K. Charvát, Dmitrij Kozhukh, M. Kepka, P. Hájek, Herman Snevajs, M. Kollerová, Hana Kubícková, Tuula Löytty, Ronald Ssembajwe, Akaninyene Obot, Antoine Kantiza, Shadrack Stephene, G. Ravid, E. Gelb
{"title":"Optimization of African LULC Database for Sustainable Development","authors":"K. Charvát, Dmitrij Kozhukh, M. Kepka, P. Hájek, Herman Snevajs, M. Kollerová, Hana Kubícková, Tuula Löytty, Ronald Ssembajwe, Akaninyene Obot, Antoine Kantiza, Shadrack Stephene, G. Ravid, E. Gelb","doi":"10.23919/IST-Africa56635.2022.9845582","DOIUrl":null,"url":null,"abstract":"Land use and land cover information in combination with other thematic datasets related to detailed reference spatial data in localities from an important dataset for different types of analyses in different domains. At the time being, when it comes to the strategy of the SDG, Green Deal, Destination Earth, and construction of Earth’s digital twins, there is no model and database that would effectively gather information about the Earth’s surface in sufficient detail and complex relations. The situation is much worse in Africa compared to Europe since there exist only scattered map layers from public sources across all Africa like Africover and CCI Land Cover 2016. Moreover, the other close option ‘OpenStreetMap’ with a continent-wide coverage collects data on a voluntary basis with minimal attributes. For this reason, it’s prudent to provide validation and harmonisation of this data. Therefore, there was a focus on developing and optimising a new solution based on the Open Land Use (OLU) 2.0 data model. The OLU 2.0 database combined various thematic data with the most detailed reference geometry available. Thematic datasets were focused primarily on the information of land use and land cover and additionally on other themes like soil, topographic characteristics, climatic parameters, data from classification of remote sensing data, vegetation indices of field blocks, etc. and in different time periods. In this way, OLU4Africa 2.0 defined a model which can have large potential in Africa for high-end applications such as food security modelling; environment, biodiversity, and ecosystem protection; planning purposes; forest and water protection. It is worth mentioning that the OLU4Africa 2.0 application has been nominated among WSIS Prizes 2022.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IST-Africa Conference (IST-Africa)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/IST-Africa56635.2022.9845582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Land use and land cover information in combination with other thematic datasets related to detailed reference spatial data in localities from an important dataset for different types of analyses in different domains. At the time being, when it comes to the strategy of the SDG, Green Deal, Destination Earth, and construction of Earth’s digital twins, there is no model and database that would effectively gather information about the Earth’s surface in sufficient detail and complex relations. The situation is much worse in Africa compared to Europe since there exist only scattered map layers from public sources across all Africa like Africover and CCI Land Cover 2016. Moreover, the other close option ‘OpenStreetMap’ with a continent-wide coverage collects data on a voluntary basis with minimal attributes. For this reason, it’s prudent to provide validation and harmonisation of this data. Therefore, there was a focus on developing and optimising a new solution based on the Open Land Use (OLU) 2.0 data model. The OLU 2.0 database combined various thematic data with the most detailed reference geometry available. Thematic datasets were focused primarily on the information of land use and land cover and additionally on other themes like soil, topographic characteristics, climatic parameters, data from classification of remote sensing data, vegetation indices of field blocks, etc. and in different time periods. In this way, OLU4Africa 2.0 defined a model which can have large potential in Africa for high-end applications such as food security modelling; environment, biodiversity, and ecosystem protection; planning purposes; forest and water protection. It is worth mentioning that the OLU4Africa 2.0 application has been nominated among WSIS Prizes 2022.