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Insects are the most diverse group of animals on Earth, yet our knowledge of their diversity, ecology and population trends remains abysmally poor. Four major technological approaches are coming to fruition for use in insect monitoring and ecological research—molecular methods, computer vision, autonomous acoustic monitoring and radar-based remote sensing—each of which has seen major advances over the past years. Together, they have the potential to revolutionize insect ecology, and to make all-taxa, fine-grained insect monitoring feasible across the globe. So far, advances within and among technologies have largely taken place in isolation, and parallel efforts among projects have led to redundancy and a methodological sprawl; yet, given the commonalities in their goals and approaches, increased collaboration among projects and integration across technologies could provide unprecedented improvements in taxonomic and spatio-temporal resolution and coverage. This theme issue showcases recent developments and state-of-the-art applications of these technologies, and outlines the way forward regarding data processing, cost-effectiveness, meaningful trend analysis, technological integration and open data requirements. Together, these papers set the stage for the future of automated insect monitoring. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'. [ABSTRACT FROM AUTHOR]

The article focuses on several aspects involved for the preparation and implementation of an environmental monitoring program. It notes that the monitoring program aims at obtaining measurement result for parameters considering an evaluation as the ground for action. Furthermore, the evaluation criteria provide an effect that is critical on the performance of monitoring schemes which cover from the improvement of a strategy to the procedure utilized in measuring the gathered data.

The widespread application of pesticides in Morocco's agriculture renders their monitoring in food and environmental samples very necessary. Recent years have witnessed a growing interest in reporting studies related to the monitoring of pesticide residues in food, water, groundwater, and soil as well as their quantitative health risk assessment. Most published studies have been done by university researchers. However, the lack of research reproducibility remains a problem that considerably limits the possibility of exploiting data from the literature. Our study involves an extensive literature review utilizing search engines with keywords like "pesticide residues," "monitoring," "vegetables and fruits," "water and soil," "risk assessment," and "Morocco" from 2009 to 2023. Analysis of pesticide residues in foodstuffs and environmental samples highlights concerns over compliance with EU regulations, the health risks associated with pesticide exposure, and the necessity for comprehensive monitoring and risk assessment strategies. This paper could help influence policies to develop a strategy and action plan for the sound management of pesticides, including measures to reduce their use, raise awareness, and monitor compliance. Also, this paper could be useful for scientists interested in understanding the current situation and challenges regarding pesticide residues in Morocco, as well as countries with which commercial links exist. [ABSTRACT FROM AUTHOR]

This paper concerns the deployment problem of wireless sensor networks (WSNs) with mobile robotic sensor nodes for spatiotemporal monitoring. The proposed approach, deep reinforced learning tree (DRLT), utilizes deep reinforcement learning (DRL) to improve the efficiency of searching the most informative sampling locations. The parameterized sampling locations in an infinite horizon space are modeled according to their spatiotemporal correlations and subject to various constraints, including field estimation error and information gain. And the model-based information gain can be calculated efficiently over an infinite horizon. In this manner, the effectiveness of the sampling locations is learned through DRLT during the exploration by the robotic sensors. Then DRLT can instruct the robotic sensors to avoid unnecessary sampling locations in future iterations. Also, it is proved in this paper that the proposed algorithm is capable of searching for the near-optimal sampling locations effectively and guaranteeing a minimum field estimation error. Simulation based on national oceanic and atmospheric administration (NOAA) datasets is presented, which demonstrates the significant enhancements made by the proposed algorithm. Compared with the traditional approaches, such as the information theory-based greedy approach or random sampling, the proposed method shows a superior performance with regard to both estimation error and planning efficiency. [ABSTRACT FROM AUTHOR]

Environmental noise has a negative impact on human health and well-being. Real-time noise monitoring for effective noise control and management helps to identify noise sources and areas with high noise pollution, and potential mitigation strategies in urban planning. This paper reports work with a pilot scale system that can continuously collect noise data to assess noise levels accurately for real-time monitoring of environmental noise, focusing on hardware and software aspects and potential applications. The system permits the transfer of measurement data to the central server computer, with storage and display there, with the code written using Python. This system includes Web integration, with open source technologies to provide data access, and is based on Wi-Fi communication and a Control Card with Wi-Fi technology. [ABSTRACT FROM AUTHOR]

Context: At present, many cities are facing severe water-resources problems caused by urbanisation. With the development of remote sensing and geostatistics, they have been widely used in urban water-resource monitoring. Aims: To review and summarise the application of remote sensing and geostatistics in monitoring urban water resources and prospect for their furtherdevelopment. Methods: First, bibliometrics was used to analyse the existing literature in this field. We then discuss the use of remote sensing and geostatistics to improve urban water-resources monitoring capacity, focusing on the classification of technologies and equipment and their applications in urban surface-water and urban groundwater monitoring. Finally, a look at the future research direction is taken. Conclusions: In the past decade, the relevant research has shown an upward trend. The use of remote sensing and geostatistics can improve the city's water-resource monitoring capacity, thereby promoting better use of water resources in cities. Implications: In the future, with the development and addition of deep learning, remote-sensing and geographic-analysis systems can be used to conduct remote-sensing monitoring and data analysis on urban water resources more accurately, intelligently, and quickly, and improve the status of urban water resources. Urbanisation leads to water-resource problems; monitoring of urban water resources is needed for urban development. This paper systematically introduces the application of geostatistics and remote sensing for monitoring urban water resources. We used bibliometrics to analyse the existing literature, discussed the use of remote sensing and geostatistics to improve urban water-resource monitoring capacity. It is obvious that improving the accuracy of urban water-resource monitoring is needed, so as to promote the city to use water resources better. [ABSTRACT FROM AUTHOR]

The recent widespread and recurrent coral bleaching events over the Great Barrier Reef, the largest coral reef system on Earth and a hotspot of marine biodiversity, are a reminder of the vulnerability of reef ecosystems to human activities and a warming world. Protection of the Great Barrier Reef and similar reef ecosystems across Oceania requires a better understanding of environmental and socio-economic pressures, as well as the development of integrated management strategies. The rapid expansion of Earth Observation technologies and data has greatly advanced our capability to map and monitor reef habitats, ecological processing and exposure risk, providing spatially rich data essential to support and evaluate management and conservation strategies. However, these technologies are proportionally still under-utilized, and it is important to synthesise remote-sensing-derived tools and methods currently available for mapping reef ecosystems in Oceania to facilitate their intake in coral reefs studies. Publications in this Special Issue contribute toward filling this gap and explore recent advances in remote sensing of the Great Barrier Reef and other reef ecosystems in Oceania, from novel methodological approaches (sensors, algorithm development and improved thematic classification) to applications for environmental monitoring and management. [ABSTRACT FROM AUTHOR]

