2023
Hammad, Sahibzada Saadoon; Iskandaryan, Ditsuhi; Trilles-Oliver, Sergio
An unsupervised TinyML approach applied to the detection of urban noise anomalies under the smart cities environment Journal Article
In: Internet of Things, vol. 23, pp. 100848, 2023, ISSN: 2542-6605.
Abstract | Links | BibTeX | Tags: environmental monitoring, machine learning, TinyML
@article{Saadoon2023a,
title = {An unsupervised TinyML approach applied to the detection of urban noise anomalies under the smart cities environment},
author = {Sahibzada Saadoon Hammad and Ditsuhi Iskandaryan and Sergio Trilles-Oliver},
doi = {10.1016/j.iot.2023.100848},
issn = {2542-6605},
year = {2023},
date = {2023-10-01},
journal = {Internet of Things},
volume = {23},
pages = {100848},
abstract = {Artificial Intelligence of Things (AIoT) is an emerging area of interest, and this can be used to obtain knowledge and take better decisions in the same Internet of Things (IoT) devices. IoT data are prone to anomalies due to various factors such as malfunctioning of sensors, low-cost devices, etc. Following the AIoT paradigm, this work explores anomaly detection in IoT urban noise sensor networks using a Long Short-Term Memory Autoencoder. Two autoencoder models are trained using normal data from two different sensors in the sensor network and tested for the detection of two different types of anomalies, i.e. point anomalies and collective anomalies. The results in terms of accuracy of the two models are 99.99% and 99.34%. The trained model is quantised, converted to TensorFlow Lite format and deployed on the ESP32 microcontroller (MCU). The inference time on the microcontroller is 4 ms for both models, and the power consumption of the MCU is 0.2693 W ± 0.039 and 0.3268 W ± 0.015. Heap memory consumption during the execution of the program for sensors TA120-T246187 and TA120-T246189 is 528 bytes and 744 bytes respectively.},
keywords = {environmental monitoring, machine learning, TinyML},
pubstate = {published},
tppubtype = {article}
}
Artificial Intelligence of Things (AIoT) is an emerging area of interest, and this can be used to obtain knowledge and take better decisions in the same Internet of Things (IoT) devices. IoT data are prone to anomalies due to various factors such as malfunctioning of sensors, low-cost devices, etc. Following the AIoT paradigm, this work explores anomaly detection in IoT urban noise sensor networks using a Long Short-Term Memory Autoencoder. Two autoencoder models are trained using normal data from two different sensors in the sensor network and tested for the detection of two different types of anomalies, i.e. point anomalies and collective anomalies. The results in terms of accuracy of the two models are 99.99% and 99.34%. The trained model is quantised, converted to TensorFlow Lite format and deployed on the ESP32 microcontroller (MCU). The inference time on the microcontroller is 4 ms for both models, and the power consumption of the MCU is 0.2693 W ± 0.039 and 0.3268 W ± 0.015. Heap memory consumption during the execution of the program for sensors TA120-T246187 and TA120-T246189 is 528 bytes and 744 bytes respectively.
2020
Achieng, Annette
Effect of land use land cover changes on carbon sequestration in Germany Masters Thesis
UNL, Lisboa, 2020.
