Definition of sub-stands for Precision Forestry: an application of the fuzzy k-means method.

Ortega, José Alfonso; Foster, William; Ortega, Rodrigo

doi:10.7764/rcia.v29i1.422

Cited by 13 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, this problem has been applied for irrigation systems design, see (Haghverdi et al, 2015) where linear programming is used as one of the methods for delineating management zones among others as Kmeans and Isodata, methods that are still being used. These other methods are classified as clustering methods, see (Ortega et al,2002), (Jaynes et al,2005) and (Jiang et al (2011), but their major drawback is the resulting fragmentation of the zones, because these methods generate oval shaped and disjoint zones. Although the problem of defining management zones in presence of site specific variability has been studied in previous works, to the best of our knowledge, an important characteristic that has not been considered yet is variability in time of the chosen soil property.…”

Section: Introductionmentioning

confidence: 99%

Delineation of Rectangular Management Zones Under Uncertainty Conditions

Sáez

Albornoz

2016

Proceedings of 5th the International Conference on Operations Research and Enterprise Systems

View full text Add to dashboard Cite

In this article we cover the problem of generating a partition of an agricultural field into rectangular and homogeneous management zones or quarters according to a given soil property, which has variability in time that is presented as a number of possible scenarios. This problem combines aspects of precision agriculture and optimization with the purpose of achieving a site and time specific management of the field properties that is consistent and effective in time for a medium term horizon. More specifically, we propose a two stage integer stochastic linear programming model with recource that solves the problem of generating a partition facing a finite number of future scenarios, with a solution that gives satisfactory results to any possible value of the chosen soil property. We describe the proposed model, the adopted methodology and the results achieved with this methodology.

show abstract

Section: Introductionmentioning

confidence: 99%

Delineation of Rectangular Management Zones Under Uncertainty Conditions

Sáez

Albornoz

2016

Proceedings of 5th the International Conference on Operations Research and Enterprise Systems

View full text Add to dashboard Cite

show abstract

A Hierarchical Planning Scheme Based on Precision Agriculture

Albornoz

Cid-García

Ortega

et al. 2015

International Series in Operations Research &Amp; Management Science

View full text Add to dashboard Cite

The process for agriculture planning starts by delineating the field into site-specific rectangular management zones to face within-field variability. We propose a bi-objective model that minimizes the number of these zones and maximizes their homogeneity with respect to a soil property. Then we use a method to assign the crops to the different plots to obtain the best profit at the end of the production cycle subject to water forecasts for the period, humidity sensors, and the chemical and physical properties of the zones within the plot. With this crop planning model we can identify the best management zones of the previous bi-objective model. Finally, we show a real-time irrigation method to decide the amount of water for each plot, at each irrigation turn, in order to maximize the total final yield. This is a critical decision in countries where water shortages are frequent. In this study we integrate these stages in a hierarchical process for the agriculture planning and empirically prove its efficiency.

show abstract