Community-based monitoring (CBM) is a widely used form of scientific data collection in which local community members directly participate in ecosystem research and also help the process by sharing traditional ecological knowledge and local understanding of land and resources. This paper presents a review of the challenges and opportunities associated with CBM projects in Canada and internationally. While Canadian cases are the primary focus, international examples are drawn on to provide additional context. Based on our review of 121 documents and publications, we found that CBM helps fill science research gaps by providing access to continuous data sets on the ecosystems being studied. CBM also increases the credibility of the data among users, as the community itself takes part in the environmental monitoring process. CBM supports cross-cultural learning and the co-production of knowledge by using traditional ecological knowledge with science, thereby enabling researchers, scientists and community members to learn from one another. Our review suggests that although there are multiple successes, CBM faces several challenges that constrain its progress including funding shortages, lack of support for local stewardship, and inadequate training for local users in the operation of equipment and data collection methods. Data sharing and rights on the use of data are also constraining to the long-term success of CBM programs. [ABSTRACT FROM AUTHOR]

With the rapid development of modern industries, more and more risk factors exist in industrial operations, leading to a gradual increase in the frequency of industrial failures. The industrial enterprises have taken a variety of measures to analyze the risk factors in industrial operations, but establishing an effective monitoring and evaluation system remains a technical challenge. To overcome this challenge, a practical industrial risk monitoring system, based on the wireless sensor network (WSN), is established in this paper to improve resilience of the respective industrial operations. In the proposed system, the existing sensor nodes in the industrial environment are organized into WSN to transmit real-time data. A special inspection robot is used to monitor comprehensively the environmental and safety risk factors in the industrial environment. To obtain the location of the robot, the partial nodes of the WSN are organized dynamically as the anchor nodes of the localization system, and two grid cumulative probability localization (GCPL) algorithms are proposed based on the GCPL-circle intersection and GCPL-path loss methods, respectively. The GCPL algorithm determines the grid cumulative probability using prior location information of the target node and the received signal strength information between the anchor nodes and target node to locate the target node. Experimental results show that the two GCPL algorithms significantly improve the localization accuracy and stability, and hence can be implemented as a risk monitoring system for real-world applications. Note to Practitioners—In industrial operations, a lot of risk factors exist which result in many frequent operational disruptions and failures. It is hence critical to develop an effective risk monitoring and evaluation system. Motivated by the industrial needs, we develop in this paper a practical wireless sensor network (WSN)-based industrial risk monitoring system. In the system, the existing sensor nodes in the industrial environment are organized into WSN to transmit real-time data. A special inspection robot is used to monitor comprehensively the environmental and safety risk factors in the industrial environment. To obtain the location of the robot, the partial nodes of the WSN are organized dynamically. We further propose two grid cumulative probability localization algorithms to establish the system. We show via computational experiments that the proposed risk monitoring system performs well and can be implemented as a real application which helps to improve risk management of industrial operations. [ABSTRACT FROM AUTHOR]

Purpose. To develop a data acquisition which is optimized for suitable purposes in monitoring/warning or decision-making assistance in the field of geography accident in mining activities or agroforestry. Methodology. In activities related to mining, agroforestry and environmental monitoring, many climate factors must be taken into account including humidity, soil moisture or level of rainfall. Those data play a key role in pre-warning or assisting in decision-making for operators who are responsible for risk warning. In this paper, we present an optimized data acquisition system which is reasonable in cost, simple and easy in installation. The system includes a sensor station (SS) and a central station to collect data from specified monitoring points. The latter one is used to gather data from SS through a new and optimized Lora WAN communication system. When sending gathered data to a cloud sever, an assistant system based on 3G module is established to warn of abnormal scenarios of the mining procedure or environmental parameters. The system is experimented, tested and implemented in the North Mountain area (Northwest) of Vietnam. Findings. A development of an acquisition system with optimized-data for alarming/warning and monitoring in the field of geography accident, mining activities and environment. The system could get sensing signal in both direct way and indirect way despite of bad weather. Originality. An improved Dijkstra algorithm is implemented to optimize and simulate the routing paths of a network. The optimization could show the best way for getting signal from sensor station indirectly to other ones, then to the central station. Practical value. A simple, reasonable-cost and easy-installation system is formed for monitoring, risk warning in the field of geography, mining, and climate. [ABSTRACT FROM AUTHOR]

In this paper, the implementation of a Wireless Sensor Network (WSN) for environmental monitoring (EM) is presented. It includes the design, implementation and experimental characterization of a multi-sector base station (BS) antenna composed of several microstrip Quasi-Yagi elements and the implementation and experimental characterization of a reduced form factor antenna for the sensor nodes (SN). Subsequently, it reports the implementation of a WSN based on Lopy4 transceivers, using the developed BS and SN antennas. Finally, experimental results obtained on the field to evaluate the performance of the network in terms of maximum coverage distance and coverage area are presented. According to the field tests, the connectivity between the sensor nodes and the developed WSN base station is confirmed at distances above 3.5 km and for all the antenna sectors of the multi-sector BS attaining a 360 ° of field of view. [ABSTRACT FROM AUTHOR]

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Monitoring studies at the base site, the Aktru glacier basin (Severo-Chuisky glaciation center, central Russian Altai Mountains), have been ongoing for 22 years and correspond to the global focus of scientific efforts on the study of mountain ecosystems. This article describes the main approaches to monitoring mountain ecosystems and their climatic response based on the leading role of their autotrophic block, especially edificator species of Altai forest ecosystems: Siberian larch and Siberian stone pine. This paper presents the main results of monitoring in old-growth forests, the forest–tundra ecotone, and ecosystems emerging on young moraines of valley glaciers. The authors provide information about the life forms of Siberian stone pine and Siberian larch, the structure of forest stands, and the species diversity of communities. The formation of tree generations in the course of supersecular warming/cooling cycles and the relationship of tree growth with secular and intrasecular climatic changes are considered; a comparative analysis of seed cone production in forests and ecotones is carried out. The current position of the tree lines (groups and single trees, reproductive) in the forest–tundra ecotone is considered, and their shift upwards the slopes as a response to climate change is found. The course of primary successions on young moraines of the Maly Aktru and Levy Bolshoi Aktru glaciers is described. [ABSTRACT FROM AUTHOR]

