Search

This article studies the monitoring of oak dieback in forests of the Centre-Val de Loire region (France), where drought-induced dieback has become a major concern due to climate change. The main objective of the study is to evaluate the applicability of multispectral satellite time series for operational monitoring of forest dieback. Using in situ data collected from 2017 to 2022 on approximately 2700 oak plots, a multiyear mapping of the analyzed region was performed using the random forest algorithm and Sentinel-2 images. Our results show that it is possible to detect oak dieback accurately (average overall accuracy = 80% and average balanced accuracy = 79%). A spatial cross-validation analysis also evaluates the performance of the model on regions that were never encountered during training, across all years, resulting in a slight decrease in accuracy ($\sim$5%). The study also highlights the importance of measuring the stability and performance of the classification model over time, in addition to standard cross-validation metrics. A feature analysis shows that the shortwave infrared part of the spectrum is the most important for mapping forest dieback, while the red-edge portion of the spectrum can increase the stability of the model over time. Overall, both in situ data and model predictions showed evidence of forest decline in many areas of the study region. Our results suggest that large areas of forest can decline over short periods of time, highlighting the interest of satellite data to provide timely and accurate information on forest status.

This research examines the potential of digital twin (DT) technology for reformation within China’s traditional solid-wood-panel processing industry, which currently suffers from production inefficiencies and the slow adoption of digital technology. The research centers around developing a digital twin system, elucidating improvements in manufacturing efficiency, waste management, process simulation, and real-time monitoring. These capabilities facilitate immediate problem solving and offer transparency in the process. The digital twin system is comprised of physical, transport, virtual, and application layers, employing a MySQL database and using the Open Platform Communications Unified Architecture (OPC UA) protocol for communication. The application of this system has led to heightened production efficiency and better material use in the solid-wood-panel manufacturing line. Integrating the dynamic selection adaptive genetic algorithm (DSAGA) into the virtual layer drives the system’s efficiency forward. This evolved approach has allowed for an enhancement of 8.93% in the scheduling efficiency of DSAGA compared to traditional genetic algorithms (GAs), thereby contributing to increased system productivity. Real-time mapping and an advanced simulation interface have strengthened the system’s monitoring aspect. These additions enrich data visualization, leading to better comprehension and a holistic process view. This research has ignited improvements in solid-wood-panel production, illustrating the tangible benefits and representing progress in incorporating digital technology into traditional industries. This research sets a path for transforming these industries into smart manufacturing by effectively bridging the gap between physical production and digital monitoring. Furthermore, the adjustability of this approach extends beyond solid-wood-panel production, indicating the capability to expedite movement towards intelligent production in various other manufacturing sectors.

The Online Monitoring System (OMS) at the Compact Muon Solenoid experiment (CMS) at CERN aggregates and integrates different sources of information into a central place and allows users to view, compare and correlate information. It displays real-time and historical information. The tool is heavily used by run coordinators, trigger experts and shift crews, to ensure the quality and efficiency of data taking. It provides aggregated information for many use cases including data certification. OMS is the successor of Web Based Monitoring (WBM), which was in use during Run 1 and Run 2 of the LHC. WBM started as a small tool and grew substantially over the years so that maintenance became challenging. OMS was developed from scratch following several design ideas: to strictly separate the presentation layer from the data aggregation layer, to use a well-defined standard for the communication between presentation layer and aggregation layer, and to employ widely used frameworks from outside the HEP community. A report on the experience from the operation of OMS for the first year of data taking of Run 3 in 2022 is presented.