Abstract | Links | BibTeX | Tags: environmental monitoring, land, Mastergeotech
@mastersthesis{Achieng2020,
title = {Effect of land use land cover changes on carbon sequestration in Germany},
author = {Annette Achieng},
editor = {Pedro da Costa Brito Cabral and Judith Vergstegen and Sergio Trilles-Oliver (supervisors)},
url = {http://hdl.handle.net/10362/93644},
year = {2020},
date = {2020-02-27},
address = {Lisboa},
school = {UNL},
abstract = {Using carbon sequestration as an indicator for environmental health, it is possible to assess whether a country is on its way to achieving carbon neutrality in the Land Use, Land-Use Change and Forestry (LULUCF) sector. A great deal of research has been conducted to find out whether there is a relationship between LULC and carbon sequestration. In this paper we explore several scenarios and compare how much carbon would be stored under each of them. In addition, this research aims to find out how best the LULUCF sector can contribute towards a country’s goals in achieving carbon neutrality. This was conducted using two models; Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, which calculates the amount of carbon stored in a landscape and TerrSet’s Land Change Modeller, which uses a combination of neural networks and CA Markov to project future Land Use Land Cover (LULC) scenarios. From the documentation of the carbon trend over the 28-year period using the InVEST model, the study finds that between the years of 1990 and 2018, the amount of carbon stored increased by 0.15%. Under the Business as Usual scenario projection there is an increase of 0.22% by the year 2048. In the development scenario we see a decrease of 0.96% and finally in the two conservation scenarios the carbon stock increases by 4.16% and 0.41% respectively. These results suggest that the scenario which would be most beneficial to Germany would be the first conservation scenario. The results of this study highlight the importance of the LULUCF sector in mitigating climate change. Therefore, they can be used to provide informed decision making to spatial planners and land management stakeholders during the development of future land use planning policies.},
keywords = {environmental monitoring, land, Mastergeotech},
pubstate = {published},
tppubtype = {mastersthesis}
}
Using carbon sequestration as an indicator for environmental health, it is possible to assess whether a country is on its way to achieving carbon neutrality in the Land Use, Land-Use Change and Forestry (LULUCF) sector. A great deal of research has been conducted to find out whether there is a relationship between LULC and carbon sequestration. In this paper we explore several scenarios and compare how much carbon would be stored under each of them. In addition, this research aims to find out how best the LULUCF sector can contribute towards a country’s goals in achieving carbon neutrality. This was conducted using two models; Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, which calculates the amount of carbon stored in a landscape and TerrSet’s Land Change Modeller, which uses a combination of neural networks and CA Markov to project future Land Use Land Cover (LULC) scenarios. From the documentation of the carbon trend over the 28-year period using the InVEST model, the study finds that between the years of 1990 and 2018, the amount of carbon stored increased by 0.15%. Under the Business as Usual scenario projection there is an increase of 0.22% by the year 2048. In the development scenario we see a decrease of 0.96% and finally in the two conservation scenarios the carbon stock increases by 4.16% and 0.41% respectively. These results suggest that the scenario which would be most beneficial to Germany would be the first conservation scenario. The results of this study highlight the importance of the LULUCF sector in mitigating climate change. Therefore, they can be used to provide informed decision making to spatial planners and land management stakeholders during the development of future land use planning policies.
Chakraborty, Tanmoy
Multi-scale assessment of drought-induced forest dieback Masters Thesis
Universidade Nova De Lisboa, Lisboa, 2020.
Abstract | Links | BibTeX | Tags: environmental monitoring, Mastergeotech, Remote sensing
@mastersthesis{Chakraborty2020,
title = {Multi-scale assessment of drought-induced forest dieback },
author = {Tanmoy Chakraborty},
editor = {Hanna Meyer and Torsten Prinz and Carlos Granell-Canut (supervisors)
},
url = {http://hdl.handle.net/10362/94403},
year = {2020},
date = {2020-01-31},
address = {Lisboa},
school = {Universidade Nova De Lisboa},
abstract = {Drought has been intensified over the years and will continue to worsen due to climate change. Existing works have focused their attention on crops rather than forests. Adverse effects are felt by all flora and fauna but the impact of the recent droughts on forest ecosystems is still unknown. Greater root depth allows them to withstand the immediate impacts of drought in contrast to crops and other vegetation. This study aims to see not only the interaction between drought and forest vitality from a multi-scale and temporal viewpoint while also to detect the impact of the recent 2018/19 drought on forest vitality based on remote sensing data. The data from the German Drought Monitor was used for the area-wide estimation of drought in Germany. Vegetative indices like NDVI collected from MODIS and Sentinel 2A were used to study the interactions between drought and forest vitality. Data for both have been acquired for the years 2000-2019. A long-standing time series data was decomposed and