In this paper, we review the evolution of environmental monitoring, from its earliest days of exploration and increasing understanding of ecosystems and environment through the development of models and similar tools, to the current application of monitoring to assess project achievements. We note that information gathered through environmental monitoring is critical in evaluating the applicability of models and the accuracy of remotely-sensed information, and supporting the role of citizen science in the acquisition of environmental data. As monitoring increasingly is applied to project management, we identify the nexus between environmental and project management as needing to have purpose; observing that the purpose of monitoring evolves over time. This evolution is supported by the evaluation or assessment of the data—environmental and management related—over time, making monitoring and evaluation foundational for sound environmental management, restoration, protection, conservation, and understanding of ecosystem values. [ABSTRACT FROM AUTHOR]

Legal and policy initiatives to address the environmental dimensions of armed conflicts and their impact on people, ecosystems and sustainable development are highly dependent on the availability of environmental data from conflict-affected areas. Socio-political and security conditions in these areas often impede data collection, while traditional models of post-conflict environmental assessments are limited in scope. In response, an increasing range of actors is utilising remote sensing and open source data collection to identify and estimate health and ecological risks during and after conflicts. This paper considers the role of participatory citizen science methodologies in complementing both remote monitoring and post-conflict assessments. It examines existing models and mechanisms for environmental data collection and utilisation in conflict contexts, and the extent to which the core values and principles of citizen science are transferable. We find that 'civilian science' is feasible and could be well-suited to conflict conditions. In addition to addressing gaps in data collection, it may also empower communities affected by environmental degradation, enhance their environmental human rights, supplement the often limited monitoring capacity of governmental agencies and facilitate cooperation and peacebuilding. The paper concludes by proposing methodological approaches for three common forms of environmental degradation associated with armed conflicts. [ABSTRACT FROM AUTHOR]

Accurate rainfall monitoring is important, and previously it has been shown that microwave backhaul link between adjacent base station towers can be used for rainfall estimation. However, with the deployment of 5G using millimeter technology, there is opportunity for dense rainfall monitoring network using both backhaul and data transmission links. This paper presents our millimeter-wave measurement results during rainy days in Beijing, China. Our measurement design is an exemplary line-of-sight transmission link. We show that it is possible to retrieve the path-averaged rain rate from the measurement and to use both millimeter-wave transmission link and backhaul link to assist rainfall monitoring. Compared to the local rain measurement from rain gauge and disdrometer, we show that the correlation value of millimeter-wave link retrieved average rain rate varies between 0.6 and 0.9 for different rainfall events. There is room for improvement, and we find that if we can monitor the received signal for a sufficiently long period of time, we can quantify the bias due to fading and work out a better estimate of the rain retrieval model's reference level. [ABSTRACT FROM AUTHOR]

Coralligenous reefs represent one of the most important coastal ecosystems of the Mediterranean Sea, and their ecological quality must be assessed under the Marine Strategy Framework Directive to evaluate seafloor integrity. An effective standardized monitoring protocol is urgently needed in order to compare data at the Mediterranean scale and to plan efficient management and intervention programmes.This paper aims to: (a) review methods used to study shallow coralligenous reefs to propose a method able to optimize sampling effort; (b) select the most effective ecological descriptors to evaluate the responses of coralligenous assemblages to anthropogenic stress; and (c) synthesize available information in an integrated and standardized procedure.Ninety‐five scientific papers dealing with shallow coralligenous reefs were found. Among these, 52 papers reporting detailed descriptions about sampling methods were selected to identify methodologies and ecological descriptors suitable for monitoring purposes.Downstream of the bibliographic review, an integrated and standardized procedure, named STAR (STAndaRdized coralligenous evaluation procedure), was proposed to assess the ecological quality of coralligenous reefs.STAR was tested on coralligenous reefs at 12 sites, six of them subjected to high human pressure and six located in areas characterized by low human pressure.Significant differences between the two conditions were detected for all the ecological descriptors selected, thus confirming the effectiveness of STAR in the assessment of ecological quality of coralligenous reefs. [ABSTRACT FROM AUTHOR]

Distributed and decentralized sensing offers a new and promising paradigm for surveillance, reconnaissance, and situation awareness. This paper introduces a new fully decentralized decision-making platform referred to as environmental monitoring station (EMS) for sensor-level detection, classification, and tracking of acoustic airborne sources in national parks. This custom-designed field-programmable gate array-based platform allows for near real-time transient source detection and classification using the 1/3 octave spectral data extracted locally from the streaming acoustic data. Source tracking through successive angle-of-arrival (AoA) estimation is also implemented locally on the EMS system using an array of microphones. The general headings of the sources generated using the AoA history and the source labels are transmitted to a park station via two possible wireless links. Field test results are provided to evaluate the performance of the overall system. [ABSTRACT FROM AUTHOR]

This paper presents the EcoChip, a new system based on the state-of-the-art electro-chemical impedance (EIS) technologies allowing the growth of single strain organisms isolated from northern habitats. This portable system is a complete and autonomous wireless platform designed to monitor and cultivate microorganisms directly sampled from their natural environment, particularly from harsh northern environments. Using 96-well plates, the EcoChip can be used in the field for real-time monitoring of bacterial growth. Manufactured with high-quality electronic components, this new EIS monitoring system is designed to function at a low excitation voltage signal to avoid damaging the cultured cells. The high-precision calibration network leads to high-precision results, even in the most limiting contexts. Luminosity, humidity, and temperature can also be monitored with the addition of appropriate sensors. Access to robust data storage systems and power supplies is an obvious limitation for northern research. That is why the EcoChip is equipped with a flash memory that can store data over long periods of time. To resolve the power issue, a low-power micro-controller and a power management unit control and supply all electronic building blocks. Data stored in the EcoChip's flash memory can be transmitted through a transceiver whenever a receiver is located within the functional transmission range. In this paper, we present the measured performance of the system, along with results from laboratory tests in vitro and from two field tests. The EcoChip has been utilized to collect bio-environemental data in the field from the northern soils and ecosystems of Kuujjuarapik and Puvirnituq, during two expeditions, in 2017 and 2018, respectively. We show that the EcoChip can effectively carry out EIS analyses over an excitation frequency ranging from 750 Hz to 10 kHz with an accuracy of 2.35%. The overall power consumption of the system was 140.4 mW in normal operating mode and 81 μW in sleep mode. The proper development of the isolated bacteria was confirmed through deoxyribonucleic acid sequencing, indicating that bacteria thrive in the EcoChip's culture wells while the growing conditions are successfully gathered and stored. [ABSTRACT FROM AUTHOR]