The introduction of Synthetic Aperture Radar (SAR) through the Oceans and Coasts Monitoring Information system (OCIMS) has therefore become a critical tool for operational coastal and ocean monitoring in South Africa. Natural/man-made ocean phenomena can be observed using satellite Synthetic Aperture Radar (SAR) techniques, making it an integral part of large ocean area monitoring for maritime domain awareness. SAR is an active instrument on-board a satellite platform that transmits electromagnetic waves and measures the returning signal to infer what is happening on the ocean surface. The objective of this paper was to provide information and present options to the decision-makers around sustainability of commercial SAR data acquisition in support of OCIMS IVT. The OCIMS IVT tool identifies ships from multiple types of SAR data, which can provide locations of vessels that have switched off their AIS and oil slicks caused by vessels. Although open-data offerings, such as Sentinel-1, can be considered alternatives to commercial sensors, they present severe limitations for an operational service. To meet OCIMS requirements, and address the imperative to reduce costs, a hybrid of commercial acquisition being used in conjunction with an open data source such as Sentinel-1 is recommended. This would ensure that an operational service with the desired latency as well as increasing the revisit time over the EEZ.

An innovative approach for the automation of operational monitoring activities in agricultural and forestry tasks is described and discussed in this article. This approach can be considered as a solution for Precision Agriculture and Precision Forestry applications and can be used as an information and communication technology (ICT) tool for the management aims by a variety of agricultural and forestry companies. The aim of the proposed concept is to develop a system, composed of both hardware and software units, with the ability to collect and manage operative raw data and then to translate them into operational information that will be used in decision-making processes. All the procedures will be carried out automatically, in order to ensure an objective compilation of the field activity register. Thus, the entrepreneur will have all the operative information automatically updated in a dedicated database system. All the obtained documents can then be used for certification and traceability processes, if required by the procedural guideline, as well as to satisfy any other management tasks, including the estimation of the actual operative costs of the farm.

We analyze the efficacy of using a Do-It-Yourself (DIY) modular instrument to estimate the diffuse attenuation coefficient (Kd) of photosynthetically active radiation (PAR), which can be used for operational oceanography in turbid shallow waters. This parameter evaluates the water transparency, as it summarizes several water components providing an indicator for water quality. Historically, water transparency has been measured with a simple and inexpensive tool: the Secchi disk. Although it contributes a valuable index of visual water clarity, the quality of its measurements is user-dependent, and it does not enable the automatic monitoring of the water quality. For this reason, we need electronic devices to get accurate measures and facilitate long-term evaluations for water quality monitoring. This paper has two main objectives: First, to present the KduPRO, a low-cost and DIY moored instrument. The KduPRO is an evolution of the KdUINO buoy, that provides an estimation of the water transparency in coastal areas and continental waters, with an automatic quality control parameter that makes this sensor suitable for operational observing systems; and second, to provide a replicability analysis associated to the uncertainty of its Kd estimations. This instrument is based on a modular system of light sensors, independent of each other, measuring the irradiance at different depths. This study analyses the performance of the KduPRO with other reference commercial instruments, the performance between different modules of the same system and finally, a case study of measuring the water quality in Loch Leven (a lake in Scotland). The affordable cost, ease of use and measurement repeatability make this instrument a potentially valuable tool for anyone interested in monitoring water quality.

Desertification is one of the destructive phenomena in the human court that causes the destruction of natural resources. Since Iran is located on a dry and semi-arid belt, recognizing the phenomenon of desertification and the factors affecting its intensification in our country is very important. In this research, satellite image information was used to study the role of land use change on desertification phenomena in the study area in northern Khuzestan. In a 24-year statistical period, a desertification intensity map was prepared using the IMDPA model based on water, climate, vegetation and soil criteria. The land use map of the area was prepared for three periods of 1991, 2003 and 2015, including six landuses: agriculture, rang land, salt land, flaggy and river. The results of the desertification intensity map showed that the intensity of desertification was initially in the period from 1991 to 2003, so that in 1991, about 9.6% of the region was in the low desertification class and 90.4% of the region was in the middle deserification class. In addition, since 2003, severe desertification class has been observed, which includes 8.3% of the region, and low and medium classes have covered about 8.7% and 87.4% of the region, respectively. Moreover, in 2015, low, medium and severe classes include about 14.8, 85 and 0.1 percent of the total area, respectively. In addition, the numerical value of the intensity of desertification in each use and its comparison showed that the most effective effect was the use of pastures, agriculture and residential areas, respectively, and the least effect was the use of Nizar in desertification of the region. To better examine the relationship between desert risk indicators and land use change, different models were adapted to the obtained data, and among these models, the best model was used for each use and intensity of desertification. Among the various uses, according to the correlation coefficient, the best relationship between desertification intensity and land use change was the use of salt land with 0.29 = 96.

