2021
Zaragozí, Benito; Rodríguez-Sala, Jesús Javier; Trilles-Oliver, Sergio; Ramón-Morte, Alfredo
Integration of New Data Layers to Support the Land Cover and Use Information System of Spain (SIOSE): An Approach from Object-Oriented Modelling Proceedings Article
In: Geographical Information Systems Theory, Applications and Management. GISTAM 2020, pp. 85-101, Springer, Cham, 2021, ISBN: 978-3-030-76374-9.
Abstract | Links | BibTeX | Tags: Geographic Information Systems (GIS), land cover classification
@inproceedings{Zaragozi2021e,
title = {Integration of New Data Layers to Support the Land Cover and Use Information System of Spain (SIOSE): An Approach from Object-Oriented Modelling},
author = {Benito Zaragozí and Jesús Javier Rodríguez-Sala and Sergio Trilles-Oliver and Alfredo Ramón-Morte},
doi = {https://doi.org/10.1007/978-3-030-76374-9_6},
isbn = {978-3-030-76374-9},
year = {2021},
date = {2021-06-01},
booktitle = {Geographical Information Systems Theory, Applications and Management. GISTAM 2020},
volume = {1411},
pages = {85-101},
publisher = {Springer, Cham},
series = {Communications in Computer and Information Science},
abstract = {Land use and land cover (LULC) information is essential in territorial planning for the study of natural risks and landscape science. Given the importance of LULC data, increasing efforts are being focused on producing quality and easily accessible databases. In Spain, the Land Use and Cover Information System (SIOSE) is a clear example of these efforts. The SIOSE database was one of the first to be built following an object-oriented data model and a set of specifications that facilitates the integration of data from different sources. However, the SIOSE information alone is so accurate and complete that there is a usability gap that means that this data is not used to its full potential in some contexts, nor is the possibility of integrating other data sources considered. In this work, we examine the circumstances of this usability gap, its causes and consequences, and we introduce an extension of the SIOSE object-oriented data model that will enable enriching the LULC data including new useful data for different types of studies. Finally, an example of implementation of this extended model serves to encourage the user community to propose and disseminate new extended LULC datasets that facilitate various types of landscape studies.},
keywords = {Geographic Information Systems (GIS), land cover classification},
pubstate = {published},
tppubtype = {inproceedings}
}
Land use and land cover (LULC) information is essential in territorial planning for the study of natural risks and landscape science. Given the importance of LULC data, increasing efforts are being focused on producing quality and easily accessible databases. In Spain, the Land Use and Cover Information System (SIOSE) is a clear example of these efforts. The SIOSE database was one of the first to be built following an object-oriented data model and a set of specifications that facilitates the integration of data from different sources. However, the SIOSE information alone is so accurate and complete that there is a usability gap that means that this data is not used to its full potential in some contexts, nor is the possibility of integrating other data sources considered. In this work, we examine the circumstances of this usability gap, its causes and consequences, and we introduce an extension of the SIOSE object-oriented data model that will enable enriching the LULC data including new useful data for different types of studies. Finally, an example of implementation of this extended model serves to encourage the user community to propose and disseminate new extended LULC datasets that facilitate various types of landscape studies.
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 - Volume 1: GISTAM, pp. 294-301, SciTePress, 2020, ISBN: 978-989-758-425-1.
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 = {10.5220/0009579502940301},
isbn = {978-989-758-425-1},
year = {2020},
date = {2020-05-15},
booktitle = {Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM},
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},
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
Mohammed, Omar Hassan
Ecological risk assessment based on land cover change: A case of Zanzibar-Tanzania, 2003-2027 Masters Thesis
Universidade Nova De Lisboa, Lisboa, 2020.
Abstract | Links | BibTeX | Tags: land cover classification, Mastergeotech
@mastersthesis{Mohammed2020,
title = {Ecological risk assessment based on land cover change: A case of Zanzibar-Tanzania, 2003-2027},
author = {Omar Hassan Mohammed},
editor = {Pedro Cabral and Hanna Meyer and Carlos Granell-Canut (supervisors)},
url = {http://hdl.handle.net/10362/93717},
year = {2020},
date = {2020-02-28},
address = {Lisboa},
school = {Universidade Nova De Lisboa},
abstract = {Land use under improper land management is a major challenge in sub-Saharan Africa, and this has drastically affected ecological security. Addressing environmental impacts related to this major challenge requires faster and more efficient planning strategies that are based on measured information on land-use patterns. This study was employed to access the ecological risk index of Zanzibar using land cover change. We first employed Random Forest classifier to classify three Landsat images of Zanzibar for the year 2003, 2009 and 2018. And then the land change modeler was employed to simulate the land cover for Zanzibar City up to 2027 from land-use maps of 2009 and 2018 under business-as-usual and other two alternative scenarios (conservation and extreme scenario). Next, the ecological risk index of Zanzibar for each land cover was assessed based on the theories of landscape ecology and ecological risk model. The results show that the built-up areas and farmland of Zanzibar island have been increased constantly, while the natural grassland and forest cover were shrinking. The forest, agricultural and grassland have been highly fragmented into several small patches relative to the decrease in their patch areas. On the other hand, the ecological risk index of Zanzibar island has appeared to increase at a constant rate and if the current trend continues this index will increase by up to 8.9% in 2027. In comparing the three future scenarios the results show that the ERI for the conservation scenario will increase by only 4.6% which is at least 1.6% less compared to 6.2% of the business as usual, while the extreme scenario will provide a high increase of ERI of up to 8.9%. This study will help authorities to understand ecological processes and land use dynamics of various land cover classes, along with preventing unmanaged growth and haphazard development of informal housing and infrastructure.},
keywords = {land cover classification, Mastergeotech},
pubstate = {published},
tppubtype = {mastersthesis}
}
Land use under improper land management is a major challenge in sub-Saharan Africa, and this has drastically affected ecological security. Addressing environmental impacts related to this major challenge requires faster and more efficient planning strategies that are based on measured information on land-use patterns. This study was employed to access the ecological risk index of Zanzibar using land cover change. We first employed Random Forest classifier to classify three Landsat images of Zanzibar for the year 2003, 2009 and 2018. And then the land change modeler was employed to simulate the land cover for Zanzibar City up to 2027 from land-use maps of 2009 and 2018 under business-as-usual and other two alternative scenarios (conservation and extreme scenario). Next, the ecological risk index of Zanzibar for each land cover was assessed based on the theories of landscape ecology and ecological risk model. The results show that the built-up areas and farmland of Zanzibar island have been increased constantly, while the natural grassland and forest cover were shrinking. The forest, agricultural and grassland have been highly fragmented into several small patches relative to the decrease in their patch areas. On the other hand, the ecological risk index of Zanzibar island has appeared to increase at a constant rate and if the current trend continues this index will increase by up to 8.9% in 2027. In comparing the three future scenarios the results show that the ERI for the conservation scenario will increase by only 4.6% which is at least 1.6% less compared to 6.2% of the business as usual, while the extreme scenario will provide a high increase of ERI of up to 8.9%. This study will help authorities to understand ecological processes and land use dynamics of various land cover classes, along with preventing unmanaged growth and haphazard development of informal housing and infrastructure.