Abstract
The architecture and general structure of the Dynamic Aerial Survey (DAS) algorithm is presented in this paper. This algorithm is specifically designed for real-time airborne prescription fertilizer applications in the agricultural industry and is designed to batch process the dynamically updated data set after the aircraft completes each successive pass over the field using remote crop monitoring equipment. A key aspect of the DAS algorithm is that it allows a variety of different regression and segmentation modules to be added or deleted to suit user requirements. A specific application is presented concerning an aerial geo-survey of a 110 ha wheat field. The DAS algorithm, using the support-vector regression machine and the uniform-cut segmentation modules, will be demonstrated to allow accurate "on-the-go" estimation, updating and segmentation of the entire field into different management zones as the aircraft completes each pass. The DAS algorithm constitutes a key step in a wider research program designed to develop active-sensor based aerial prescription technology.
| Original language | English |
|---|---|
| Pages (from-to) | 1772-1779 |
| Journal | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Volume | 5 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
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SDG 15 Life on Land
Keywords
- Agricultural Land Management
- Agricultural Spatial Analysis and Modelling
- Decision Support and Group Support Systems
- Photonics and Electro-Optical Engineering (excl Communications)
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