2003) in one farm for the period of 2003 and 2021 using the historical GE imagery resource. A procedure involving the estimation of four transformation parameters was demonstrated for the alignment of GNSS data with GE imagery. However, as the scale factor was unity and the rotational value was near zero, the use of a simple horizontal mean shift vector was recommended. Further recommendations are provided on (i) the use of web mapping services, with a comparison of the use of UAV survey imagery, and (ii) the need for metadata, particularly the date of collection, on collected position data, in the context of use in farm management information systems.https://www.mdpi.com/2073-4395/13/10/2563GDA2020GDA94WGS84tectonic shiftvisualizationweb imagery |
| spellingShingle | Hari Krishna Dhonju Kerry Brian Walsh Thakur Bhattarai Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study Agronomy GDA2020 GDA94 WGS84 tectonic shift visualization web imagery |
| title | Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study |
| title_full | Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study |
| title_fullStr | Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study |
| title_full_unstemmed | Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study |
| title_short | Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study |
| title_sort | web mapping for farm management information systems a review and australian orchard case study |
| topic | GDA2020 GDA94 WGS84 tectonic shift visualization web imagery |
| url | https://www.mdpi.com/2073-4395/13/10/2563 |
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