seasonally adjusted for better cross-correlation between the variables. The cross-correlation was verified by using breakpoints estimation by dividing the data into historically observed and test data. The coniferous-dominated black forest was used as a study area for a more in-depth analysis. Results showed that forest vitality was lowest one month after a severe drought, indicated by the highest decline in NDVI for all the forest types. This was verified using high resolution Sentinel images and the highest change does correspond to the month of January 2019. There was change in NDVI of over -0.5 for 80.63% of the entire study area. The change for each forest type was 81.74%, 54.42%, 84.14% for coniferous, broadleaved and mixed forests respectively. Two decades of NDVI and Soil Moisture Index (SMI) data along with Sentinel images for better area calculation because of higher resolution make this a highly effective approach to assess the impacts of drought on forest dieback. The methodology and data can be applied across the study area and with suitable drought indices can be used to assess the drought induced forest dieback across the globe. However, in-situ analysis with ecological considerations at the individual level could further the validity of the cross-correlations among forest types and drought. Reproducibility self-assessment (https://osf.io/j97zp/): 3, 2, 3, 1, 3 (input data, pre-processing, methods, computational environment, results).},
keywords = {environmental monitoring, Mastergeotech, Remote sensing},
pubstate = {published},
tppubtype = {mastersthesis}
}
Drought has been intensified over the years and will continue to worsen due to climate change. Existing works have focused their attention on crops rather than forests. Adverse effects are felt by all flora and fauna but the impact of the recent droughts on forest ecosystems is still unknown. Greater root depth allows them to withstand the immediate impacts of drought in contrast to crops and other vegetation. This study aims to see not only the interaction between drought and forest vitality from a multi-scale and temporal viewpoint while also to detect the impact of the recent 2018/19 drought on forest vitality based on remote sensing data. The data from the German Drought Monitor was used for the area-wide estimation of drought in Germany. Vegetative indices like NDVI collected from MODIS and Sentinel 2A were used to study the interactions between drought and forest vitality. Data for both have been acquired for the years 2000-2019. A long-standing time series data was decomposed and seasonally adjusted for better cross-correlation between the variables. The cross-correlation was verified by using breakpoints estimation by dividing the data into historically observed and test data. The coniferous-dominated black forest was used as a study area for a more in-depth analysis. Results showed that forest vitality was lowest one month after a severe drought, indicated by the highest decline in NDVI for all the forest types. This was verified using high resolution Sentinel images and the highest change does correspond to the month of January 2019. There was change in NDVI of over -0.5 for 80.63% of the entire study area. The change for each forest type was 81.74%, 54.42%, 84.14% for coniferous, broadleaved and mixed forests respectively. Two decades of NDVI and Soil Moisture Index (SMI) data along with Sentinel images for better area calculation because of higher resolution make this a highly effective approach to assess the impacts of drought on forest dieback. The methodology and data can be applied across the study area and with suitable drought indices can be used to assess the drought induced forest dieback across the globe. However, in-situ analysis with ecological considerations at the individual level could further the validity of the cross-correlations among forest types and drought. Reproducibility self-assessment (https://osf.io/j97zp/): 3, 2, 3, 1, 3 (input data, pre-processing, methods, computational environment, results).
2018
Smid, Marek
Climate change and impacts in the urban systems PhD Thesis
Universidade Nova de Lisboa. Information management school, 2018.
BibTeX | Tags: environmental monitoring, GEO-C, Smart Cities
@phdthesis{Smid2018,
title = {Climate change and impacts in the urban systems},
author = {Marek Smid},
editor = {Ana Cristina Costa and Edzer Pebesma and Carlos Granell-Canut (supervisors)
},
year = {2018},
date = {2018-11-28},
address = {Lisboa},
school = {Universidade Nova de Lisboa. Information management school},
keywords = {environmental monitoring, GEO-C, Smart Cities},
pubstate = {published},
tppubtype = {phdthesis}
}
Twesigye, Anthony
Improving public health in smart cities in the air pollution context Masters Thesis
Departamento de Lenguajes y Sistemas Informáticos, Castellón, 2018.
BibTeX | Tags: environmental monitoring, Mastergeotech, Smart Cities
@mastersthesis{Twesigye2018,
title = {Improving public health in smart cities in the air pollution context},
author = {Anthony Twesigye},
editor = {Francisco Ramos-Romero and Ana Cristina Costa and Judith Verstegen},
year = {2018},
date = {2018-03-02},
address = {Castellón},
school = {Departamento de Lenguajes y Sistemas Informáticos},
keywords = {environmental monitoring, Mastergeotech, Smart Cities},
pubstate = {published},
tppubtype = {mastersthesis}
}
Nišić, Nikolina
Monitoring the environmental impacts and risks of the quarry blasts on the surrounding area using the UAV and Landsat imagery by testing the different classifiers Masters Thesis
Departamento de Lenguajes y Sistemas Informáticos, Castellón, 2018.
