Abstract
In this report we show 2 different cases in which Remote Sensing can help Precision Farming techniques to optimize and improve profits in the agricultural sector. First, we’ll show a practical case in an olive trees field and second an example of how to monitor a greenhouse crop with aerial images and deep learning techniques.
Highlights
Terms like precision agriculture (PA), precision farming, site-specific crop management or even site-specific farming suggest that agricultural management can be practised with high precision
We present 2 different cases of study to show how this methodology can be adapted to any kind of crop, it can be useful in greenhouse crops too, improving and modernizing the agroforestry sector using the information obtained through remote sensing and changing the traditional farming practices
The first trial (Case A) is an Olive Trees field located in a production farm in the region of “Montes Orientals” in Granada province, Spain (37°23’33.93"N, 3°24’40.93"O) (Fig. 1)
Summary
Terms like precision agriculture (PA), precision farming, site-specific crop management or even site-specific farming suggest that agricultural management can be practised with high precision. The world’s food scenery is changing fast rising the global demand and increasing the cost of agricultural inputs [2]. The adoption of this kind of technology is lower than 5% usually in countries, is more than 30% in USA [3]. The general steps of PA practice are data collection, field variability mapping, decision making, and management practice. It is critical to obtain up-to-date images/maps during the process of decision making, field variability could be mapped using remotely sensed imagery. Drones play a special role in this field [4]
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