The authors showed that the imperfection of precision farming methods, methods of transferring energy from the tractor engine to the working bodies required the development of new methods for reliable and accurate identification of the soil and its properties, as well as the state of machine-tractor units. (Research purpose) To determine the actual energy and economic indicators of a working machine and unit reliably and promptly in the operating conditions of agricultural production by parameters closely related to the energy indicators of an internal combustion engine, the measurement of which did not require large costs. (Materials and methods) 24 indirect parameters reflecting the power and degree of engine load were used for the operational assessment. In this case, the angular accelerations of the internal combustion engine and the turbocharger rotor crankshaft, including those caused by the operation of individual cylinders, the working processes of the generator (their average and extreme values), as well as the amplitude-frequency spectra of these processes, and speed characteristics were taken into account. To improve the accuracy and reliability of the assessment of energy indicators, the authors selected the processes in the frequency and phase domains. (Results and discussion) The considered methods were tested in production conditions during the main processing of the alkaline-chernozem complexes of the Chulym district of the Novosibirsk region. The authors found that the use of a flexible machine-tractor unit based on an energy-rich tractor improved the quality of soil cultivation: the share of soil lumps less than 5 centimeters in size was 73-80 percent; the productivity of the tillage machine increased by 15-20 percent. (Conclusions) The authors proved that with the help of indirectly determined indicators of power and degree of load, it was possible to estimate the actual values of the energy and technical and economic indicators of the working machine and the unit, the quality of the assembly of the unit, the heterogeneity of the soil was much easier and cheaper than using the known force-measuring methods. It was found that the use of digital systems for automatic control of the unit using the indicated indicators made it possible to provide quite simply the setting of the optimal zone of energy modes.

The issues of image fusion in a two-position small-size radar on-board operational monitoring system are considered. The aim of present research is to develop a method for fusion of images of the land surface based on data obtained from a multi-sensor spatially distributed on-board location system implemented on the basis of a UAV. The method of combining different-angle location images is implemented iteratively. At each iteration, there is a search for pairs of points of the contour of the isolated areas. Areas are highlighted using two image segmentation methods. The final result is a proposed method for information fusion from a two-position on-board small-sized radar system and an optical location system. The implemented method of fusion makes it possible to increase the information content, quality and reliability of information about the observed underlying surfaces and the physical objects detected on them. The practical significance of the results obtained lies in the formation of integral information in real time in the interests of environmental reconnaissance, monitoring in hard-to-reach and dangerous places for human life, as well as in order to promptly prevent natural and man-made emergencies.

In 2017–2019, a seismic swarm was triggered in the Maurienne valley (French Alps), with more than 5000 events detected by the regional SISmalp network. The population, who asked SISmalp to provide information on the processes and the associated risk, felt many earthquakes. In a post-L’Aquila trial context, we conducted a reflection on the scientific and social operational management of the crisis. The geological and tectonic analysis, the deployment of a temporary seismic network, an automatic double-difference relocation procedure (HypoDD) after clustering earthquakes, as well as the interactions with the population and the risk managers, have been carried out jointly. The length and unpredictability of the sequence complicated crisis management and the relations between local authorities and civil protection. The involvement of SISmalp, beyond its main scientific and observation prerogatives, has contributed to moderate the fears of the population by providing scientific explanations.