BibTeX | Tags: environmental monitoring, Mastergeotech, satellite images
@mastersthesis{Nišić2018,
title = {Monitoring the environmental impacts and risks of the quarry blasts on the surrounding area using the UAV and Landsat imagery by testing the different classifiers},
author = {Nikolina Nišić},
editor = {Roberto André Pereira and Edzer Pebesma and Joaquín Torres-Sospedra (supervisors)},
year = {2018},
date = {2018-02-27},
address = {Castellón},
school = {Departamento de Lenguajes y Sistemas Informáticos},
keywords = {environmental monitoring, Mastergeotech, satellite images},
pubstate = {published},
tppubtype = {mastersthesis}
}
2017
Trilles-Oliver, Sergio; Calia, Andrea; Belmonte, Óscar; Torres-Sospedra, Joaquín; Montoliu, Raul; and, Joaquín Huerta-Guijarro
Deployment of an open sensorized platform in a smart city context Journal Article
In: Future Generation Computer Systems, vol. 76, pp. 221-233, 2017, ISSN: 0167-739X.
Abstract | Links | BibTeX | Tags: environmental monitoring, GEOEvent, GIScience, Internet of things, Open-hardware, senviro, Smart Cities
@article{Trilles2017,
title = {Deployment of an open sensorized platform in a smart city context },
author = {Sergio Trilles-Oliver and Andrea Calia and Óscar Belmonte and Joaquín Torres-Sospedra and Raul Montoliu and Joaquín Huerta-Guijarro and
},
doi = {http://dx.doi.org/10.1016/j.future.2016.11.005},
issn = {0167-739X},
year = {2017},
date = {2017-02-28},
journal = {Future Generation Computer Systems},
volume = {76},
pages = {221-233},
abstract = {The race to achieve smart cities is producing a continuous effort to adapt new developments and knowledge, for administrations and citizens. Information and Communications Technology are called on to be one of the key players to get these cities to use smart devices and sensors (Internet of Things) to know at every moment what is happening within the city, in order to make decisions that will improve the management of resources. The proliferation of these “smart things” is producing significant deployment of networks in the city context. Most of these devices are proprietary solutions, which do not offer free access to the data they provide. Therefore, this prevents the interoperability and compatibility of these solutions in the current smart city developments.
This paper presents how to embed an open sensorized platform for both hardware and software in the context of a smart city, more specifically in a university campus. For this integration, GIScience comes into play, where it offers different open standards that allow full control over “smart things” as an agile and interoperable way to achieve this. To test our system, we have deployed a network of different sensorized platforms inside the university campus, in order to monitor environmental phenomena.},
keywords = {environmental monitoring, GEOEvent, GIScience, Internet of things, Open-hardware, senviro, Smart Cities},
pubstate = {published},
tppubtype = {article}
}
The race to achieve smart cities is producing a continuous effort to adapt new developments and knowledge, for administrations and citizens. Information and Communications Technology are called on to be one of the key players to get these cities to use smart devices and sensors (Internet of Things) to know at every moment what is happening within the city, in order to make decisions that will improve the management of resources. The proliferation of these “smart things” is producing significant deployment of networks in the city context. Most of these devices are proprietary solutions, which do not offer free access to the data they provide. Therefore, this prevents the interoperability and compatibility of these solutions in the current smart city developments.
This paper presents how to embed an open sensorized platform for both hardware and software in the context of a smart city, more specifically in a university campus. For this integration, GIScience comes into play, where it offers different open standards that allow full control over “smart things” as an agile and interoperable way to achieve this. To test our system, we have deployed a network of different sensorized platforms inside the university campus, in order to monitor environmental phenomena.
This paper presents how to embed an open sensorized platform for both hardware and software in the context of a smart city, more specifically in a university campus. For this integration, GIScience comes into play, where it offers different open standards that allow full control over “smart things” as an agile and interoperable way to achieve this. To test our system, we have deployed a network of different sensorized platforms inside the university campus, in order to monitor environmental phenomena.
Trilles-Oliver, Sergio; Belmonte-Fernández, Óscar; Schade, Sven; Huerta-Guijarro, Joaquín
A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data Journal Article
In: International Journal of Digital Earth, vol. 10, no. 1, pp. 103-120, 2017, ISSN: 1753-8947.
