New photogrammetric sensors for precision agriculture: the use of hyperspectral cameras

Photogrammetric and remote sensing techniques are increasingly getting used in precision agriculture to improve monitoring and management of the crops and at the same time to increase the crop yield and reduce the environmental impacts derived from the treatments. The entire production sector can benefit from the advance in technologies and the development of lightweight sensors for UAV (uncrewed aerial vehicles) with a higher spectral and spatial resolution such as the hyperspectral sensors. The hyperspectral sensors’ ability for measuring hundreds of bands has impacts on the complexity and the data processing. Indeed, it is necessary to handle a considerable quantity of acquired data and select the relevant information for interventions in the agricultural area. The aims of this work are providing a survey of the UAV-based hyperspectral sensors available on the market and their acquisition technology and a global view of possible applications in the agriculture field. Moreover, the paper highlights future research developments related to this new type of device.

Photogrammetric and remote sensing techniques are increasingly getting used in precision agriculture to improve monitoring and management of the crops and at the same time to increase the crop yield and reduce the environmental impacts derived from the treatments. The entire production sector can benefit from the advance in technologies and the development of lightweight sensors for UAV (uncrewed aerial vehicles) with a higher spectral and spatial resolution such as the hyperspectral sensors. The hyperspectral sensors’ ability for measuring hundreds of bands has impacts on the complexity and the data processing. Indeed, it is necessary to handle a considerable quantity of acquired data and select the relevant information for interventions in the agricultural area. The aims of this work are providing a survey of the UAV-based hyperspectral sensors available on the market and their acquisition technology and a global view of possible applications in the agriculture field. Moreover, the paper highlights future research developments related to this new type of device.


ISSN 1121-9041

CiteScore:
2020: 3.8
CiteScore measures the average citations received per peer-reviewed document published in this title.
CiteScore values are based on citation counts in a range of four years (e.g. 2016-2019) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2016 —19).
Source Normalized Impact per Paper (SNIP):
2019: 1.307
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR)
2019: o.657
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal's impact.
Journal Metrics: CiteScore: 1.0 , Source Normalized Impact per Paper (SNIP): 0.381 SCImago Journal Rank (SJR): 0.163

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