|MOUAZEN, ABDUL - Ghent University|
|ALEXANDRIDIS, THOMAS - Aristotle University Of Thessaloniki|
|BUDDENBAUM, HENNING - University Of Trier|
|COHEN, YAFIT - Agricultural Research Organization Of Israel|
|MOSHOU, DIMITRIOS - Aristotle University Of Thessaloniki|
|MULLA, DAVID - University Of Minnesota|
|NAWAR, SAID - Ghent University|
|Sudduth, Kenneth - Ken|
Submitted to: Agricultural Internet of Things and Decision Support for Smart Farming
Publication Type: Book / Chapter
Publication Acceptance Date: 6/3/2019
Publication Date: 1/17/2020
Citation: Mouazen, A., Alexandridis, T., Buddenbaum, H., Cohen, Y., Moshou, D., Mulla, D., Nawar, S., Sudduth, K.A. 2020. Monitoring. In: Castrignano, A., Buttafuoco, G., Khosla, R., Mouazen, A.M., Moshou, D., Naud, O. Agricultural Internet of Things and Decision Support for Smart Farming. Cambridge, MA: Academic Press. p. 35-138. https://doi.org/10.1016/B978-0-12-818373-1.00002-0.
Technical Abstract: The first requirement for successful implementation of precision agriculture in the plant production sector is to measure and map within field spatial and temporal variability. This can be achieved by means of two main sensing approaches, namely, remote sensing and proximal sensing, for characterizing both soils and crops. Each of these two categories has advantages and shortcomings. This chapter discusses the potential of different sensing technologies to characterize within-field variability of soils and crops, by providing high sampling resolution data necessary for site-specific management of farm input resources (e.g., fertilisers, water for irrigation, seeds, pesticides). Each of the sensing methods presented are discussed in terms of: 1) A brief introduction of a technology, 2) List of properties measured, and associated accuracy and practicality, 3) Application case studies for agricultural management and 4) Conclusions and future perspectives.