Abstract | BibTeX | Tags: environmental monitoring, Internet of things, Real time analysis, real-time sensor streams
@article{TrillesOliver16,
title = {A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data},
author = { Sergio Trilles-Oliver and Óscar Belmonte-Fernández and Sven Schade and Joaquín Huerta-Guijarro},
issn = {1753-8947},
year = {2017},
date = {2017-01-01},
journal = {International Journal of Digital Earth},
volume = {10},
number = {1},
pages = {103-120},
abstract = {Pushed by the Internet of Things (IoT) paradigm modern sensor networks monitor a wide range of phenomena, in areas such as environmental monitoring, health care, industrial processes, and smart cities. These networks provide a continuous pulse of the almost infinite activities that are happening in the physical space and are thus, key enablers for a Digital Earth Nervous System. Nevertheless, the rapid processing of these sensor data streams still continues to challenge traditional data handling solutions and new approaches are being requested. We propose a generic answer to this challenge, which has the potential to support any form of distributed real-time analysis. This neutral methodology follows a brokering approach to work with different kinds of data sources and uses web-based standards to achieve interoperability. As a proof of concept, we implemented the methodology to detect anomalies in real-time and applied it to the area of environmental monitoring. The developed system is capable of detecting anomalies, generating notifications, and displaying the recent situation to the user.},
keywords = {environmental monitoring, Internet of things, Real time analysis, real-time sensor streams},
pubstate = {published},
tppubtype = {article}
}
Pushed by the Internet of Things (IoT) paradigm modern sensor networks monitor a wide range of phenomena, in areas such as environmental monitoring, health care, industrial processes, and smart cities. These networks provide a continuous pulse of the almost infinite activities that are happening in the physical space and are thus, key enablers for a Digital Earth Nervous System. Nevertheless, the rapid processing of these sensor data streams still continues to challenge traditional data handling solutions and new approaches are being requested. We propose a generic answer to this challenge, which has the potential to support any form of distributed real-time analysis. This neutral methodology follows a brokering approach to work with different kinds of data sources and uses web-based standards to achieve interoperability. As a proof of concept, we implemented the methodology to detect anomalies in real-time and applied it to the area of environmental monitoring. The developed system is capable of detecting anomalies, generating notifications, and displaying the recent situation to the user.
2014
García-Martí, Irene; Torres-Sospedra, Joaquín; Rodríguez-Pupo, Luis Enrique
A comparative study on VGI and professional noise data Proceedings Article
In: Huerta-Guijarro, Joaquín; Schade, Sven; Granell-Canut, Carlos (Ed.): Connecting a Digital Europe through Location and Place. Proceedings of the AGILE'2014 International Conference on Geographic Information Science., AGILE Digital Editions, 2014, ISBN: 978-90-816960-4-3.
Abstract | Links | BibTeX | Tags: Citizen Science, crowdsourcing, environmental monitoring, Geographic Information, noise pollution, Smart Cities, VGI
@inproceedings{GarciaMarti2014,
title = {A comparative study on VGI and professional noise data},
author = { Irene García-Martí and Joaquín Torres-Sospedra and Luis Enrique Rodríguez-Pupo},
editor = {Joaquín Huerta-Guijarro and Sven Schade and Carlos Granell-Canut},
url = {http://repositori.uji.es/xmlui/handle/10234/98489},
isbn = {978-90-816960-4-3},
year = {2014},
date = {2014-01-01},
booktitle = {Connecting a Digital Europe through Location and Place. Proceedings of the AGILE'2014 International Conference on Geographic Information Science.},
publisher = {AGILE Digital Editions},
abstract = {The ubiquitous nature of mobile devices and its growing presence in urban areas, turn them up into low cost environmental monitoring platforms. In this field, several authors made different efforts to provide alternatives to Sensor Networks, to assess noise pollution in cities using crowdsourcing techniques. In this sense, citizens might potentially produce large spatio-temporal datasets using their mobile devices to measure noise levels. There are few attempts of assessing the quality of the mobile noise samples on a real scenario and compare them to commercial data to evaluate if they are reliable enough. This contribution reviews the existing applications to collect or assess the quality of noise samples when they are used as sound level meters. Moreover, it presents the results of our experiment: the volunteer noise dataset generated in a ‘mapping party' on our campus is compared to professional data. Results show that VGI data might be sufficient for multiple daily situations.},
keywords = {Citizen Science, crowdsourcing, environmental monitoring, Geographic Information, noise pollution, Smart Cities, VGI},
pubstate = {published},
tppubtype = {inproceedings}
}
The ubiquitous nature of mobile devices and its growing presence in urban areas, turn them up into low cost environmental monitoring platforms. In this field, several authors made different efforts to provide alternatives to Sensor Networks, to assess noise pollution in cities using crowdsourcing techniques. In this sense, citizens might potentially produce large spatio-temporal datasets using their mobile devices to measure noise levels. There are few attempts of assessing the quality of the mobile noise samples on a real scenario and compare them to commercial data to evaluate if they are reliable enough. This contribution reviews the existing applications to collect or assess the quality of noise samples when they are used as sound level meters. Moreover, it presents the results of our experiment: the volunteer noise dataset generated in a ‘mapping party' on our campus is compared to professional data. Results show that VGI data might be sufficient for multiple daily situations.
