An Operational Analysis Ready Radar Backscatter Dataset for the African Continent

Digital Earth Africa is now providing an operational Sentinel-1 normalized radar backscatter dataset for Africa. This is the first free and open continental scale analysis ready data of this kind that has been developed to be compliant with the CEOS Analysis Ready Data for Land (CARD4L) specification for normalized radar backscatter (NRB) products. Partnership with Sinergise, a European geospatial company and Earth observation data provider, has ensured this dataset is produced efficiently in the cloud infrastructure and can be sustained in the long term. The workflow applies radiometric terrain correction (RTC) to the Sentinel-1 ground range detected (GRD) product, using the Copernicus 30 m digital elevation model (DEM). The method is used to generate data for a range of sites around the world and has been validated as producing good results. This dataset over Africa is made available publicly as a AWS public dataset and can be accessed through the Digital Earth Africa platform and its Open Data Cube API. We expect this dataset to support a wide range of applications, including natural resource monitoring, agriculture, and land cover mapping across Africa.

An IoT-Based Services Infrastructure for Utility-Scale Distributed Solar Farms

Internet of Things (IoT) provides large-scale solutions for efficient resource monitoring and management. As such, the technology has been heavily integrated into domains such as manufacturing, healthcare, agriculture, and utilities, which led to the emergence of sustainable smart cities. The success of smart cities depends on the availability of data, as well as the quality of the data management infrastructure. IoT introduced numerous new software, hardware, and networking technologies designed for efficient and low-cost data transport, storage, and processing. However, proper selection and integration of the correct technologies is crucial to ensuring a positive return on investment for such systems. This paper presents a novel end-to-end infrastructure for solar energy analysis and prediction via edge-based analytics.

Transdisciplinary resource monitoring is essential to prioritize circular economy strategies in cities

Seeking to meet sustainability targets, cities are promoting a number of circular economy initiatives. Whether or not these actions help cities to approach sustainable resource management is often unclear. To identify, prioritize and monitor resource-efficient strategies, cities can look for targets and indicators among the Sustainable Development Goals (SDGs). While the SDGs provide useful goals, they lack applicable and accurate indicators for cities. To address this shortcoming, we link the SDGs to the urban circular economy by looking at the urban metabolism and identify monitoring needs and gaps. Although consumption-based footprint indicators are the most suitable approach, these are barely covered in the SDGs. We propose a framework facilitating transdisciplinary projects and experimentation to assess resource footprints and prioritize circular strategies in cities. Our discussion will guide practitioners and academics towards a sustainable circular transformation in cities.

Developing Integrated Smartphones Notification of Server Resource Monitoring System Using Zabbix, Webhook, and Telegram

Server monitoring activities are important to ensure the availability of resources used for the execution of its internal processes. Generally, Administrators monitor the use of server resources through a computer using a browser. The problem with monitoring through a computer is less flexible and slow for checking notifications about the state of problem server resources in real-time anytime and anywhere using smartphones. This study aims to develop notification integration on smartphones from a server resource monitoring system using Zabbix Webhook and Telegram. The research method used is the Cisco PPDIOO Lifecycle Approach to Network Design and Implementation. As a case study, it is located at the Center for Empowerment of Informatics and Nuclear Strategic Area, the National Nuclear Energy Agency. The results of the study are notifications on smartphones via the Telegram bot account indicating a problem with resource usage. The results of this study have been used by server Administrators. The server Administrators have provided information about the benefits of this system, for flexibility, speed of getting information in resource usage, identifying, and resolving problems before there are complaints so that the quality of service is getting better.

Genetic microbial faecal source tracking: rising technology to support future water quality testing and safety management

Recent developments in water resource monitoring have increased the demand for the reliable identification of faecal pollution sources, also defined as microbial (faecal) source tracking (MST). Standardized faecal indicator bacteria (SFIB) enumeration does not directly support MST, as SFIB occur in animal and human sources. The aim of this study was to rigorously evaluate the applicability of host-associated faecal genetic MST markers detected by quantitative PCR (qPCR) at representative Austrian water resources (ground-, surface-, raw and treated wastewater, n = 196 samples) with high importance for the water management sector. Groundwater covered a gradient of non- (i.e., deep wells) to surface influenced resources (i.e., karst and shallow wells). In addition, single faecal excreta from humans as well as representative livestock and wildlife species were collected to evaluate the faecal source-specificity and -sensitivity of the MST assays. Genetic MST marker resistance against UV irradiation was evaluated in on-site ground and wastewater treatment installations. Bacteroides-based human- (HF183II, BacHum), ruminant- (BacR), and pig-associated (Pig2Bac) MST marker qPCR quantification was performed in concert with cultivation of E. coli, intestinal enterococci, and Clostridium perfringens (SFIB diagnostics). The selected MST makers revealed high faecal source identification capacity for the Austrian water compartments and quantitatively reflected the selected faecal pollution gradient. The study also demonstrated that SFIB data can efficiently be combined with MST data to solve previously unanswered questions in water safety monitoring and management (e.g., support pollution source-targeted catchment protection, hazard assessment, and health risk management). Further research and development needs are discussed to exploit the full power of MST technology. In conclusion, this study illustrates the capacity of molecular faecal pollution diagnostics to revolutionize water quality testing in the decades to come.