Inspecting and monitoring oil-gas pipelines, roads, rivers, and canals are very important in ensuring the reliability and life expectancy of these civil systems. An autonomous unmanned aerial vehicle (UAV) can decrease the operational costs, expedite the monitoring process, and be used in situations where a manned inspection is not possible. This paper addresses the problem of monitoring these systems using an autonomous UAV based on visual feedback. A single structure detection algorithm that can identify and localize various structures including highways, roads, and canals is presented in the paper. A fast learning algorithm that requires minimal supervision is applied to obtain detection parameters. The real time detection algorithm runs at 5 Hz or more with the onboard video collected by the UAV. Both hardware simulations and flight results of the vision-based control algorithm are presented in this paper. A fixed wing UAV equipped with a camera onboard was able to track a 700 m canal based on vision several times with an average cross-track error of around 10 m. [ABSTRACT FROM AUTHOR]

This paper presents the development of a cyber-physical system that monitors the environmental conditions or the ambient conditions in indoor spaces at remote locations. The communication between the system’s components is performed using the existent wireless infrastructure based on the IEEE 802.11 b/g standards. The resulted solution provides the possibility of logging measurements from locations all over the world and of visualizing and analyzing the gathered data from any device connected to the Internet. This work encompasses the complete solution, a cyber-physical system, starting from the physical level, consisting of sensors and the communication protocol, and reaching data management and storage at the cyber level. The experimental results show that the proposed system represents a viable and straightforward solution for environmental and ambient monitoring applications. [ABSTRACT FROM PUBLISHER]

The purpose of the study described in this paper is aimed at identifying the environmental situation of the agroecosystem and studying the impact of resource-saving technology methods for the cultivation of oilseed rapeseed, ensuring sustainability and productivity of the agroecosystem during environmental monitoring. The object of the study was spring rapeseed of the Maily variety. Experimental studies were carried out using the generally accepted classical techniques, such as experiment and observation, in the form of a multifactorial field experiment. A two-factor field experiment was laid out by the split plots method and based on the methodology for conducting field experiments with oilseeds. The results of the study were obtained using the methods of a soil-protective agriculture system based on the principles of soil protection technology. The studied minimal tillage provides a reduction in the amount of mechanical impact on the soil, restoration and preservation of soil fertility, improvement of moisture supply by leaving the plant stubble and scattering chopped straw after harvesting the previous crop, and replacing deep moldboard tillage with shallow flat-cut tillage. On the basis of the obtained study results, it was proven that the replacement of energy-intensive moldboard tillage with shallow flat-cut tillage (mini-till), ensuring the rational use of soil resources and resource-energy conservation, was feasible. The reconstructed parameters of agrophysical factors of soil fertility were determined, such as density, aggregate composition, and the structure and water resistance of soil aggregates, which ensured the sustainability of the environmental situation of the agroecosystem. It has been established that the soil protection methods of resource-saving rapeseed cultivation technology mitigate the risk and optimize the conditions for the growth and development of crops, where productivity increases to 21.3%, and also provide 29.3 thousand tenges/ha of additional income from each hectare with an increase in the profitability of rapeseed cultivation to 97% and 108% under the conditions of South-East Kazakhstan. [ABSTRACT FROM AUTHOR]

Upon tightening new regulations, the demand for using smart wireless sensing for health, safety, and surveillance applications of nuclear installations is growing rapidly. To help with the developments, this paper describes the design of a practical small-scaled wireless sensor network (WSN) that allows a smart real-time monitoring of radiation levels at nuclear facilities. A wireless system compiled with a radiation sensor and associated peripherals been developed and implemented upon ZigBee technology using TI CC2530 chip. The radiation sensor uses a Geiger Muller tube as a reliable detector for the radioactive particulates in the gaseous effluent vented from nuclear facilities. The WSN allows the operators to record and control the radiation levels emitted to the environment and it is supported with a warning system, for the early detection of radiation release. However, building a reliable wireless sensing system with an effective coverage, especially for indoor applications, requires professional planning and proper investigation. In this paper, a procedure to investigate the wireless sensing coverage is reported where a ray-tracing simulator is adopted to enable the wireless node placement prior to the deployment. A real test scenario has been implemented based on the built wireless node to examine network coverage inside a 60-m hallway and results have been compared with simulations showing a 100% packet reception ratio. [ABSTRACT FROM PUBLISHER]

This paper evaluates two alternative regression techniques for oceanic chlorophyll-a (Chl-a) content estimation. One of the investigated methodologies is the recently introduced Gaussian process regression (GPR) model. We explore two feature ranking methods derived for the GPR model, namely sensitivity analysis (SA) and automatic relevance determination (ARD). We also investigate a second regression method, the partial least squares regression (PLSR) for oceanic Chl-a content estimation. Feature relevance in the PLSR model can be accessed through the variable importance in projection (VIP) feature ranking algorithm. This paper thus analyzes three feature ranking models, SA, ARD, and VIP, which are all derived from different fundamental principles, and uses the ranked features as inputs to the GPR and PLSR to assess regression strengths. We compare the regression performances using some common performance measures, and show how the feature ranking methods can be used to find the lowest number of features to estimate oceanic Chl-a content by using the GPR and PLSR models, while still producing comparable performance to the state-of-the-art algorithms. We evaluate the models on a global MEdium Resolution Imaging Spectrometer matchup dataset. Our results show that the GPR model has the best regression performance for most of the input feature sets we used, and our conclusion is this model can favorably be used for Chl-a content retrieval, already with two features, ranked by either the SA or ARD methods. [ABSTRACT FROM PUBLISHER]

Management of resource consumption in residential areas should take into account advances in the concept of Community Energy Management Systems, in which communities are involved in the monitoring and coordination of resource consumption. This paper presents a monitoring environment enabling the provision of monitoring and negotiation rules among residential users in order to minimize dispersion in total power consumption. It establishes mechanisms of detection of inconsistencies based on Linear Temporal Logic rules and mechanisms based on publication-subscription for transfer of quota among neighbors. The system is implemented and validated in a home environment. [ABSTRACT FROM PUBLISHER]