2012
Tamayo-Fong, Alain; Granell-Canut, Carlos; Huerta-Guijarro, Joaquín
Using SWE Standards for Ubiquitous Environmental Sensing: A Performance Analysis Journal Article
In: Sensors, vol. 12, pp. 12026–12051, 2012, ISSN: 1424-8220, (IF: 1.939, Q1).
Abstract | Links | BibTeX | Tags: environmental monitoring, GEOCLOUD, OSMOSIS, Sensors, Standards
@article{TamayoFong2012a,
title = {Using SWE Standards for Ubiquitous Environmental Sensing: A Performance Analysis},
author = { Alain Tamayo-Fong and Carlos Granell-Canut and Joaquín Huerta-Guijarro},
url = {http://hdl.handle.net/10234/62253},
doi = {10.3390/s120912026},
issn = {1424-8220},
year = {2012},
date = {2012-08-01},
journal = {Sensors},
volume = {12},
pages = {12026--12051},
abstract = {Although smartphone applications represent the most typical data consumer tool from the citizen perspective in environmental applications, they can also be used for in-situ data collection and production in varied scenarios, such as geological sciences and biodiversity. The use of standard protocols, such as SWE, to exchange information between smartphones and sensor infrastructures brings benefits such as interoperability and scalability, but their reliance on XML is a potential problem when large volumes of data are transferred, due to limited bandwidth and processing capabilities on mobile phones. In this article we present a performance analysis about the use of SWE standards in smartphone applications to consume and produce environmental sensor data, analysing to what extent the performance problems related to XML can be alleviated by using alternative uncompressed and compressed formats.},
note = {IF: 1.939, Q1},
keywords = {environmental monitoring, GEOCLOUD, OSMOSIS, Sensors, Standards},
pubstate = {published},
tppubtype = {article}
}
Although smartphone applications represent the most typical data consumer tool from the citizen perspective in environmental applications, they can also be used for in-situ data collection and production in varied scenarios, such as geological sciences and biodiversity. The use of standard protocols, such as SWE, to exchange information between smartphones and sensor infrastructures brings benefits such as interoperability and scalability, but their reliance on XML is a potential problem when large volumes of data are transferred, due to limited bandwidth and processing capabilities on mobile phones. In this article we present a performance analysis about the use of SWE standards in smartphone applications to consume and produce environmental sensor data, analysing to what extent the performance problems related to XML can be alleviated by using alternative uncompressed and compressed formats.
Kamberov, Rustam
Decision-making utilizing a Web GIS to Monitor Hazardous Industrial Emissions in the Valencian community of Spain Masters Thesis
Universitat Jaume I, 2012.
BibTeX | Tags: environmental monitoring, Geographic Information Systems (GIS)
@mastersthesis{Kamberov,
title = {Decision-making utilizing a Web GIS to Monitor Hazardous Industrial Emissions in the Valencian community of Spain},
author = { Rustam Kamberov},
editor = {Laura Díaz-Sánchez (supervisor) and Eduard Pultar (co-supervisor) and Miguel Neto (co-supervisor)},
year = {2012},
date = {2012-01-01},
school = {Universitat Jaume I},
keywords = {environmental monitoring, Geographic Information Systems (GIS)},
pubstate = {published},
tppubtype = {mastersthesis}
}
Clarck-López, Sergio
GIS capacity building for risk management to help developing countries: Case of climate change problem in Amhara rural region (Ethiopia) Masters Thesis
Universitat Jaume I, 2012.
