2020
Zaragozí, Benito; Navarro-Carrión, J.; Rodríguez-Sala, J.; Trilles-Oliver, Sergio; Ramón-Morte, A
Improving the Usability of the Land Cover and Use Information System of Spain (SIOSE): A Proposal to Distribute New Thematic Layers and Predefined Reclassifications Proceedings Article
In: Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM), pp. 294-301, SciTePress, 2020, ISBN: 978-989-758-425-1, (2020-32).
Abstract | Links | BibTeX | Tags: land, land cover classification
@inproceedings{Zaragozí2020c,
title = {Improving the Usability of the Land Cover and Use Information System of Spain (SIOSE): A Proposal to Distribute New Thematic Layers and Predefined Reclassifications},
author = {Benito Zaragozí and J. Navarro-Carrión and J. Rodríguez-Sala and Sergio Trilles-Oliver and A Ramón-Morte},
doi = {https://doi.org/10.5220/0009579502940301},
isbn = {978-989-758-425-1},
year = {2020},
date = {2020-05-15},
urldate = {2020-05-15},
booktitle = {Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM)},
volume = {1},
pages = {294-301},
publisher = {SciTePress},
abstract = {Information on land use and land cover (LULC) is fundamental in the study and planning of human activities. In recent years, accessibility to quality geographical information has significantly increased, and this is also true for the case of LULC datasets. In Spain, the Land Cover and Use Information System of Spain (SIOSE) is concerned with harmonising access to this type of information through an object-oriented model and a series of technical specifications that regional administrations must follow. However, the information from SIOSE is so rich and complex that there is a usability gap that makes this data not exploited to its full potential in some contexts. In this communication, we analyse the context in which this usability gap occurs, its causes and consequences. Among other possible improvements, we suggest that enriching the SIOSE database with new thematic information would make its use more attractive and reduce the usability gap for less expert users. We propose an extension to the SIOSE object-oriented data model that will make it possible to enrich the LULC data with new data that are useful for various types of studies},
note = {2020-32},
keywords = {land, land cover classification},
pubstate = {published},
tppubtype = {inproceedings}
}
Information on land use and land cover (LULC) is fundamental in the study and planning of human activities. In recent years, accessibility to quality geographical information has significantly increased, and this is also true for the case of LULC datasets. In Spain, the Land Cover and Use Information System of Spain (SIOSE) is concerned with harmonising access to this type of information through an object-oriented model and a series of technical specifications that regional administrations must follow. However, the information from SIOSE is so rich and complex that there is a usability gap that makes this data not exploited to its full potential in some contexts. In this communication, we analyse the context in which this usability gap occurs, its causes and consequences. Among other possible improvements, we suggest that enriching the SIOSE database with new thematic information would make its use more attractive and reduce the usability gap for less expert users. We propose an extension to the SIOSE object-oriented data model that will make it possible to enrich the LULC data with new data that are useful for various types of studies
Achieng, Annette
Effect of land use land cover changes on carbon sequestration in Germany Masters Thesis
UNL, Lisboa, 2020, (2020-28).
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},
urldate = {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.},
note = {2020-28},
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.