In this paper, we describe the investigations and actions taken to reduce risk and prevent casualties from a catastrophic 210,000 m rockslope failure, which occurred near the village of Preonzo in the Swiss Alps on May 15, 2012. We describe the geological predisposition and displacement history before and during the accelerated creep stage as well as the development and operation of an efficient early warning system. The failure of May 15, 2012, occurred from a large and retrogressive instability in gneisses and amphibolites with a total volume of about 350,000 m, which formed an alpine meadow 1250 m above the valley floor. About 140,000 m of unstable rock mass remained in place and might collapse partially or completely in the future. The instability showed clearly visible signs of movements along a tension crack since 1989 and accelerated creep with significant hydromechanical forcing since about 2006. Because the active rockslide at Preonzo threatened a large industrial facility and important transport routes located directly at the toe of the slope, an early warning system was installed in 2010. The thresholds for prealarm, general public alarm, and evacuation were derived from crack meter and total station monitoring data covering a period of about 10 years, supplemented with information from past failure events with similar predisposition. These thresholds were successfully applied to evacuate the industrial facility and to close important roads a few days before the catastrophic slope failure of May 15, 2012. The rock slope failure occurred in two events, exposing a compound rupture plane dipping 42° and generating deposits in the midslope portion with a travel angle of 39°. Three hours after the second rockslide, the fresh deposits became reactivated in a devastating debris avalanche that reached the foot of the slope but did not destroy any infrastructure. The final run-out distance of this combined rock collapse-debris avalanche corresponded to the predictions made in the year 2004. [ABSTRACT FROM AUTHOR]

The abrupt event monitoring is a challenging and critical issue in water environment systems. There are two main different abrupt events in the monitoring system, namely, the emergency water pollution accident and the abrupt sensor fault. The two different abrupt events have similar data characteristics, and few methods can be used to recognize the events. In this paper, a novel abrupt event monitoring approach based on kernel principal component analysis (KPCA) and support vector machines is proposed, which is combined with the physical redundancy method. The trust mechanism is introduced into the proposed approach to reduce the interference of external noise and improve the performance of quick response for the abrupt events. A spare data area is set up to store the data for the KPCA modeling. The data in the spare data area are updated continuously, and the KPCA model is updated subsequently to improve the adaptivity of the KPCA model for the abrupt event monitoring. The experimental results show that the proposed approach is capable of detecting and recognizing the two different abrupt events efficiently. [ABSTRACT FROM PUBLISHER]

The advent of routine collection of high-quality digital photography provides for traditional uses, as well as “remote sensing” uses such as the monitoring of environmental indicators. A well-devised monitoring system, based on consistent data and methods, provides the opportunity to track and communicate changes in features of interest in a way that has not previously been possible. Data that are geometrically and radiometrically consistent are fundamental to establishing systems for monitoring. In this paper, we focus on models for the radiometric calibration of mosaics consisting of thousands of images. We apply the models to the data acquired by the Australian Commonwealth Scientific and Industrial Research Organisation and its partners as part of regular systematic acquisitions over the city of Perth for a project known as Urban Monitor. One goal of the project, and hence the model development, is to produce annually updated mosaics calibrated to reflectance at 0.2-m ground sample distance for an area of approximately 9600 \km^2. This equates to terabytes of data and, for frame-based instruments, tens of thousands of images. For the experiments considered in this paper, this requires mosaicking estimates derived from 3000 digital photographic frames, and the methods will shortly be expanded to 30 000+ frames. A key part of the processing is the removal of spectral variation due to the viewing geometry, typically attributed to the bidirectional reflectance distribution function (BRDF) of the land surface. A variety of techniques based on semiempirical BRDF kernels have been proposed in the literature for correcting the BRDF effect in single frames, but mosaics with many frames provide unique challenges. This paper presents and illuminates a complete empirical radiometric calibration method for digital aerial frame mosaics, based on a combined model that uses kernel-based techniques for BRDF correction and incorporates additive and multiplicative terms for correcting other effects, such as variations due to the sensor and atmosphere. Using ground truth, which consists of laboratory-measured white, gray, and black targets that were placed in the field at the time of acquisition, we calculate the fundamental limitations of each model, leading to an optimal result for each model type. We demonstrate estimates of ground reflectance that are accurate to approximately 10%, 5%, and 3% absolute reflectances for ground targets having reflectances of 90%, 40%, and 4%, respectively. [ABSTRACT FROM AUTHOR]

The need for effective and rational use of land, protection, and preservation of its qualitative state (as the agricultural land soil) is due to some negative details, namely, more than a third of the land is eroded, half of which are black soil in particular, which have an average level of nutrient supply, a lot of contaminated abandoned or overdented land. The acuteness of this problem, which has developed with regard to the protection and preservation of the land qualitative state, has become particularly relevant. The solution to this problem requires truly effective methods of influence. One of such methods is the surveillance of ecological and economic monitoring of land. The article analyzes the ecological and economic factors and factors influencing the monitoring and surveillance of land in Ukraine. Perspectives and objectives for improvements in land monitoring are highlighted. The paper discloses a theoretical synthesis and new approaches to solving the problem of environmental management, which can participate in the development of innovative economic and environmental factors of rational land use, which will contribute to enhancing the transition of Ukraine to the model of sustainable land use. The purpose of this work is a scientific analysis of the various organizational factors of monitoring and surveillance of agricultural land in relation to the current legislation in Ukraine. [ABSTRACT FROM AUTHOR]

Project proponent‐ and government‐led environmental monitoring are required to identify, understand, and manage cumulative effects (CE), yet such monitoring initiatives are rarely mutually supportive. Notwithstanding the need for a more integrated and complementary approach to monitoring, monitoring efforts are often less effective than intended for addressing CE. This paper examines current monitoring programs in the Mackenzie Valley, Northwest Territories, Canada, based on 7 attributes: consistency, compatibility, observability, detectability, adaptability, accessibility, and usability. Results indicate a tenuous link between and across proponent‐led monitoring requirements under project‐specific water licenses and government‐led monitoring of regional baseline conditions. There is some consistency in what is monitored, but data are often incompatible, insufficient to understand baseline change, not transferable across projects or scales, inaccessible to end users, and ultimately unsuitable to understanding CE. Lessons from the Mackenzie Valley highlight the need for improved alignment of monitoring efforts across programs and scales, characterized by a set of common parameters that are most useful for early detection of cumulative change and supporting regulatory decisions at the project scale. This alignment must be accompanied by more open and accessible data for both proponents and regulators, while protecting the sensitivity of proprietary information. Importantly, there must be conceptual guidance for CE, such that the role of monitoring is clear, providing the types of CE questions to be asked, identifying the hypotheses to be tested, and ensuring timely and meaningful results to support regulatory decisions. © 2019 SETAC Key Points: There is significant variability in what is monitored, how it is monitored, and the accessibility of data in the Mackenzie Valley, Northwest Territories, Canada, limiting the usefulness of water quality monitoring results for understanding and assessing cumulative change.Government monitoring programs are coarse, focused on baseline conditions and detecting gross change; their precision and focus do not align with proponent needs for assessing baselines and the potential cumulative effects of their projects during regulatory reviews.Project proponents are likely to support a core set of parameters for monitoring, whether affected by their project or not, given that most water licenses already require monitoring for some combination of indicators for physical parameters, major ions, nutrients, and metals.Monitoring is necessary but not sufficient; conceptual guidance is needed on the fundamental nature, principles, and characteristics of cumulative effects, including how cumulative effects are interpreted, the types of decisions or actions they trigger, and the responsibility for managing them. [ABSTRACT FROM AUTHOR]

