@article{Zaragozí2020d,

title = {A geotagged image dataset with compass directions for studying the drivers of farmland abandonment},

author = {Benito Zaragozí and Sergio Trilles-Oliver and D. Carrion and Y. Pérez Albert},

doi = {https://doi.org/10.1016/j.dib.2020.106340 },

year  = {2020},

date = {2020-12-09},

urldate = {2020-12-09},

journal = {Data in Brief},

volume = {33},

pages = {106340},

abstract = {In this work, we present a dataset containing a collection of pictures taken during the fieldwork of a farmland abandonment study. Data was taken in 2010 with a compact camera that incorporates GPS and a digital compass sensor. The photographs were taken as part of a GIS database. Using their Exif metadata, we created a layer of geographic fields of view (geoFOVs) that can be used to perform specific spatial queries. The dataset contains 2,235 pictures and GIS layers of geoFOVs contextualising the agricultural plots being photographed. The dataset is hosted in a Zenodo dataset repository.},

keywords = {Agriculture, Geographic Information Systems (GIS)},

pubstate = {published},

tppubtype = {article}

}

@article{Trilles-Oliver2020f,

title = {Reliability Evaluation of the Data Acquisition Potential of a Low-Cost Climatic Network for Applications in Agriculture},

author = {Sergio Trilles-Oliver and Pablo Juan-Verdoy and Carlos Díaz-Avalos and S. Ribeiro and Marco Painho},

doi = {https://doi.org/10.3390/s20226597 },

issn = {1424-8220},

year  = {2020},

date = {2020-12-02},

journal = {Sensors},

volume = {20},

number = {22},

pages = {6597},

abstract = {Temperature, humidity and precipitation have a strong influence on the generation of diseases in different crops, especially in vine. In recent years, advances in different disciplines have enabled the deployment of sensor nodes on agricultural plots. These sensors are characterised by a low cost and so the reliability of the data obtained from them can be compromised, as they are built from low-confidence components. In this research, two studies were carried out to determine the reliability of the data obtained by different SEnviro nodes installed in vineyards. Two networks of meteorological stations were used to carry out these studies, one official and the other professional. The first study was based on calculating the homogenisation of the data, which was performed using the Climatol tool. The second study proposed a similarity analysis using cross-correlation. The results showed that the low-cost node can be used to monitor climatic conditions in an agricultural area in the central zone of the province of Castelló (Spain) and to obtain reliable observations for use in previously published fungal disease models.},

keywords = {Agriculture, crop monitoring, Sensor networks, Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{Valencia2020,

title = {A GIS-based methodological framework to identify superficial water sources and their corresponding conduction paths for gravity-driven irrigation systems in developing countries},

author = {Jefferson Valencia and Fredy Monserrate and Sven Casteleyn and Vincent Bax and Wendy Francesconi and Marcela Quintero},

doi = {10.1016/j.agwat.2020.106048},

issn = {0378-3774},

year  = {2020},

date = {2020-02-04},

urldate = {2020-02-04},

journal = {Agricultural Water Management},

volume = {232},

pages = {1-9},

abstract = {The limited availability of fresh water is a major constraint to agricultural productivity and livelihood security in many developing countries. Within the coming decades, smallholder farmers in drought-prone areas are expected to be increasingly confronted with local water scarcity problems, but their access to technological knowledge and financial resources to cope with these problems is often limited. In this article, we present a methodological framework that allows for identifying, in a short period of time, suitable and superficial water sources, and cost-effective water transportation routes for the provisioning of gravity-driven irrigation systems. As an implementation of the framework, we present the automated and extensible geospatial toolset named “AGRI’’, and elaborate a case study in Western Honduras, where the methodology and toolset were applied to provide assistance to field technicians in the process of identifying water intake sites and transportation routes. The case study results show that 28 % of the water intake sites previously identified by technicians (without the support of AGRI) were found to be not feasible for gravity-driven irrigation. On the other hand, for the feasible water intake sites, AGRI was able to provide viable and shorter water transportation routes to farms in 70 % of the cases. Furthermore, AGRI was able to provide alternative feasible water intake sites for all considered farms, with correspondingly viable water transportation routes for 74 % of them. These results demonstrate AGRI’s potential to reduce time, costs and risk of failure associated with the development of low-cost irrigation systems, which becomes increasingly needed to support the livelihoods of some of the world’s most vulnerable populations.},

note = {IF},

keywords = {Agriculture, Geographic Information Systems (GIS)},

pubstate = {published},

tppubtype = {article}

}

@article{Trilles-Oliver2018,

title = {A Comprehensive IoT Node Proposal Using Open Hardware. A Smart Farming Use Case to Monitor Vineyards},

author = {Sergio Trilles-Oliver and Alberto González-Pérez and Joaquín Huerta-Guijarro},

doi = {10.3390/electronics7120419},

year  = {2018},

date = {2018-03-28},

journal = {Electronics},

volume = {7},

number = {12},

pages = {419},

abstract = {The last decade has witnessed a significant reduction in prices and an increased performance of electronic components, coupled with the influence of the shift towards the generation of open resources, both in terms of knowledge (open access), programs (open-source software), and components (open hardware). This situation has produced different effects in today’s society, among which is the empowerment of citizens, called makers, who are themselves able to  generate citizen science or build assembly developments. Situated in the context described above, the current study follows a Do-It-Yourself (DIY) approach. In this way, it attempts to define a conceptual design of an Internet of Things (IoT) node, which is reproducible at both physical and behavioral levels, to build IoT nodes which can cover any scenario. To test this conceptual design, this study proposes a sensorization node to monitor meteorological phenomena. The node is called SEnviro (node) and features different improvements such as: the possibility of remote updates using Over-the-Air (OTA) updates; autonomy, using 3G connectivity, a solar panel, and applied energy strategies to prolong its

life; and replicability, because it is made up of open hardware and other elements such as 3D-printed pieces. The node is validated in the field of smart agriculture, with the aim of monitoring different meteorological phenomena, which will be used as input to disease detection models to detect possible diseases within vineyards.},

note = {IF: },

keywords = {Agriculture, crop monitoring, Internet of things, senviro},

pubstate = {published},

tppubtype = {article}

}

@article{7898821,

title = {Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale},

author = {Lorenzo Busetto and Sven Casteleyn and Carlos Granell-Canut and Monica Pepe and M. Barbieri and M. Campos-Taberner and R. Casa and F. Collivignarelli and R. Confalonieri and A. Crema and F. J. García-Haro and L. Gatti and I. Z. Gitas and Alberto González-Pérez and G. Grau-Muedra and T. Guarneri and F. Holecz and D. Katsantonis and C. Minakou and Ignacio Miralles-Tena and E. Movedi and F. Nutini and V. Pagani and A. Palombo and F. D. Paola and S. Pascucci and S. Pignatti and A. Rampini and L. Ranghetti and E. Ricciardelli and F. Romano and D. G. Stavrakoudis and D. Stroppiana and M. Viggiano and M. Boschetti},

doi = {10.1109/JSTARS.2017.2679159},

issn = {1939-1404},

year  = {2017},

date = {2017-04-13},

journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},

volume = {PP},

number = {99},

pages = {1-19},

keywords = {Agriculture, Data models, Electronic mail, ERMES, Europe, food industry, FPU_Miralles, Meteorology, modeling, Monitoring, Remote sensing, RyC-Casteleyn, RyC-Granell},

pubstate = {published},

tppubtype = {article}

}