{"title":"High spatiotemporal resolution PM2.5 concentration estimation with satellite and ground observations: A case study in New York City","authors":"Yongquan Zhao, B. Huang, A. Marinoni, P. Gamba","doi":"10.1109/EE1.2018.8385255","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385255","url":null,"abstract":"High spatiotemporal resolution concentration of fine particulate matter (PM2.5) enables accurate and detailed air quality monitoring, especially for metropolitan cities with high levels of population density. Although ground air quality monitoring stations can provide timely and accurate observations, they are usually very sparsely distributed, and cannot provide PM2.5 concentration data with continuous spatial coverage. Instead, satellite observations, e.g., Landsat 8/Thermal Infrared Sensor (TIRS) and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS), can both obtain data with continuous coverage. However, there is a trade-off between satellite sensors' spatial and temporal resolution. Hence, this study presents an estimation model for PM2.5 concentrations that combines these multi-source data to produce high spatiotemporal resolution concentration maps in urban area. The approach is tested on New York City, NY, USA. Specifically, we first use cloud-free MODIS thermal band images and the corresponding ground-station PM2.5 records to build a local PM2.5 prediction model. Then, we exploit a spatiotemporal image fusion technique to obtain Landsat-like thermal band image series from Landsat 8/TIRS (100 m spatial resolution) and Terra/MODIS (1 km spatial resolution) sensors. Finally, we convert the fused high spatiotemporal resolution thermal band images to PM2.5 concentration maps by the prediction model from step 1. The validation between the estimated and the real PM2.5 values shows that the detailed Landsat-like high spatial resolution PM2.5 estimations are more accurate than the original blurred MODIS one.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134474535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michelangelo Villano, G. Krieger, K. Papathanassiou, A. Moreira
{"title":"Monitoring dynamic processes on the earth's surface using synthetic aperture radar","authors":"Michelangelo Villano, G. Krieger, K. Papathanassiou, A. Moreira","doi":"10.1109/EE1.2018.8385251","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385251","url":null,"abstract":"Synthetic aperture radar (SAR) has proven to be a key remote sensing technique for Earth observation. However, conventional SAR systems are limited in that a wide coverage can only be achieved at the expense of a degraded resolution. Staggered SAR overcomes this limitation by means of digital beamforming and continuous variation of the pulse repetition interval (PRI). Staggered SAR is currently being considered as the baseline acquisition mode of the Tandem-L mission, whose powerful instrument will deliver weekly high-resolution global images of our planet, thereby allowing quantification of a number of essential climate variables.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123934659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bandwidth extension of a 4.5 Hz geophone for seismic monitoring purpose","authors":"G. Vitale, L. Greco, A. D’Alessandro, S. Scudero","doi":"10.1109/EE1.2018.8385253","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385253","url":null,"abstract":"The devices usually employed for seismic monitoring have some limitations that prevent a complete characterization of the seismic signals, especially at the low frequency. In order to overcome such limitations we propose a relatively easy and low-cost device able to extend the bandwidth of a commercial 4.5 Hz geophone. The system basically consists in a operational amplifier with negative feedback, a buffer amplifier, and a numerical filter. The system has been specifically designed for the selected geophone, however, the idea can be easily applied to other similar devices. The low-cost of the system if compared to the manufactured expensive broadband sensor enables large-scale and/or high-density application with contained cost.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"58 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115411765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Energy efficiency for IoT devices in home environments","authors":"Paula Raymond Lutui, B. Cusack, George Maeakafa","doi":"10.1109/EE1.2018.8385277","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385277","url":null,"abstract":"The Internet of things (IoT) is a conceptual grouping of technological capabilities that enable not only the interconnectivity of useful devices but also the environmental control of useful experiences. The IoT may be viewed as a multiplicity of connected environments in which a user can control and be controlled by experiences. Environments are populated by sensors, controllers, and other objects, which are principally powered by electricity. As a consequence the growth of the IoT impacts the requirement for renewable energy and energy consumption efficiencies. In this paper we discuss optimizing energy consumption in the IoT smart environment of a home. Optimization by simple design is adopted as the best strategy for planning and regulating energy consumption.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133445206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MEMS technology in seismology: A short review","authors":"S. Scudero, A. D’Alessandro, L. Greco, G. Vitale","doi":"10.1109/EE1.2018.8385252","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385252","url":null,"abstract":"Great advancements in the broad field of the seismic monitoring have been achieved in the last decades mainly because of the technical advancement of the instrumentation. Also the seismic monitoring applications greatly developed, mainly since the 1990s owing to the Micro Electro-Mechanical Systems (MEMS) technology. In this short review we outline the applications of the MEMS technology in various sectors of broad field of seismology, distinguishing three main areas of interest and summarizing the state of the art and the most recent progresses.