BibTeX | Tags: Disaster management, environmental monitoring, Geographic Information Systems (GIS)
@mastersthesis{Lopez2012,
title = {GIS capacity building for risk management to help developing countries: Case of climate change problem in Amhara rural region (Ethiopia)},
author = { Sergio Clarck-López},
editor = {Joaquín Huerta-Guijarro (supervisor) and Marco Painho (co-supervisor) and Pau Aragó-Galindo (co-supervisor)},
year = {2012},
date = {2012-01-01},
school = {Universitat Jaume I},
keywords = {Disaster management, environmental monitoring, Geographic Information Systems (GIS)},
pubstate = {published},
tppubtype = {mastersthesis}
}
Mcinerney, Daniel; Revez, Gonçalo; Bastin, Lucy; Barredo, José I.; Díaz-Sánchez, Laura; Bastin, Lucy; Figueiredo, Carlos; San-Miguel, Jesús
Web-based Forest Monitoring Tools Using OGC Services Proceedings Article
In: Eurogeoss Conference. Madrid, 25-27 January 2012, 2012.
Abstract | BibTeX | Tags: environmental monitoring, EUROGEOSS, forest fire, OGC
@inproceedings{Mcinerney2012b,
title = {Web-based Forest Monitoring Tools Using OGC Services},
author = { Daniel Mcinerney and Gonçalo Revez and Lucy Bastin and José I. Barredo and Laura Díaz-Sánchez and Lucy Bastin and Carlos Figueiredo and Jesús San-Miguel},
year = {2012},
date = {2012-01-01},
booktitle = {Eurogeoss Conference. Madrid, 25-27 January 2012},
abstract = {There is an increasing demand for consistent and harmonised forest and environmental information at a range of spatial scales from local through to regional and global. These data are necessary for forest management and planning, but they are also inherently linked to multi-disciplinary research relating to natural hazards, climate change, land management and biodiversity. With these issues in mind, the EuroGEOSS project aims to demonstrate the added value of making existing systems and applications interoperable and used within the GEOSS and INSPIRE frameworks. This presentation focuses on the development of the Web-based forest operating capacities and their interactions with the developments of the advance operating capacities such as the EuroGEOSS Discovery Broker and other thematic areas that include biodiversity and droughts. It specifically highlights the development of an interoperable web application that integrates interoperable components such as a map client and metadata catalogue that supports bidirectional data exchange between both systems. In addition, it presents advanced forest modeling and monitoring capabilities that are developed as Web Processing Services (WPS) based on forestry, biodiversity and climatic data published using OGC Web Services (OWS) that include Web Feature Services (WFS) and Web Coverage Services (WCS). Furthermore, we present the integration of the GEOSS Service Factory WPS into the forestry workflows for content publication capabilities as well as the potential use of geo-referenced Web2.0 resources.},
keywords = {environmental monitoring, EUROGEOSS, forest fire, OGC},
pubstate = {published},
tppubtype = {inproceedings}
}
There is an increasing demand for consistent and harmonised forest and environmental information at a range of spatial scales from local through to regional and global. These data are necessary for forest management and planning, but they are also inherently linked to multi-disciplinary research relating to natural hazards, climate change, land management and biodiversity. With these issues in mind, the EuroGEOSS project aims to demonstrate the added value of making existing systems and applications interoperable and used within the GEOSS and INSPIRE frameworks. This presentation focuses on the development of the Web-based forest operating capacities and their interactions with the developments of the advance operating capacities such as the EuroGEOSS Discovery Broker and other thematic areas that include biodiversity and droughts. It specifically highlights the development of an interoperable web application that integrates interoperable components such as a map client and metadata catalogue that supports bidirectional data exchange between both systems. In addition, it presents advanced forest modeling and monitoring capabilities that are developed as Web Processing Services (WPS) based on forestry, biodiversity and climatic data published using OGC Web Services (OWS) that include Web Feature Services (WFS) and Web Coverage Services (WCS). Furthermore, we present the integration of the GEOSS Service Factory WPS into the forestry workflows for content publication capabilities as well as the potential use of geo-referenced Web2.0 resources.