Applications using estimates of forest parameters derived from satellite and forest inventory data

From the combination of optical satellite data, digital map data, and forest inventory plot data, continuous estimates have been made for several forest parameters (wood volume, age and biomass). Five different project areas within Sweden are presented which have utilized these estimates for a range of applications. The method for estimating the forest parameters was a ”k-Nearest Neighbor” algorithm, which used a weighted mean value of k spectrally similar reference plots. Reference data were obtained from the Swedish National Forest Inventory. The output was continuous estimates at the pixel level for each of the variables estimated. Validation results show that accuracy of the estimates for all parameters was low at the pixel level (e.g., for total wood volume RMSE ranged from 58-80%), with a tendency toward the mean, and an underestimation of higher values while overestimating lower values. However, when the accuracy of the estimates is assessed over larger areas, the errors are lower, with best results being 10% RMSE over a 100 ha aggregation, and 17% RMSE over a 19 ha aggregation. Applications presented in this paper include moose and bird habitat studies, county level planning activities, use as input information to prognostic programs, and computation of statistics on timber volume within drainage basins and smaller land holdings. This paper provides a background on the kNN method and gives examples of how end users are currently applying satellite-produced estimation data such as these

Development of model based sensors for the supervision of a solar dryer

Solar dryers are increasingly used in developing countries as an alternative to drying in open air, however the inherent variability of the drying conditions during day and along year drive the need for achieving low cost sensors that would enable to characterize the drying process and to react accordingly. This paper provides three different and complementary approaches for model based sensors that make use of the psychrometric properties of the air inside the drying chamber and the temperature oscillations of the wood along day. The simplest smart sensor, Smart-1, using only two Sensirion sensors, allows to estimate the accumulated water extracted from wood along a complete drying cycle with a correlation coefficient of 0.97. Smart-2 is a model based sensor that relays on the diffusion kinetics by means of assesing temperature and relative humidity of the air inside the kiln. Smart-2 model allows to determine the diffusivity, being the average value of D for the drying cycle studied equal to 5.14 × 10−10 m2 s−1 and equal to 5.12 × 10−10 m2 s−1 for two experiments respectively. The multidistributed supervision of the dryer shows up the lack of uniformity in drying conditions supported by the wood planks located in the inner or center of the drying chamber where constant drying rate kinetics predominate. Finally, Smart-3 indicates a decreasing efficiency along the drying process from 0.9 to 0.

Development of canopy vigour maps using UAV for site-specific management during vineyard spraying process

Site-specific management of crops represents an important improvement in terms of efficiency and efficacy of the different labours, and its implementation has experienced a large development in the last decades, especially for field crops. The particular case of the spray application process for what are called “specialty crops” (vineyard, orchard fruits, citrus, olive trees, etc.)FI-DGR grant from Generalitat de Catalunya (2018 FI_B1 00083). Research and improvement of Dosaviña have been developed under LIFE PERFECT project: Pesticide Reduction using Friendly and Environmentally Controlled Technologies (LIFE17 ENV/ES/000205)This research was partially funded by the “Ajuts a les activitats de demostració (operació 01.02.01 de Transferència Tecnològica del Programa de desenvolupament rural de Catalunya 2014-2020)” and an FI-DGR grant from Generalitat de Catalunya (2018 FI_B1 00083). Research and improvement of Dosaviña have been developed under the LIFE PERFECT project: Pesticide Reduction using Friendly and Environmentally Controlled Technologies (LIFE17 ENV/ES/000205).This research was partially funded by the “Ajuts a les activitats de demostració (operació 01.02.01 de Transferència Tecnològica del Programa de desenvolupament rural de Catalunya 2014-2020)” and an FI-DGR grant from Generalitat de Catalunya (2018 FI_B1 00083). Research and improvement of Dosaviña have been developed under LIFE PERFECT project: Pesticide Reduction using Friendly and Environmentally Controlled Technologies (LIFE17 ENV/ES/000205)Postprint (updated version

Selected bibliography of remote sensing

Bibliography of remote sensing techniques for analysis and assimilation of geographic dat

Development and evaluation on a wireless multi-gas-sensors system for improving traceability and transparency of table grape cold chain

There is increasing requirement to improve traceability and transparency of table grapes cold chain. Key traceability indicators including temperature, humidity and gas microenvironments (e.g., CO2, O2, and SO2) based on table grape cold chain management need to be monitored and controlled. This paper presents a Wireless Multi-Gas-Sensors System (WGS2) as an effective real-time cold chain monitoring system, which consists of three units: (1) the WMN which applies the 433 MHz as the radio frequency to increase the transmission performance and forms a wireless sensor network; (2) the WAN which serves as the intermediary to connect the users and the sensor nodes to keep the sensor data without delay by the GPRS remote transmission module; (3) the signal processing unit which contains embedded software to drive the hardware to normal operation and shelf life prediction for table grapes. Then the study evaluates the WGS2 in a cold chain scenario and analyses the monitoring data. The results show that the WGS2 is effective in monitoring quality, and improving transparency and traceability of table grape cold chains. Its deploy ability and efficiency in implantation can enable the establishment of a more efficient, transparent and traceable table grape supply chain.N/

The role of RFID in agriculture: Applications, limitations and challenges

The recent advances in RFID offer vast opportunities for research, development and innovation in agriculture. The aim of this paper is to give readers a comprehensive view of current applications and new possibilities, but also explain the limitations and challenges of this technology. RFID has been used for years in animal identification and tracking, being a common practice in many farms. Also it has been used in the food chain for traceability control. The implementation of sensors in tags, make possible to monitor the cold chain of perishable food products and the development of new applications in fields like environmental monitoring, irrigation, specialty crops and farm machinery. However, it is not all advantages. There are also challenges and limitations that should be faced in the next years. The operation in harsh environments, with dirt, extreme temperatures; the huge volume of data that are difficult to manage; the need of longer reading ranges, due to the reduction of signal strength due to propagation in crop canopy; the behavior of the different frequencies, understanding what is the right one for each application; the diversity of the standards and the level of granularity are some of them

Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture

[EN] The term "Agri-Food 4.0" is an analogy to the term Industry 4.0; coming from the concept "agriculture 4.0". Since the origins of the industrial revolution, where the steam engines started the concept of Industry 1.0 and later the use of electricity upgraded the concept to Industry 2.0, the use of technologies generated a milestone in the industry revolution by addressing the Industry 3.0 concept. Hence, Industry 4.0, it is about including and integrating the latest developments based on digital technologies as well as the interoperability process across them. This allows enterprises to transmit real-time information in terms behaviour and performance. Therefore, the challenge is to maintain these complex networked structures efficiently linked and organised within the use of such technologies, especially to identify and satisfy supply chain stakeholders dynamic requirements. In this context, the agriculture domain is not an exception although it possesses some specialities depending from the domain. In fact, all agricultural machinery incorporates electronic controls and has entered to the digital age, enhancing their current performance. In addition, electronics, using sensors and drones, support the data collection of several agriculture key aspects, such as weather, geographical spatialization, animals and crops behaviours, as well as the entire farm life cycle. However, the use of the right methods and methodologies for enhancing agriculture supply chains performance is still a challenge, thus the concept of Industry 4.0 has evolved and adapted to agriculture 4.0 in order analyse the behaviours and performance in this specific domain. Thus, the question mark on how agriculture 4.0 support a better supply chain decision-making process, or how can help to save time to farmer to make effective decision based on objective data, remains open. 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