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114788521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reliable detection of abnormal ozone measurements using an air quality sensors network","authors":"F. Harrou, Abdelkader Dairi, Ying Sun, M. Senouci","doi":"10.1109/EE1.2018.8385265","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385265","url":null,"abstract":"Ozone pollution is one of the most important pollutants that have a negative effect on human health and the ecosystem. An effective statistical methodology to detect abnormal ozone measurements is proposed in this study. We used a Deep Belief Network model to account for nonlinear variation of ground-level ozone concentrations, in combination with a one-class support vector machine, for detecting abnormal ozone measurement. We assessed the efficiency of this methodology by using real data from a network of air quality monitoring systems in Isère, France. Results demonstrated the capability of the proposed strategy to identify abnormalities in ozone measurements.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114716282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. D’Alessandro, G. Vitale, S. Scudero, R. D'Anna, G. Passafiume, L. Greco, S. Speciale, D. Patanè, O. Torrisi, Sergio Di Prima, Salvatore Magiagli, G. Tusa
{"title":"Real-time urban seismic network and structural monitoring by means of accelerometric sensors: Application to the historic buildings of Catania (Italy)","authors":"A. D’Alessandro, G. Vitale, S. Scudero, R. D'Anna, G. Passafiume, L. Greco, S. Speciale, D. Patanè, O. Torrisi, Sergio Di Prima, Salvatore Magiagli, G. Tusa","doi":"10.1109/EE1.2018.8385254","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385254","url":null,"abstract":"A real-time urban seismic network for seismic and structural health monitoring is being installed in the city of Catania (Sicily, Italy). The 27 monitoring stations, specifically designed and assembled, equipped with a low-noise 3-axial MEMS accelerometer, are located in 23 high exposure and vulnerability buildings. In this paper we present the characteristics of the monitoring station and of the network. In case of strong seismic events, the system will provide shake maps to the emergency management centre, and will allow to assess the health conditions of the monitored buildings. The network is conceived to be further expandable over the whole historical city centre of the city of Catania.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117203796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Maratea, S. Gaglione, A. Angrisano, Giuseppe Salvi, Alessandro Nunziata
{"title":"Non parametric and robust statistics for indoor distance estimation through BLE","authors":"A. Maratea, S. Gaglione, A. Angrisano, Giuseppe Salvi, Alessandro Nunziata","doi":"10.1109/EE1.2018.8385266","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385266","url":null,"abstract":"Indoor positioning through Smart Bluetooth (Bluetooth Low Energy or BLE) sensors is a promising new field, where noisy data and outliers make challenging even the simplest distance estimates. The power of the BLE signal is known to be highly unstable even when measurement conditions remain unchanged and statistics on repeated measurements are required in order to have a good confidence in the obtained short-range distance estimates. This work proposes a stack of corrections based on non-parametric and robust statistics as a preprocessing step on the measured data, such that both the calibration and the range estimation processes improve their accuracy. According to experiments, robust and non-parametric statistics are able to handle effectively the severe noise involved in RSSI measurements, reaching most of the times a sub-meter precision.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132657305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ICT vision & strategy for a developing country harmonization of environment & engineering","authors":"Paula Raymond Lutui, B. Cusack, George Maeakafa","doi":"10.1109/EE1.2018.8385274","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385274","url":null,"abstract":"The government of Tonga has identified that ICT technologies can be used as an engine for growth. As a result, they have developed and put in place their National ICT Vision and Strategy to aid the national growth. The Tonga National e-Strategy objectives are — first is for ICT to reach individuals homes and various communities; to develop and focus on Education and improvement of skills in various domain; the e-Government initiative; focus on growing the country's economies; Provide support and enable the country's technical infrastructure; develop and update relevant legislations to ICT. A set of Goals that consist of 17 steps released by the UN, this covers a range of social and economic developments. These were created based on the accomplishments and difficulties of previous goals known as the Millennium Development Goals. This study is in two folds — one is to investigate how the Tonga National e-Strategy aligns to the UN's SDGs 17 steps. Second is to analyze the Tonga e-Government model and provide a set of recommendations.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121842495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Influence of the complexity selection method on multilayer perceptron properties: Case study on environmental data","authors":"A. Johannet, T. Darras, Dominique Bertin","doi":"10.1109/EE1.2018.8385256","DOIUrl":"https://doi.org/10.1109/EE1.2018.8385256","url":null,"abstract":"This paper investigates the way to adapt neural network design to non-Gaussian environmental data. The process of model selection is specifically investigated in order to make the model more robust. It appears that the standard method of cross-validation gains to be applied on an ensemble model, rather than a unique model, in order to apply additional regularization. Specific architectures of neural networks based on multilayer perceptron were used simultaneously with various methods of complexity selection. Prediction results on floods and droughts show that the sensitivity to the initial value of parameters could be greatly reduced. A case-study is chosen on a exceptionally complex hydrosystem, subjected to critical water resource conflicts.","PeriodicalId":173047,"journal":{"name":"2018 IEEE International Conference on Environmental Engineering (EE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125792914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}