Most SEA practice and research has focused on the pre-decision stages, whereas post-decision follow-up stages such as monitoring, evaluation, and management have been given far less attention. These stages, referred to as SEA follow-up, are integral to making SEA effective and learning-oriented. This paper takes the first step towards a framework for conducting SEA follow-up, by analysing the requirements for ex post activities according to the European SEA Directive (2001/42/EC), reviewing existing experiences and literature on how to perform SEA follow-up, and exploring lessons to be learnt from the adjacent fields of EIA follow-up and policy evaluation. The directive, along with most mainstream applications of SEA, is based on EIA follow-up concepts. However, SEA follow-up displays a number of critical differences, including: an enhanced risk of implementation gaps; a focus on performance rather than compliance; and less direct linkages between decisions and impacts. The paper argues that the SEA Directive is seriously constrained and that a more ambitious interpretation of SEA follow-up is necessary to enable strategic decision making and learning. Lessons from the policy/programme evaluation literature could strengthen SEA follow-up by giving it analytical rigour in relation to establishing causality and providing insights into the use and acceptance of SEA follow-up among decision makers and stakeholders. Further explorations into policy evaluation toolkits, and practical experiences in applying them, are needed to enhance the potential of SEA follow-up in supporting strategic decision making. [ABSTRACT FROM AUTHOR]

The problem of measuring the electromagnetic (EM) exposure through a distributed, real-time, and inexpensive approach is addressed in this paper. A relocable and resilient system is proposed which combines: 1) the flexibility given by a wireless sensor network (WSN) backbone, enabling an high scalability and reconfigurability of the monitoring architecture; 2) the fidelity and robustness of an ad hoc designed three-axis field probe (mounted on each node in the WSN), which guarantees satisfactory measurement accuracy despite its compact, low consumption, and inexpensive nature (unlike traditional technologies for EM exposure assessment); and 3) also because of the self-tuning capabilities of the resulting architecture (which exploits the environmental parameters monitored by each node to consider the intrinsic thermal drifts in the field probe response). The proposed system is designed and experimentally validated in selected real-time scenarios, also in comparison with professional field probe solutions. The capability of the introduced architecture to implement cooperative communication strategies and to enable a reliable and fault-tolerant data transmission has been demonstrated, as well. [ABSTRACT FROM PUBLISHER]

As an extension of wireless sensor network in underwater environment, underwater acoustic sensor networks (UASNs) have caused widespread concern of academia. In UASNs, the efficiency and reliability of data transmission are very challenging due to the complex underwater environment in variety of ocean applications, such as monitoring abnormal submarine oil pipelines. Motivated by the importance of energy consumption in many deployments of UASNs, we therefore propose an energy-efficient data transmission scheme in this paper, called energy-efficiency grid routing based on 3D cubes (EGRCs) in UASNs, considering the complex properties of underwater medium, such as 3D changing topology, high propagation delay, node mobility and density, as well as rotation mechanism of cluster-head nodes. First, the whole network model is regarded as a 3D cube from the grid point of view, and this 3D cube is divided into many small cubes, where a cube is seen as a cluster. In the 3D cube, all the sensor nodes are duty-cycled in the media access control layer. Second, in order to make energy efficient and extend network lifetime, the EGRC shapes an energy consumption model considering residual energy and location of sensor nodes to select the optimal cluster-heads. Moreover, the EGRC utilizes residual energy, locations, and end-to-end delay for searching for the next-hop node to maintain the reliability of data transmission. Simulation validations of the proposed algorithm are carried out to show the effectiveness of EGRC, which performs better than the representative algorithms in terms of energy efficiency, reliability, and end-to-end delay. [ABSTRACT FROM PUBLISHER]

This paper describes the development of a system for decimetre-scale monitoring of land-surface and land-cover in urban and peri-urban environments. We describe our methodology that comprises the application of highly automated processing and analysis methods to digital aerial photography. The approach described in this paper addresses a monitoring need by providing the ability to generate change information at a spatial resolution suitable for urban, peri-urban and coastal areas, where an increasing percentage of the worlds’ population dwells. These areas are dynamic, with many environmental issues associated with planning, service provision, resource management and allocation, as well as monitoring regulatory compliance. We present a system based on standardised data and methods, which is able to track and communicate changes in features of interest in a way that has not been previously possible. We describe the methodology and then demonstrate its feasibility by applying it to geographic areas of planning and policy relevant size (the order of tens of thousands of square kilometres). We demonstrate the approach by applying it to the problem of urban forest assessment. [ABSTRACT FROM PUBLISHER]

Most existing query processing algorithms for wireless sensor networks (WSNs) can only deal with discrete values. However, since the monitored environment always changes continuously with time, discrete values cannot describe the environment accurately and, hence, may not satisfy a variety of query requirements, such as the queries of the maximal, minimal, and inflection points. It is, therefore, of great interest to introduce new queries capable of processing time-continuous data. This paper investigates curve query processing for WSNs as curve is an effective way to represent continuous sensed data. Specifically, a sensed curve derivation algorithm to support curve query processing in WSNs is first proposed. Then, the aggregation operation is employed as an example to illustrate curve query processing. The corresponding accurate and approximate aggregation algorithms are devised accordingly. We demonstrate that the energy cost of the approximate aggregation algorithm is optimal, provided that the required precision is satisfied. The theoretical analysis and experimental results indicate that the proposed algorithms can achieve high performance in terms of accuracy and energy efficiency. [ABSTRACT FROM AUTHOR]