Understanding uptake of community groundwater monitoring in rural Brazil

Resource monitoring is often cited as important for effective common pool resources management. In practice, not all monitoring interventions are successful, particularly when the resource, such as groundwater, is challenging to monitor and measure. We conducted a field experiment on groundwater monitoring in Ceará, Brazil, where communities are increasingly reliant on groundwater yet do not engage in monitoring. Despite careful implementation, uptake of monitoring within the 80 treatment communities was low. To unpack this low uptake, we conduct multimethods exploratory research. We find that uptake is less likely in communities facing high coordination costs, either within the community leadership or across the broader community. Uptake is also less likely when there are physical barriers to monitoring, when there are more substitutes for groundwater, and when there is lower variability in water availability. Our findings can inform future monitoring interventions in similar contexts worldwide.

An Informative Path Planner for a Swarm of ASVs Based on an Enhanced PSO with Gaussian Surrogate Model Components Intended for Water Monitoring Applications

Controlling the water quality of water supplies has always been a critical challenge, and water resource monitoring has become a need in recent years. Manual monitoring is not recommended in the case of large water surfaces for a variety of reasons, including expense and time consumption. In the last few years, researchers have proposed the use of autonomous vehicles for monitoring tasks. Fleets or swarms of vehicles can be deployed to conduct water resource explorations by using path planning techniques to guide the movements of each vehicle. The main idea of this work is the development of a monitoring system for Ypacarai Lake, where a fleet of autonomous surface vehicles will be guided by an improved particle swarm optimization based on the Gaussian process as a surrogate model. The purpose of using the surrogate model is to model water quality parameter behavior and to guide the movements of the vehicles toward areas where samples have not yet been collected; these areas are considered areas with high uncertainty or unexplored areas and areas with high contamination levels of the lake. The results show that the proposed approach, namely the enhanced GP-based PSO, balances appropriately the exploration and exploitation of the surface of Ypacarai Lake. In addition, the proposed approach has been compared with other techniques like the original particle swarm optimization and the particle swarm optimization with Gaussian process uncertainty component in a simulated Ypacarai Lake environment. The obtained results demonstrate the superiority of the proposed enhanced GP-based PSO in terms of mean square error with respect to the other techniques.

Influence of Hydrologic Alteration on Sediment, Dissolved Load and Nutrient Downstream Transfer Continuity in a River: Example Lower Brda River Cascade Dams (Poland)

Hydrologic alternation of river systems is an essential factor of human activity. Cascade-dammed waters are characterized by the disturbed outflow of material from the catchment. Changes in sediment, dissolved load and nutrient balance are among the base indicators of water resource monitoring. This research was based on the use of hydrological and water quality data (1984–2017) and the Indicators of Hydrologic Alteration (IHA) method to determine the influence of river regime changes on downstream transfer continuity of sediments and nutrients in the example of the Lower Brda river cascade dams (Poland). Two types of regimes were used: hydropeaking (1984–2000) and run–of–river (2001–2017). Using the IHA method and water quality data, a qualitative and quantitative relationship were demonstrated between changes of regime operation and sediment and nutrient balance. The use of sites above and below the cascade made it possible to determine sediment, dissolved load, and nutrient trapping and removing processes. Studies have shown that changes in operation regime influenced the supply chain and continuity of sediment and nutrient transport in cascade-dammed rivers. The conducted research showed that sustainable management of sediment and nutrient in the alternated catchment helps achieve good ecological status of the water.

Internet Tourism Resource Retrieval Using PageRank Search Ranking Algorithm

At present, there is a wide variety of tourism resources on the Internet. Tourism management departments must monitor these resources. At the same time, tourists must also retrieve personalized information that they are interested in. This requires a lot of time and energy. This essay studies and implements the tourism network resource monitoring system. The main work completed in the thesis proposes and constructs a topic collection algorithm and establishes a starting point, topic keywords, and a prediction mechanism. The algorithm includes three stages: the first climbing stage, the learning stage, and the continuous climbing stage. Open category directory search is used for similarity judgment and result evaluation. The experimental results show that with the continuous execution of the crawling process, the collection speed of related pages is getting faster and faster. We propose an algorithm for the extraction of wood based on the density of Internet tourism resources. The algorithm calculates the ratio of Internet tourism resource labels by row and uses a threshold extraction algorithm to distinguish area from private non-Internet tourism resource area. Experimental results show that the algorithm can successfully extract the main content of the article from a wide variety of web pages. This thesis takes the monitoring of tourism network resources as the research object and establishes a tourism network resource monitoring system, which can provide users with customizable, all-round, and real-time tourism network resource collection, extraction, and retrieval services so as to monitor tourism resources. The research results of this article can promote the construction of tourism informatization and can help users grasp the latest tourism information, thereby bringing great convenience to tourism. The system only downloads travel-related information through the use of topic collection technology, reducing the interference of irrelevant redundant web pages.