Data-driven precision agricultural applications using field sensors and Unmanned Aerial Vehicle

Abstract: Unmanned Aerial Vehicle (UAVs) and crop sensors are the most widely used remote sensing tool in precision agriculture.  Use of UAVs in precision agriculture is attracting increasing interest due to its unique non-destructive approach.  In recent years, dramatic evolution of precision agriculture technology has been driven by technologies such as sensors and controllers, telematics, and UAVs.  An intriguing area in the field of precision agriculture and UAVs is big volume of data and its analysis that have not been dealt with in depth.  The objective of this study was to validate the crop data acquisition procedure and the crop relationship with different type of data acquisition technique.  In particular, this paper will compare ground based active optical sensor data collection with UAVs imagery for site-specificnitrogen management.  To accomplish these objectives randomized complete block plantation experimental design was used with four treatments and four replicates.  The plots were 12 rows wide at 38” spacing and were 125 ft. in length.  GreenSeeker field sensor and Micasense sensor for UAVs was used to evaluate the Normalized Difference Vegetation Index.  The software used to analyze the data were Microsoft ® Excel ®  2013, Statistical Analysis Software (ver.9.4) and ESRI ArcGIS (ver. 10.3).  The results showed that UAVs assessed NDVI are good indicator of crop nutrition along with the ground based crop sensors.  The result of the statistical data analysis showed that NDVI values are dependent on nitrogen application rate.  The average NDVI value for no nitrogen application was recorded 0.54 whereas for240 lb./acre nitrogen application it was noted to be 0.76.  Crucially, this correlation holds true for definite extent of nitrogen application rate.  Because there was not any significant change in NDVI for 160 lb./acre and240 lb./acre.  The NDVI values being 0.74 and 0.76 respectively.  The results are significant because it shows the potential of further validating the use of aerial imagery derived NDVI for real time application of crop nutrient.  This research has also proven that UAVs are reliable platform for nutrient assessment and making crop management decisions. Keywords: Digital image, NDVI, Nitrogen, ground based sensor, crop DOI: 10.33440/j.ijpaa.20180101.0004 Citation: Pathak R, Barzin R, Bora G C. Data-driven precision agricultural applications using field sensors and Unmanned Aerial Vehicle (UAVs). Int J Precis Agric Aviat, 2018; 1(1): 19 –23.

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