The economic and environmental impacts of precision agriculture and interactions with agro-environmental policy

Schieffer, Jack; Dillon, Carl R.

doi:10.1007/s11119-014-9382-5

Cited by 58 publications

(36 citation statements)

References 9 publications

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“…With the reduction in machine size and inherent weight advantage comes a reduced potential for soil compaction. Coupled with the ability to improve chemical, fertilizer and fuel use efficiency, the environmental impacts of autonomous machinery will be substantial especially to the extent they can be coupled with variable rate application (Scheiffer and Dillon, 2015). Hence, the utilization of autonomous machinery could develop into a more profitable approach to production agriculture.…”

Section: An Economic Feasibility Assessment Of Autonomous Field Machimentioning

confidence: 99%

An economic feasibility assessment of autonomous field machinery in grain crop production

2019

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A multi-faceted whole farm planning model is developed to compare conventional and autonomous machinery for grain crop production under various benefit, farm size, suitable field day risk aversion, and grain price scenarios. Results suggest that autonomous machinery can be an economically viable alternative to conventional manned machinery if the establishment of intelligent controls is cost effective. An increase in net returns of 24% over operating with conventional machinery is found when including both input savings and a yield increase due to reduced compaction. This study also identifies the break-even investment price for intelligent controls for the safe and reliable commercialization of autonomous machinery. Results indicate that the break-even investment price is highly variable depending on the financial benefits resulting from the deployment of autonomous machinery, farm size, suitable field day risk aversion, and grain prices. The maximum break-even investment price for intelligent, autonomous controls is nearly U.S. $500,000 for the median days suitable for fieldwork when including both input savings and a yield increase due to reduced compaction.

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Section: An Economic Feasibility Assessment Of Autonomous Field Machimentioning

confidence: 99%

An economic feasibility assessment of autonomous field machinery in grain crop production

2019

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“…Precision agriculture (PA) [1] is a very significant societal challenge and promises to enable several significant improvements: increase of productivity; optimal, and thus reduced, use of pesticides and fertilizers; and decreased use of water. These will translate into substantial benefits, including making more food available for mankind, increasing environmental sustainability, and contributing to the mitigation of climate change effects [2]. One key component of precision agriculture is crop health diagnostic capability.…”

Section: Key Topicsmentioning

confidence: 99%

Geometric and Radiometric Consistency of Parrot Sequoia Multispectral Imagery for Precision Agriculture Applications

et al. 2019

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This paper is about the geometric and radiometric consistency of diverse and overlapping datasets acquired with the Parrot Sequoia camera. The multispectral imagery datasets were acquired above agricultural fields in Northern Italy and radiometric calibration images were taken before each flight. Processing was performed with the Pix4Dmapper suite following a single-block approach: images acquired in different flight missions were processed in as many projects, where different block orientation strategies were adopted and compared. Results were assessed in terms of geometric and radiometric consistency in the overlapping areas. The geometric consistency was evaluated in terms of point cloud distance using iterative closest point (ICP), while the radiometric consistency was analyzed by computing the differences between the reflectance maps and vegetation indices produced according to adopted processing strategies. For normalized difference vegetation index (NDVI), a comparison with Sentinel-2 was also made. This paper will present results obtained for two (out of several) overlapped blocks. The geometric consistency is good (root mean square error (RMSE) in the order of 0.1 m), except for when direct georeferencing is considered. Radiometric consistency instead presents larger problems, especially in some bands and in vegetation indices that have differences above 20%. The comparison with Sentinel-2 products shows a general overestimation of Sequoia data but with similar spatial variations (Pearson’s correlation coefficient of about 0.7, p-value < 2.2 × 10−16).

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“…Its ultimate objective is to optimize crop production and profitability through a reduction in production inputs (e.g., pesticides, fertilizers, machinery, fuel, water, etc.) and, consequently, diminish potential damage to the environment due to the over-application of inputs [3,4].…”

Section: Introductionmentioning

confidence: 99%

3-D Characterization of Vineyards Using a Novel UAV Imagery-Based OBIA Procedure for Precision Viticulture Applications

et al. 2018

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Precision viticulture has arisen in recent years as a new approach in grape production. It is based on assessing field spatial variability and implementing site-specific management strategies, which can require georeferenced information of the three dimensional (3D) grapevine canopy structure as one of the input data. The 3D structure of vineyard fields can be generated applying photogrammetric techniques to aerial images collected with Unmanned Aerial Vehicles (UAVs), although processing the large amount of crop data embedded in 3D models is currently a bottleneck of this technology. To solve this limitation, a novel and robust object-based image analysis (OBIA) procedure based on Digital Surface Model (DSM) was developed for 3D grapevine characterization. The significance of this work relies on the developed OBIA algorithm which is fully automatic and self-adaptive to different crop-field conditions, classifying grapevines, and row gap (missing vine plants), and computing vine dimensions without any user intervention. The results obtained in three testing fields on two different dates showed high accuracy in the classification of grapevine area and row gaps, as well as minor errors in the estimates of grapevine height. In addition, this algorithm computed the position, projected area, and volume of every grapevine in the field, which increases the potential of this UAV-and OBIA-based technology as a tool for site-specific crop management applications.

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The economic and environmental impacts of precision agriculture and interactions with agro-environmental policy

Cited by 58 publications

References 9 publications

An economic feasibility assessment of autonomous field machinery in grain crop production

An economic feasibility assessment of autonomous field machinery in grain crop production

Geometric and Radiometric Consistency of Parrot Sequoia Multispectral Imagery for Precision Agriculture Applications

3-D Characterization of Vineyards Using a Novel UAV Imagery-Based OBIA Procedure for Precision Viticulture Applications

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