Since 2012, the State Geological Institute of Dionýz Štúr has been carrying out tasks related to the monitoring of 309 environmental burdens. Following the article 4 by Kordík et al. (2019), this paper focuses on the results of groundwater and surface water quality monitoring in selected heavily polluted sites representing mainly industrial activities, waste management facilities and raw mineral extraction sites. Pollution from landfills is associated typically with the occurrence of high levels (above IT criteria) of boron, Cl-, NH4 + and conductivity. The highest content of TOC (1,460 mg.l-1) as an indicator of organic pollution was found at the site Komárno - area after the Soviet Army. Extremely high levels of CODMn (above 50 mg.l-1) were found among the sites of interest at the site Bojná - landfill - part A. Among the organic substances, chlorinated hydrocarbons (concentrations of cis 1,2-dichloroethene, dichloromethane, tetrachloroethene, trichloroethene and chloroethene above the IT criteria) appear to be problematic specifically within the industrial EB (Zlaté Moravce - Calex, Bratislava - Vrakuňa - CHZJD landfill, Bratislava - Chemika, Bratislava - Gumon, Čierna nad Tisou - transshipment station, Komárno - area after Soviet Army). Some trace inorganic elements (As, Sb, Cd, Cu, Ni, Zn), also due to the inclusion of mining sites in monitoring, exceeded IT criteria in groundwaters frequently. [ABSTRACT FROM AUTHOR]

Adaptive policies have emerged as a valuable strategy for dealing with uncertainties by recognising the capacity of systems to adapt over time to new circumstances and surprises. The efficacy of adaptive policies hinges on detecting on-going change and ensuring that actions are indeed taken if and when necessary. This is operationalised by including a monitoring system composed of signposts and triggers in the design of the plan. A well-designed monitoring system is indispensable for the effective implementation of adaptive policies. Despite the importance of monitoring for adaptive policies, the present literature has not considered criteria enabling the a-priori evaluation of the efficacy of signposts. In this paper, we introduce criteria for the evaluation of individual signposts and the monitoring system as a whole. These criteria are relevance, observability, completeness, and parsimony. These criteria are intended to enhance the capacity to detect the need for adaptation in the presence of noisy and ambiguous observations of the real system. The criteria are identified from an analysis of the information chain, from system observations to policy success, focusing on how data becomes information. We illustrate how models, in particular, the combined use of stochastic and exploratory modelling can be used to assess individual signposts, and the whole monitoring system according to these criteria. This analysis provides significant insight into critical factors that may hinder learning from data. The proposed criteria are demonstrated using a hypothetical case, in which a monitoring system for a flood protection policy in the Niger River is designed and tested. [ABSTRACT FROM AUTHOR]

In the context of the Water Framework Directive (WFD) and a comprehensive water protection in Slovakia it is necessary to address the problems related to point pollution sources (so called environmental burdens). Since 2012, several projects related to monitoring of environmental burdens are carried out by the State Geological Institute of Dionýz Štúr (SGIDŠ). The aim of the projects is to design and implement the monitoring programme for 309 environmental burdens in Slovakia, to identify leakage of pollutants into the environment and their extent and to assess the trends in concentrations of pollutants. The activities carried out are in line with the standard procedures applied in the EU countries and in line with the WFD and its Daughter Directive on Groundwater Protection, which constitute the basic legal framework for the implementation of the geological task. Monitoring carried out by SGIDŠ consists of several activities: processing of archival documents and data, building of conceptual models, designing of a monitoring programme, implementation of monitoring (sampling, field measurements and laboratory works), evaluation of monitoring results. Within the projects, a huge amount of data on water and rock environment quality have been collected and analysed. Monitoring programmes are compiled separately for each site based on the hydrogeological conceptual models. Number of proposed monitoring sites has essentially depended on the spatial extent of contamination, the number of pollution releases, type and distribution of contaminants, complexity of the hydrogeological structure and groundwater flow, behaviour of pollutants in the environment, access, sensitivity of the receptor at risk and legislative requirements. Obtained data and monitoring results contribute to a comprehensive and systematic management and gradual removal of environmental burdens as well as reduction of risks to human health and environment. The main principles and methods of monitoring of environmental burdens are discussed in the paper. [ABSTRACT FROM AUTHOR]

Increase of "greenhouse gases" level, rise caused by human activities, have artificially accentuated the greenhouse effect, resulting in increasing of global temperatures and disturbing climate. This paper analyzed the concentrations of three greenhouse gases recorded for Romania in 2011. The data come from European Environment Agency, Airbase. In the database of European Environment Agency, 2011 is the last year where there are data on greenhouse gas emissions. Annual average concentrations of analyzed greenhouse gases exceeded the thresholds in many cities around Romania especially in highly industrialized centers and large population cities. [ABSTRACT FROM AUTHOR]

Long-term stability of geotechnical structures is critical to any engineering design. Design of underground structures is initially planned using empirical approaches based on the rock mass-classification system. This design is mainly based on limited data obtained from boreholes and surface geological mapping. However, this design needs to be continuously updated based on the information gathered as the excavation work progresses. Over the last few years, geotechnical monitoring has emerged as a major engineering tool for engineers to review and update their existing design configuration based on the actual behavior of excavated rock mass. This paper presents a case study of the interaction of two large unlined rock caverns that were excavated using a drill-and-blast technique with a heading-down benching approach. The mechanical response of the two caverns was numerically modeled and studied in terms of the stress-deformation behavior of the excavated caverns and rock support installed, taking into account the actual sequence of heading and benching followed during parallel excavation activity at one of the construction sites. It was observed from the analysis that the crown/wall junction is sensitive to displacements under both good and fair rock-mass conditions. Limited comparative study was also carried out between the measured and calculated displacements; this showed encouraging results. Progressive buildup of forces in the rock bolts and development of the stresses in pillars were also studied as part of the interaction response of two caverns. [ABSTRACT FROM AUTHOR]

In many real tasks the features are evolving, with some features vanished and some other features being augmented. For example, in environment monitoring some sensors expired whereas some new ones were deployed; in mobile game recommendation some games dropped whereas some new ones were added. Learning with such incremental and decremental features is crucial but rarely studied, particularly when the data comes like a stream and thus it is infeasible to keep the whole data for optimization. In this paper, we study this challenging problem and present the OPID approach. Our approach attempts to compress important information of vanished features into functions of survived features, and then expand to include the augmented features. It is an one-pass learning approach, which only needs to scan each instance once and does not need to store the whole data, and thus satisfies the evolving streaming data nature. After tackling this problem in one-shot scenario, we then extend it to multi-shot case. Empirical study on a broad range of data sets shows that our approach can address this problem effectively. [ABSTRACT FROM AUTHOR]

