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 categories, namely, remote sensing and proximal sensing, for characterizing both soils and crops. Each of these two categories has advantageous 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., fertilizers, water for irrigation, seeds and pesticides). Each of the sensing methods presented are discussed in terms of (1) a brief introduction of a technology, (2) list of properties and associated accuracy and practicality and (3) application case studies for agricultural management.
|Original language||English (US)|
|Title of host publication||Agricultural Internet of Things and Decision Support for Precision Smart Farming|
|Number of pages||104|
|State||Published - Jan 14 2020|
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- High sampling resolution
- Proximal sensing
- Remote sensing