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This chapter reviews key issues in using sensor data in precision agriculture (PA) and, in particular, their mode of deployment (proximal or remote). It assesses relative strengths and weaknesses of proximal sensing techniques, compared with imaging data typically acquired from remote sensing platforms, before assessing trade-offs in sensor data resolution, as well as sources of error in the way data is processed. The chapter concludes by looking at ways of integrating remote and proximal sensor data, to utilize the beneficial characteristics of each type of data to improve the impact precision agriculture in improving efficiency and sustainability.
- 1 Introduction
- 2 Remote and proximal sensing in agriculture
- 3 Active and passive sensors
- 4 Trade-offs in sensor data resolution
- 5 Processing sensor data: sources of error and their resolution
- 6 Integrating remote and proximal sensor data for precision agriculture
- 7 Conclusion
- 8 References