Trichloroethene (TCE) and tetrachloroethene (PCE) are chemical compounds which pose a serious threat for human health. Their specific properties make it possible that these substances may linger in soil and water for many years. These are the reasons why wells with water designed for drinking purposes have been subject of monitoring since 2006. This paper presents the results of monitoring research conducted in the soil-water environment within the framework in third phase of an ecological audit of land. The ecological audit of land made it possible to identify the cause and degree of the degradation, and helped formulate rationale for remedy decisions pertaining to the land (remediation/reclamation). The objective of the paper was to determine the pollution status of the soil-water environment and, subsequently, monitor (in years 2008-2010) the contents of the hazardous substances, namely trichloroethene and tetrachloroethene, within the area of the potential impact of metallurgical plant located in borders of the Main Underground Water Reservoir Wierzbica-Ostrowiec (GZWP 420) in in voivodeship Świętokrzyskie. [ABSTRACT FROM AUTHOR]

Monitoring surveys allow managers to document system status and provide the quantitative basis for management decision-making, and large amounts of effort and funding are devoted to monitoring. Still, monitoring surveys often fall short of providing required information; inadequacies exist in survey designs, analyses procedures, or in the ability to integrate the information into an appropriate evaluation of management actions. We describe current uses of monitoring data, provide our perspective on the value and limitations of current approaches to monitoring, and set the stage for 3 papers that discuss current goals and implementation of monitoring programs. These papers were derived from presentations at a symposium at The Wildlife Society's 13th Annual Conference in Anchorage, Alaska, USA. [ABSTRACT FROM AUTHOR]

Abstract: Between 1950 and 1989, marine fisheries catch in the open‐ocean and deep‐sea beyond 200 nautical miles from shore increased by a factor of more than 10. While high seas catches have since plateaued, fishing effort continues to increase linearly. The combination of increasing effort and illegal, unreported and unregulated (IUU) fishing has led to overfishing of target stocks and declines in biodiversity. To improve management, there have been numerous calls to increase monitoring, control and surveillance (MCS). However, MCS has been unevenly implemented, undermining efforts to sustainably use high seas and straddling stocks and protect associated species and ecosystems. The United Nations General Assembly is currently negotiating a new international treaty for the conservation and sustainable use of biodiversity beyond national jurisdiction (BBNJ). The new treaty offers an excellent opportunity to address discrepancies in how MCS is applied across regional fisheries management organizations (RFMOs). This paper identifies ways that automatic identification system (AIS) data can inform MCS on the high seas and thereby enhance conservation and management of biodiversity beyond national jurisdictions. AIS data can be used to (i) identify gaps in governance to underpin the importance of a holistic scope for the new agreement; (ii) monitor area‐based management tools; and (iii) increase the capacity of countries and RFMOs to manage via the technology transfer. Any new BBNJ treaty should emphasize MCS and the role of electronic monitoring including the use of AIS data, as well as government–industry–civil society partnerships to ensure critically important technology transfer and capacity building. [ABSTRACT FROM AUTHOR]

Objective: This paper examines the integration of a noninvasive vital sign monitoring feature into the workers’ hearing protection devices (HPDs) by using a microphone positioned within the earcanal under the HPD. Methods: 25 test-subjects were asked to breathe at various rhythms and intensities and these realistic sound events were recorded in the earcanal. Digital signal processing algorithms were then developed to assess heart and breathing rates. Finally, to test the robustness of theses algorithms in noisy work environments, industrial noise was added to the in-ear recorded signals and an adaptive denoising filter was used. Results: The developed algorithms show an absolute mean error of 4.3 beats per minute (BPM) and 2.7 cycles per minute (CPM). The mean difference estimate is –0.44 BPM with a limit of agreement (LoA) interval of –14.3 to 13.4 BPM and 2.40 CPM with a LoA interval of –2.62 to 7.48 CPM. Excellent denoising is achieved with the adaptive filter, able to cope with ambient sound pressure levels of up to 110 dB SPL, resulting in a small error for heart rate detection, but a much larger error for breathing rate detection. Conclusion: Extraction of the heart and breathing rates from an acoustical measurement in the occluded earcanal under an HPD is possible and can even be conducted in the presence of a high level of ambient noise. Significance: This proof of concept enables the development of a wide range of noninvasive health and safety monitoring audio wearables for industrial workplaces and life-critical applications where HPDs are used. [ABSTRACT FROM AUTHOR]

Adaptation is increasingly recognised as essential when dealing with the adverse impacts of climate change on societies, economies and the environment. However, there is insufficient information about the effectiveness of adaption policies, measures and actions. For this reason, the establishment of monitoring programmes is considered to be necessary. Such programmes can contribute to knowledge, learning and data to support adaptation governance. In the European Union (EU), member states are encouraged to develop National Adaptation Strategies (NASs). The NASs developed so far vary widely because of differing views, approaches and policies. A number of member states have progressed to monitoring and evaluating the implementation of their NAS. It is possible to identify key elements in these monitoring programmes that can inform the wider policy learning process. In this paper, four generic building blocks for creating a monitoring and evaluation programme are proposed: (1) definition of the system of interest, (2) selection of a set of indicators, (3) identification of the organisations responsible for monitoring and (4) definition of monitoring and evaluation procedures. The monitoring programmes for NAS in three member states-Finland, the UK and Germany-were analysed to show how these elements have been used in practice, taking into account their specific contexts. It is asserted that the provision of a common framework incorporating these elements will help other member states and organisations within them in setting up and improving their adaptation monitoring programmes. [ABSTRACT FROM AUTHOR]

Increasingly, natural resource managers see the marine protected areas that they are responsible for as linked social-ecological systems. This requires an equal focus on managing for both natural and human dimensions of the protected estate. Consequently, identification of indicators that represent the human dimensions of Large Scale Marine Protected Areas (LSMPAs) such as the Great Barrier Reef (GBR) is critical if these values are to be properly considered as part of standard management practice. Assessment and monitoring of the human dimensions of LSMPAs requires a replicable, collaborative process, rolled out at local scales but comparable across vast, socially and geographically diverse areas. This paper explores the application of a process for the development, assessment, and monitoring of the GBR's human dimensions. The process includes (a) development of a conceptual framework that links indicator sets to the desired state of the GBR's human dimensions; and (b) a collaborative approach including ten practical steps to implement assessment, monitoring, and benchmarking of the human dimensions of an LSMPA. We conclude with examination of challenges and opportunities for implementing this process in the GBR context, specifically with respect to the targets and objectives of the Reef 2050 Long-Term Sustainability Plan. [ABSTRACT FROM AUTHOR]